Recently, my partner, Criscillia, and I demonstrated that truth mathematically, by understanding that the information brains need for trust is not the kind of information you find in newspapers or books. It is the kind of information we receive through our senses: sight, sound, smell, taste, touch and interoception, all at once. Real people know nervous systems need real life.

That same math shows that digital inputs are bad for us. The more “personalized” they are, the worse. Because personalized digital technology makes so much money, that basic tension pits private profit against public health. I have never heard any scientific disagreements with this contention, even after trying for a decade to provoke them. The math of information flow and all unbiased evidence agree: Digital media damage learning and sociability. So any country hoping to protect its youth must severely limit childrens’ digital exposure.

The United States, which pioneered this awful tech and makes the most money from it, must now officially face this choice just as Trump takes office. The Senate side of Congress already passed the Kids Online Safety Act (KOSA) — a proposed legislation meant to protect children on the Internet — by the lopsided odds of 91–3, showing wide bipartisan support. But the House of Representatives has stalled and tried to weaken it to make it easier on industry.

The House will vote on KOSA on Tuesday, December 17. Will the congressmen protect kids from known digital toxins? Or will they protect their contributors’ profit margins? It seems too close to call.

KOSA vs free speech

The big news came this week when Trump’s tech vizier, Elon Musk, the world’s most influential technologist, announced his support of KOSA. Even more crucially, he and X CEO Linda Yaccarino helped the House restore the teeth of the Senate version. He and his tech company voted for life over tech.

Unlike earlier bills, KOSA was designed to identify and neutralize the toxin, not just give it a name and a punishment. The toxin in this case is described in the key term, “design feature.” Design features are software elements (such as “infinite scroll,” for example) which entrain the human nervous system unconsciously; individuals can’t defend themselves. Their basic structures have been mathematically understood since the old days when “persuasive technology” was considered good, not evil. KOSA’s genius approach embeds that established industry knowledge into the very legislation regulating industry and protecting kids and teens.

The major objection to KOSA is based on a weird US myth, going by the name “free speech.” Free speech in the US means people get to speak their minds without government interference, which is good for democracy. Furthermore, according to our scientific understanding of trust, speaking out loud in public is very good for the nervous system. So what our Founding Fathers imagined is still alive and well.

Unfortunately, the US also has a sub-population of people who think that typing posts is equal to using the voice. Some of those people further claim that free speech ought to apply in ways having nothing to do with voices or even people, so any regulation at all constitutes “censorship.”

The people who say such things call themselves intelligent. But does a foreign server hosting porn deserve free speech? How about social media platforms urging kids to kill themselves?

Musk was right: Choose life. Science says so.

[Lee Thompson-Kolar edited this piece.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Elon Musk Chooses Life (and Science) Over Tech appeared first on Fair Observer.

In his lecture, Hopfield showed diagrams of networks now called “Hopfield networks.” Bell Labs was hosting a Hopfield network day honoring him and his new-fangled ideas of using relaxation-energy equations from physics to design networks that “solved” certain difficult problems. Some of his diagrams looked just like the operational amplifiers (op-amps) in electronic circuit diagrams, which I had tinkered with for years — but now he called them neurons. So, my skill at making circuits now applied to brains. I was hooked, and within three years I was accepted as a student in the brand-new academic program called Computation and Neural Systems (CNS) that Hopfield was founding at the California Institute of Technology (Caltech).

An example of a Hopfield network with four nodes. Via Zawersh on English Wikipedia (CC BY-SA 3.0).

I attended Caltech in the CNS program’s second year. The first words I heard in a classroom were from Hopfield: roughly, “If you can explain how you do something, say solve an equation, odds are computers can already do it better. If you have no idea how you do it, say how you recognize your mother’s voice, odds are we have no idea how it works, and computers can’t get close.” That insight explains, among other things, why computers are better at following rules than at making sense of real life.

Hopfield himself was imposing, in a grandfatherly way. Six feet tall, he seemed even taller when tipping back on his heels, clasping his hands, looking benignly down his nose and speaking in a booming bass voice. When graduate student Mike Vanier performed an imitation of Hopfield in a skit during our first year, it brought down the house. 

That core class Hopfield taught on Neural Nets (in 1988) was difficult in an epic way. Homework for the very first week — the same week students were still getting computer accounts and finding the bookstore — involved a set of three different kinds of supremely hard problems: solving a difficult set of differential equations, writing and testing a computer program to simulate a simple neural circuit and constructing that same working “neural” circuit by wiring a battery, op-amps, resistors and capacitors up to blink LEDs. Neither programming nor soldering was a stated class requirement. Lucky for me, I already knew how to program and build circuits, so I passed.

In fact, the little circuit I built in Hopfield’s class proved to be a key to my PhD project, and key to his final question for me. Hopfield sat on my committee and approved my thesis — even though I had proved that real neurons can’t possibly operate like those circuits. (Real neurons have to be hundreds-fold faster, at least.)

An interdisciplinary paradise

By world standards, Caltech is a tiny and very exclusive university, having only about a thousand undergrad and another thousand graduate students. Caltech specializes in leading scientific trends; the new CNS program (started with silicon guru Carver Mead) was meant to create an entirely new field by using mathematical techniques from physics, electronics and computer science to understand how information moves in biological systems like brains, muscles, eyes and ears.

Psychology, psychophysics, optics, silicon design, algorithms, neuroscience, robotics — a score of scientific disciplines overlapped in lecture halls, classrooms and labs. It was an interdisciplinary paradise. Caltech’s philosophy is to base nearly everything (even biology) on physics principles. Hopfield and Mead’s common treatment of biological information processing as continuous equation accessible to physics, following in this tradition, made the CNS program a scientific innovation.

Hopfield’s contribution to physics, and to science in general, was to link well-established math about molecules and crystals to poorly understood computation problems like parallel processing and machine intelligence. His key scientific invention (the Hopfield network) was complex enough to solve real and interesting AI-like problems but simple enough to explain through equations initially designed to describe crystal formation. Hopfield created a whole new form of analog computation with his nets and a whole new way of describing neurons with the math behind them.

(While they make the math easier, it turns out that Hopfield’s smoothly responding mathematical “neurons” are nothing like real neurons in brains. Real neurons make irregular pulses whose noisy crackle must, in fact, carry information — a point first made in my dissertation under Christof Koch. [You can read the PDF here.] This fact undermines the one thing neuroscience thought it knew about the neural code.)

The Caltech CNS program was a university-wide expansion of Hopfield’s approach, bringing together math-wielding theorists with lab-bench experimentalists. As a member of both camps, I was in my element, and everyone around me was, too. It was exhilarating to bring humanity’s last 50 years of technological progress in audio, radio, circuits and computers to bear on explaining how brains work and what they do. With CNS, Hopfield and Mead had built a whole new discipline around their visions of mathematically simple neural nets.

I benefitted directly from a major initiative of Hopfield’s. While he was on my committee, Hopfield wrote to the Caltech faculty at large, advising that he would require any grad student getting a PhD with him (e.g., me) to write a single-author paper. Usually, every paper a grad student writes has their advisor’s name on it too. That meant no one was sure whose ideas were whose. Hopfield’s point was that if a student submits a paper entirely on their own, it proves the ideas are theirs. I don’t know how my advisor responded, but I heard the faculty collectively was in a rage: Junior professors needed those extra papers to fill out their publication lists. Publish-or-perish was very real to them, and Hopfield’s principled stand for intellectual integrity made life tougher.

But not for me. Hopfield had “forced” me to do what I always wanted to do anyway: publish my most radical ideas as clearly as possible, in my own voice. So, I wrote a paper pretty much proving that neurons could operate a hundred-fold faster (i.e., 10,000% faster) than anyone thought at the time, which means a hundredfold more bandwidth. That paper started my career as a renegade and bandwidth advocate, a lonely position now utterly validated by many lines of evidence showing sub-microsecond processing in brains, as presented in Tucson this April. Thanks to John Hopfield’s principled vision of science, I was not pressured to water down a good clean idea, which has now been vindicated.

A true physicist

The last conversation I remember with John Hopfield was when I defended my Ph.D. dissertation (the one “disproving” his model of neurons) in the old, storied East Bridge building at Caltech.

This room was nearly sacred to physicists. Steven Hawking had answered questions on these tiles a couple of years before. An alcove across the hall displayed a working micro-motor, less than a tenth of one millimeter on a side, inspired by nano-tech founder (and Nobelist) Richard Feynman. Around the corner were (not-yet-Nobelist) Kip Thorne’s framed bets about black holes. In a tiny room just down the hall, their common advisor John Wheeler had derived quantum mechanics from information theory on a chalkboard — “It from Bit.” On the floor in front of me (I had arrived early) sat his former student Kip Thorne. 

In this hallowed place, I had not expected more questions. I had already been answering questions for hours in the seminar room next door, and I frankly expected Hopfield to say something different. I expected him to say “Congratulations, Dr. Softky.” This was supposed to be the end of my dissertation exam.

“We’d like to ask you some more questions,” Hopfield told me.

This wasn’t how it was supposed to work. Moments before, during my PhD defense, I had proved a popular body of knowledge wrong by invoking undisputed math. The panel had accepted the debunking, as CNS co-founder Carver Mead had accepted it weeks before. But I hadn’t debunked physics itself; I had debunked neuroscience. To my committee, that was a lower form of science, and they wanted to make sure I actually knew physics.

So, Hopfield asked me a question that hit the heart of my dissertation. He drew a little diagram of a circuit on the chalkboard: a battery, a capacitor, a resistor and a tiny neon bulb. He asked me what it would do.

I remembered that little circuit from my childhood as a relaxation oscillator. It charges up until it hits the voltage where the bulb lights and then dumps the charge, starting the cycle anew. In other words, it goes blink-blink-blink. That little circuit was exactly the model of a neuron that my dissertation had disproven (such a circuit can’t produce the “noisy” pulses that real neurons produce). It was also the one Hopfield had inflicted on his students in our very first week of class, to solve, program and simulate with wires. Now I got to tell him how it worked, and didn’t work, as I became one of his own program’s very first PhDs. 

Very few people create whole new forms of science and technology. Hopfield was the first to use laws of physical energy flow to calculate information flow, just like Mead was the first to use laws of physical structure to design integrated circuits.

Combined, those two ideas now let computers act like dumb or clumsy people. Soon, they will also let us know how brilliant, graceful human beings do what we do best.

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Nobel Prize Winner John Hopfield Changed Neurophysics — and My Life appeared first on Fair Observer.

The problem is, growing babies learn from high-bandwidth, back-and-forth sensory interaction — not “content.” Our nervous systems are hardwired to use and learn from all our muscles and senses in concert, interacting with three-dimensional people and objects. Babies learn by putting things in their mouth, making faces, wiggling and noticing the results.

That applies doubly to social learning. Infants learn by imitating and practicing. They coo while their mothers speak in sing-song (which is referred to as “parentese”). They learn by sound, mimicry and serve-and-return interaction first and foremost, because it underlies both social and physical skills. Full three-dimensional awareness develops years later, and being able to see three-dimensional content on flat screens develops later still.

Practicing social skills with real people worked well until it didn’t. For millennia, most babies always had people around to play with: parents, older siblings, relatives and neighbors. Any live human was fair game for cuddling or teasing, and many people liked playing with them. Work was manual, so it was simple enough to entertain the baby in the kitchen, the workshop or the field. In physical settings, babies get to practice with actual playmates.

Fast-forward to our screen-saturated present. Parents are often at work, and older kids are at school. Both are typically on screens. The age-old supply of social companions has dried up, leaving babies lonely. For many guardians, the solutions are either to pay for professional childcare by the hour or to subject little ones to vivid screen entertainment, which costs far less. In crass economic terms, parents must choose between connecting with their baby or having money. That is a toxic tradeoff.

But at least the toxicity can be understood epidemiologically, and the tradeoffs understood economically. Both are needed to realize and fight baby media’s negative influence.

Economics vs. epidemiology

Economics is the weaker of these two sciences, being deeply unprincipled. The profession praises capitalism professionally, yet in its core competency, information flow, still can’t tell up from down: should information flow unhindered and unmodified, to benefit society, or should information be filtered and amplified for private profit? It can’t be both ways.

On the opposite side of the spectrum, epidemiology — the study of how ill-health spreads within populations and how that spread can be controlled — is as deeply scientific as particle physics. It balances subtle hypotheses spanning multiple streams of data and leverages its conclusions to save human lives. This branch of science is how diseases and environmental dangers from germs to chemicals are discovered, understood and fought. Its full statistical power is the best way to manage growing threats to public health: COVID-19, cigarettes, fentanyl and electronic screens.

Economics investigates the connection between behavior and money. Epidemiology investigates the connection between behavior and public health. When both are in play, cash flow impacts public health.

Sometimes, the interaction is beneficial, like when a profitable new vaccine or therapy saves lives. But malignant interactions grow exponentially, especially when biological instincts are up for grabs. For example, opium chemically creates cravings, which affects behavior, which affects profit. The profit is concentrated and actionable, while the damage appears as distant externalities. “Externalities” is the catch-all term for unintended and long-term consequences, the unplanned results that happen off the spreadsheets. Externalities are always the problem.

For instance, in the Opium Wars of the 19th century, Britain systematically profited by creating drug addiction in China — the profit was local, while the damage was distant. Today, the similarly addictive chemical nicotine drives a profit cycle via the tobacco industry. Alcohol and sugar cause similar problems while supporting large industries. Now all of those are regulated, because for a society to survive long-term, it must limit attractive products that hurt the populace. As I’ll soon describe, baby media is one of those dangerous products.

Baby media hacks and damages babies’ brains

It’s clear that chemicals like opium and nicotine drive basic urges. But videos aren’t chemicals at all, just patterns of light and sound. How could patterns of pixels hack our brains’ biology?

They do it the same way chemicals do. Chemicals carry both fuel and information. Some we need in bulk, like water and air. Others we’re sensitive to in trace amounts, like vitamins. Opium and nicotine happen to trigger mind-altering and behavior-changing pathways in the brain (and to a lesser degree, alcohol and sugar do as well). The particular patterns of atoms in opium and nicotine “hack” our information processing.

Particular patterns of light and sound work similarly. Bright flowers send attractive signals, while camouflage does the opposite, erasing the signals of a creature’s presence. Our nervous systems are tuned from birth to interpret specific colors, shapes, frequencies and movements as meaning certain things. Pre-programmed biological boosts are crucial cues for filling in a rich, detailed world.

Babies not only make cries and coos which pull the mother’s heartstrings; she makes sounds which touch her baby, too. Her sing-song “Hello, baby!” voice or soothing tones were primed by primate physiology ten million years ago. The baby’s nervous system knows those sounds mean Mom is near, so the child instinctively responds. That natural, native back-and-forth at certain frequencies and cadences is why the mother-baby bond appears in the first place. Those patterns taste sweet to the child’s heart and mind.

In that informational sense, baby media is taking candy from a baby, over and over. The jangly, clangy, ultra-high-pitched frequencies on shows like Chip and Potato, Ms. Rachel and CoComelon catch a baby’s attention; their frequency spectra overlap with the ones the baby’s nervous system naturally enjoys. So, those shows capture babies’ attention specifically by triggering vibratory mother-infant bonding instincts. Likewise, the shows’ looming, veering cartoon faces and frequent cutscenes cue nearby motion to the primary visual cortex. It’s ear-candy and eye-candy, in other words, and not by accident. The creators of CoComelon, for instance, algorithmically optimized the show for this.

When such patterns grab a baby’s attention, the kid responds as if called by a real person, typically by looking or wiggling. They then expect the person to respond. In real life, this would be a perfect data-gathering opportunity for the child.

But when watching a video, if the show’s pre-recorded response is timed just right — as some are — the baby might be fooled into thinking it received its desired answer. But the screen is just a screen, and doesn’t pay attention to the baby. Every time the video and sound provoke them into tasting the sweetness of anticipated play, the reward is yanked back. Mom never appears. That moment’s bonding instinct is wasted, and a precious chance to gather social data is desensitized. It alienates the young mind a little bit more, as the child falls for a machine in place of a person, and is then jilted.

This is the same dynamic as social media, in fact. The algorithms that so successfully manipulate teenagers into spending hours a day on social media provoke the same innate instincts as those locking babies’ eyes to screens. The difference is that social media uses the selection and timing of content such as posts and videos, while baby media hacks babies’ brains using the native harmonies of the nervous system. Both of them desensitize and disrupt basic nervous system function.

It doesn’t just damage social skills. Children can’t make three-dimensional sense of a two-dimensional screen until the age of three (the video deficit effect). And that’s if the kid grew up strictly in our three-dimensional world. Unfortunately, touch screen tablets, in the same way as baby media, harness native urges for novelty and interaction to keep kids’ eyes and fingers glued to glass.

In order to learn multi-sensory consistency and physical reality, babies search out novelty, the frontier beyond what they already know. Tablets are delightfully interesting, of course, but their novelty cheats by deviating from our world with surprising, disconnected lights and sounds. So interaction with a tablet poisons babies’ training data. Babies who use tablets will undoubtedly face later problems with spatial skills, navigation and stereo vision, just as children who spend too much time on close focus become near-sighted — which is a growing worldwide problem blamed on education, not on screens. Epidemiology will discover the damage to babies soon enough, but can it save the day?

The battle against baby media begins

The imminent battle over baby media is horribly lopsided. Corporations outgun pro-child advocates millions-fold.

Anti-digital advocates have at best millions of dollars of funding, while media companies have trillions. Advocates promote laborious studies on hundreds of people, while companies surveil whole populations automatically. Advocates know little about companies, while companies know loads about us. Humans have nervous systems easily dazzled by distraction and misdirection, which companies are paid to exploit, fueled by biometric data and protected by fig-leaf disclaimers and disclosures.

The deepest asymmetry, paradoxically, is ethical. Human morality forbids experimenting on people, but that wasn’t always the case. The infamous Tuskegee Study of Untreated Syphilis deliberately and secretly withheld medical treatment from sick people over decades. The Nazi physician Josef Mengele performed such awful and specific experiments on prisoners that medical science has renounced and forever forsworn using such experiments, data or lessons. The notorious Stanford Prison Experiment spurred the creation of human subjects protections, restricting university experiments from harming their subjects. These rules make gathering direct medical evidence of harm to humans difficult, slow and expensive.

Those ethical rules don’t apply to private experiments. Social media companies routinely use an automated method called A/B testing to maximize users’ time online without their knowledge. I once coded such programs myself. Ten years ago, Facebook intentionally made many users feel depressed by selecting depressing news for their feeds.

The most extreme human experiment today is the ingenious gadget called the Distractatron, which CoComelon owner Moonbug Entertainment uses to optimize the show’s captivating effect. As a test infant watches the show on a main screen, a screen to the side plays boring, real-world scenes to vie for their attention — this is the Distractatron. Every time the kid’s attention wanders to that second screen, program creators declare that moment a weak point. They add yet more attractants to the video to prevent the baby from un-glueing its eyes. 

I’d urge readers to view Time’s pro-corporate, propagandizing take on CoComelon. Note how it positively describes the show’s content without addressing that its attractiveness comes from low-level cues that exploit child biology. Babies can’t even comprehend the identified “positives” while they’re learning to use their eyeballs.

Scientifically speaking, optimizing for captivation is like optimizing a digital drug. The fact that optimized shows all reproduce the same high-speed, high-frequency sonic and visual textures proves the science of attention-grabbing works. Unfortunately, the goal is to create addiction, not stop it.

The baby in the lab may not be harmed much by those few hours of experimentation, but the finished show puts infants everywhere at risk, for their whole lives. Which country will step forward first to renounce and forever forswear such experiments, data and lessons and products based on them?

[Lee Thompson-Kolar edited this piece.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Colorful, Toxic Economics and Epidemiology of “Baby Media” appeared first on Fair Observer.

The damage screens cause

Is it possible to disentangle the damage caused by smartphones from that caused by social media? Probably not, because so much of social media appears on smartphones. From a data point of view, that’s good; we can use either one to roughly estimate the other. So first, we’ll see how screens hurt people one by one and hour by hour. Next, we’ll see how the introduction of smartphones increased suicides. Then we’ll combine those observations into an estimate of deaths caused by social media combined with phones.

The first data observation is that hours-per-day screen use directly correlates with all kinds of loneliness and mental distress, including suicidality and actual suicide. The more hours screens are used, the more mental problems worsen — year-over-year specific demographic slivers of young people indicate that they get 1% worse per hour of screens per day.

Evidence like this shows up everywhere, undisputed in general but loudly disputed by whichever app is currently under fire. Once you know that brains need continuous three-dimensional space, the damage done by twinkly, two-dimensional screens makes sense.

The second observation is that the introduction of smartphones around 2010 coincided with a rough 50% spike in teen suicides for both girls and boys in the US. This number has continued to the current day. The point was first made by social scientist Jean Twenge in 2020, and has been validated ever since. No other force right then penetrated teen lives as dramatically, so a safe estimate is that phones and the stresses brought by social media are the root of teen mental anguish. This neutral line of reasoning concludes that statistically, about 2,000 extra teen suicides per year in the US are caused by smartphones.

Over the whole US population, an extra 15,000 suicides per year (approximately one-third) are caused in aggregate by smartphones and social media. That’s a kind of annual body count. On one hand, it is a small fraction of the statistical half-million people killed each year by cigarettes. But the social media body count is vast by other standards. For example, 50 years ago, the Ford Motor Company was sued and charged with criminal homicide when a car the automakers knew to be dangerous, the Ford Pinto, killed 27 total people by exploding. A few dozen fatalities is plenty to answer for, but nowhere close to tens of thousands.

Proper responses: Executive Officer vs. Algorithm Officer

Every parent knows that phones and social media are bad for children. The Senate committee room was full of such parents, looking at Zuckerberg to put a human face on that which had killed their kid. He was there to answer for their lives.

In the US, there is a ritual when a great sin has been committed: Someone must be fired for the offense. Minutes earlier, committee member Senator Josh Hawley had just proved that Facebook knew their product was killing children, yet did nothing to stop it. Hawley bluntly confronted Zuckerberg.

Hawley: Had Facebook fired anyone for killing kids?

Zuckerberg: No. [He repeated this over and over.]

Hawley: Had Facebook compensated any grieving families?

Zuckerberg: No. Our job is to build industry-leading tools.

Hawley asked the same question over and over. He went in like a boxer, relentlessly hammering Zuckerberg about the lack of firings and his fussy deference to the privacy of employee records. He ignored Zuckerberg’s blather about building “industry-leading tools.” Finally, having destabilized his adversary, Hawley insisted that Zuckerberg physically turn around and face the crowd of grieving mothers.

Zuckerberg performed his sacrificial role ably, showing an earnest public face for the trillion-dollar Facebook. His face looked honest as he enunciated the bland apology, “No one should have to go through the things your families have suffered….” Masterful bearing, plenty of empathy and no acceptance of responsibility. That is another American ritual. It would have been a perfect CEO performance, except that it tapered into a final shout-out for his beloved industry-leading tools: “…and this is why we have invested so much in industry-leading efforts….”

Zuckerberg was only doing his job by dodging the blame. In the US, the job of CEO is to defend shareholder value, which in this case means building software that leads the industry in making money, and to defend that source of revenue against attackers. CEOs are meant to pay their owners, not admit the entire enterprise is wrong.

What would I have said had I been in his place? Not as a Chief Executive who moves fast and breaks things, but as Chief Algorithm Officer, ie Chief Truth-Teller? What truths about technology can I express that Senators and grieving parents should know? I would say:

“My Honored Senators and parents everywhere, we humans are the victims of our own success, our hands so skilled they fill the world with captivating things, our eyes so innocent they follow eagerly. That statement combining our human ability to be charmed with our ability to manufacture charming things is not just self-evidently true, it is also the text of the peer-reviewed conclusion of a theoretical neuroscience research paper in the most prestigious journal possible, as conveyed by the journal’s founder. My wife Criscillia and I spent two years alone, unpaid, writing that paper and sealing a scientific truth into the permanent record, forever.

“Our paper, ‘Sensory Metrics of Neuromechanical Trust,’ in effect proves that all sensory systems — as a general mathematical principle — are subject to self-reinforcing informational addictions, such as screen addiction or social media addiction. Like our tongue’s attraction to sugar, brains are attracted to special rare things, but are at the same time damaged by too much of them. Media companies did read our paper the week it came out in 2017, yet have stayed mum ever since.

“The natural and mathematical splendor of the human sensorimotor system, and its tragic capture by digital dazzlement, is the message of ‘Sensory Metrics’ and also our message for you. Human brains need attention for our own needs, to trust our senses and ourselves. That’s how brains must work, especially childrens’ brains. Attention is meant to be used, not captured. Even a few distractions can be dangerous, but to let a corporation or machine make money stealing attention wholesale is theft of the most destructive sort, taking not your belongings but your mind.

“It is true these screens and apps kill children, so they must stop, and fast. That is why you should pass KOSA, the Kids Online Safety Act, which might have saved these children, and will save many more.

“Bills like KOSA are a necessary stopgap, but cannot be the final word. The laws of attention and economics are continuous, naturally capturing or flowing around regulatory boundaries. The problem is like nailing jelly to a wall: As long as software is allowed to look for a connection between human attention and profit, it will find it. And software is getting better every year, as Silicon Valley boasts. As a general rule, each single step inside a killer app is functional, legal and profitable. That’s why those steps are there. Get a child’s attention, keep it by keeping just one step ahead, show things the child likes, get paid by showing related things, algorithmically select and pair child with message with ad, refresh once a second…each of these steps is standard, rational business and engineering. That’s how software is supposed to work. The so-called “industry-leading tools” that Facebook claims to make would have to impede such programs. Fortunately for Facebook, the tools themselves don’t actually work, so they, in fact, do lead the industry by protecting profit through fig leaf control.

“So as long as computerized advertising or attention-grabbing remains legal, it will undermine human attention and mental health. There is no particular piece to regulate to stop collective damage. In the long run, harvesting attention is like harvesting organs. Profit must be prohibited or people will die.

“There is, in fact, a software tool technologists could build to substantially reduce that human collateral damage. Much like Facebook’s tools, and much like the dashboard tools I invented and built for businesses myself, continuous statistical algorithms fed by real-time metrics optimally fit to historical trends. The data is there, the math is there, the computing power is there, the chance for infinite transparency is there. Version 1.0 could be done in a year. The only difference is what this new tool would measure. Instead of the profit and user value and time-on-device which tools measure now, this new tool would measure the body count and misery index, a set of meters and dials of despair. How many hours of human life are reduced per dollar of advertising profit? This tool would show the only cost/benefit analysis which matters: the cost in human life offsetting the benefit of algorithmic profit. It would use and show real live data and straightforward metrics, sensory metrics, of neuromechanical trust. This tool would show the world what only executives know now. This new tool would lead the industry, but in the right direction.

“These software tool-builders are my tribe. I love being a scientist and technologist. To ask questions no one ever asked, to answer them, to build cool stuff which never before existed. It means hanging out with fun, sharp people, differently brilliant, but in ways we mutually respect. We can save the world if you invite us to.

“But only you, Honorable Senators, can make it happen. The market can’t. Our current paymasters have their own paymasters, and therefore they shackle us to wooden metrics pulling galleys of ads the wrong direction, against the needs of real live kids. Only human people, acting on behalf of human people over and above machines, can compel all of us collectively to do the job that we so want to do. The market can’t undo its damage; you can.”

That is what I would have said to the US Senators in place of Mr. Zuckerberg, had I been invited to the US Senate.

Instead, I had been invited to testify to a smaller committee: one for the Senate of the state of Vermont, which was considering banning cell phones in schools. They were deciding whether even to pass this proposal, S.284, to the full Senate for debate. I was one of four people giving testimony, mine remote from California.

The best testimony came from the principal of a private school, who explained how much happier and more productive everyone on his campus, students and teachers alike, became since the school banned phones. Every person testifying brought a different perspective: how distracting phones are to all children, how socially disruptive, how addictive, how phones enable cyberbullying. They gave reason after reason, all the way up to how phones cause mental illness and suicide. Proponents showed Senators the following graph, which illustrates both those horrors rising about 50% (as I mentioned prior) in the years since smartphones became widespread.

In particular, the boost in attempted suicide from 4% to 7% means an extra 3% per year which wouldn’t be there otherwise, presumably due to phones and online activity. Vermont’s teenage population is about 60,000, so 3% translates to 1,800 extra attempted suicides per year. Those additional almost-deaths are what the bill’s proponents are fighting.

I didn’t have those numbers when I testified. In the moment, I emphasized three firm points — not of opinion, but of undisputed scientific truth. First, all these facts about screen damage are absolutely true, interrelated, and explained by the simplest scientific understanding possible: the understanding that humans are three-dimensional creatures for whom screens are alien. That means these problems are rooted in human biology, and won’t go away or get better. Second, this quantified perspective comes courtesy of our paper, which is scientifically perfect. It’s public, peer-reviewed, based on undisputed principles and itself undisputed for over seven years. Third, only a legal structure committed to actual scientific truth, rather than to a legalistic set of rules and targets, has the power to stop technology destroying kids’ brains. For man-made law to work, natural law must trump it. Any law worth passing must first and foremost be aimed at protecting children’s health, regardless of how bad actors learn to bend the rules.

The Vermont Senators presumably did not look into that scientific proof. Within 24 hours, the proposed ban on phones was watered-down into a proposal that in two years, the Secretary of Education would gather lots of information and generate an overall policy. This would enable local schools to set their own individual policies: which phones, where, what times, what punishments etc. That is, wait two years and begin all over, but with much less urgency. In general, people trying to prevent real deaths don’t just ask for studies.

That attitude was in the air already. In the week before our hearing, there were quotes in Vermont media on behalf of school principals and the health bureau saying a ban on phones in schools was too much. Their statements sounded practical, the kind of sensible thing a good administrator says. But translated into common sense, they don’t add up.

Below are six such quotes and my translations, which I passed among the Vermont enthusiasts. The silver lining is that each dumb statement has the same structure: inflicting health problems now is okay because it’s cheaper and more administratively convenient. So to these administrators, the theme of known-effective health measures vs short-term convenience is reliable enough to lean on constantly. It doesn’t actually work, but they think it does because they measure the savings, not the damage.

Translating administrative nonsense

“Jay Nichols, executive director of the Vermont Principals’ Association, says he understands the negative impact of social media on young minds. As he put it Feb. 2, the association is ‘on the front line of the negative impacts of digital addiction to social media.’ However, he said it does not support S.284.

“‘Already, most schools have social media and cell phone access completely or significantly restricted during the school day,’ he said. ‘Providing the mental health resources that students need when they need them is probably a better approach to addressing mental health needs in students than banning cell phones and social media from schools from our perspective.’”

In other words, we recognize that phones cause mental health problems, but we’re happy to allow that because we already have systems for addressing and maybe even fixing mental health problems later.

“Nichols called the opt-out element of the bill unreasonable. He told committee members that providing paper copies of digital materials is ‘a huge burden to schools and is not necessary,’ saying later that ‘it’s not appropriate to allow students to simply opt out of learning how to use technology in today’s world.’”

In other words, even though reading on paper causes less eye strain and headaches and is 400% better for comprehension, it’s slightly more expensive. So we will force harmful yet ineffective screens on all students, always.

“‘We completely support the idea of minimizing and reducing exposure to social media while in school,’ Levine told members of the Senate Committee on Education. But he said the bill felt ‘unrealistic’ and a bit ‘heavy handed’ — possibly even ‘accusatory’ and ‘disempowering.’”

In other words, we know screens, phones and social media are bad for kids. But a bigger risk than children’s health is that administrators might be unfairly accused of disapproving of something someone likes.

“While Vermont’s youth may experience negative impacts due to social media, Dr. Levine said the most marginalized youth — who experience social isolation at ‘much higher’ rates than average — can find ‘hope and community’ online.”

In other words, phone and screen use increases social isolation for children everywhere, except for the most isolated kids who paradoxically will benefit from them.

“Levine added that he would like to see a focus on ‘health education’ that could give youth the skills to navigate the complexities of the digital world.”

In other words, phone and screen use is so unhealthy, we want to train them in managing these unhealthy things by doing them even more.

[Lee Thompson-Kolar edited this piece.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Social Media Has a Colossal, Horrific Body Count appeared first on Fair Observer.

Mid-century modern design is best known for furniture, among the best ever produced (like the curved writing desk, with a lip, at which I sit right now). Mid-century furniture flourished at the simultaneous peaks of aesthetic science, ergonometric design and new high-precision woodworking technology. Sadly, its slow death ensued with the plummet of profit margins and consumer discrimination. Designers like Charles and Ray Eames lost out to mass-produced furniture by Ikea and others.

Alongside furniture, however, mid-century aesthetics gave us amazing architecture and art—often both in one place. Every week I visit a stunning example, Our Lady of the Pillar Catholic Church in Half Moon Bay, California, affectionately known as OLP.

An unrecognized jewel

OLP is a mostly unknown, seaside country church with an intricate, curved interior of stained glass murals under a soaring aircraft-hanger roof. The choir at 10:00 AM Mass has only three people, of whom my wife Criscillia and I are two. I may be the only person there who recognizes OLP’s unique artistic heritage, which is why I want to keep it as it is, and why I’m writing this.

Since OLP is unknown, let’s compare it with an actually famous mid-century building, First United Methodist Church of San Diego. Here’s what that church looks like inside:

Note the curved barrel ceiling and angled supports, which bisect horizontal beams. The ends of the pews echo that parabolic art, as do the outlines of the chandeliers, shaped like rocket ships. In great buildings like this, as with those by architect Frank Lloyd Wright, motifs reappear across the floor, the furniture, the windows and the roof. Everything elegantly fits. 

Now let’s look at OLP. From the outside, it looks simple and boxy, a cross between a mission church and a high school gym (although the gardens are magnificent).

The inside of the church is a complete contrast. Curves dominate, a likely relation to the new age of aviation in the 1950s, when the church was built. At that time, San Francisco had just opened its international airport “over the hill”—this little town of Half Moon Bay, although just thirty kilometers south of San Francisco, was effectively isolated from San Francisco and the rest of the Bay Area by steep mountains. Half Moon Bay had gotten its own airport only a few years earlier, thanks to the Army and World War II. 

Also south of San Francisco, but on the populated side of the mountains, was one of the largest buildings in the world, Hanger A at Moffett Field. The hanger was built in the 1930s to accommodate Zeppelins.

The angled sides and curved roof of this giant hanger resemble a smoothed-off trapezoid. 

Now let’s look inside OLP: 

There are actually three kinds of curved arch here: the most boxy is the wall/ceiling shape, then the wider arch, then the narrower arch whose perfect half-circle centers on the circle of the Virgin Mary’s halo. That narrower arch has the same shape as the one in San Diego, as do the vertical struts bisecting horizontal beams.

The same curves appear looking from the altar towards the entrance. From this angle, the circular Rose Window is prominent. It carried over from the older church which this one replaced.

The chandeliers contain gentle arcs at their tops, echoing the arc motif seen in the roofline and the stained-glass windows. Unusually, the curved flares of the cylinders imitate aircraft-engine cowlings, a separate invocation of aviation in addition to the aircraft-hanger shape.

So it looks to my amateur eye as if this tiny rural church contains several of the key motifs of the famous San Diego church, in particular the angled support columns, aircraft-hanger roofline and matching aircraft/rocket chandeliers. But here’s the catch: OLP held its first mass in 1954, a full ten years before the San Diego church was built. The little rural church beat out the big famous one and perhaps even inspired it. 

But what makes OLP so spectacular is the cycle of stained glass windows portraying eight frames of the Christian narrative. The windows incorporate circular arcs in the cartoonish, abstract mid-century style, a style that rarely depicts human figures.

1. The Annunciation. The arcs here intersect above Mary, as if forming the roof-beam of a church.

2. The Nativity of Jesus. Here the arcs intersect above as the beams of the manger, and below to cradle the baby.

3. The Three Wise Men bringing gifts. Here the arcs intersect to form the Star of Bethlehem

4. Jesus enthroned as Christ the King. The arcs form his crown:

5. Pentecost, in which the Holy Spirit descends on the Apostles.

6. The entry of Jesus into Jerusalem on Palm Sunday. The arcs here are palm leaves.

7. The Crucifixion. The arcs are asymmetrical, like a spiral.

8. The Angel of the Resurrection. The arcs form a sun:

Below, at eye-level with the congregation, is a very different view. There is a large stained-glass “mural” that depicts the Christian history of California and its missions. The same arc-shapes that appear in the upper windows reappear as dividing shapes throughout the mural, but in muted blues and golds which match the original rose window. Note also the metal decoration wrapping the angled vertical beam, part of the metallic aviation theme.

My photographs do not do this church justice, and my dilettante’s knowledge of art and architecture should not be the last word on this gem box of a church. I sincerely hope that others more qualified will visit this beautiful place, to know what it is to sit, sing or worship inside a unified work of art.

OLP is a church, not a museum

But what if no one knows it’s art?

The photos above show the building, not the people. Lots of old people, yet enough newborns to coo together during service. Three different languages: English, Spanish and Portuguese. Rich and poor. And brought together recently through tragedy, when three church members were killed in a violent attack.

The congregation works hard on the church. A few years ago, when Covid first hit, construction-minded men jerry-rigged a giant tent in the parking lot so Mass could be held outdoors. It was held there for two years. The services were the only continuous services in the area. OLP people also share a love of neat, bright decoration. The gardens are pretty and thriving, the festive fabrics stunning, the flowers always vibrant.

And therein lies the problem. Those abstract modern chandeliers don’t have the bright and festive look most OLP folks like, and they’re the ones who worship there. Over the last few years, congregants have renovated almost every element: the church now has a freshly painted ceiling, a new carpet, a new altar, new pews, restored paintings. Those rusty, abstract chandeliers are now the dullest elements in the building.

Some parishioners want to replace those old chandeliers with these brand-new ones:

These sparky new things don’t match the old aesthetic, but many parishioners like them. It’s possible that OLP, a perfect example of a bygone form of art, like other art before it, will slowly erode its coherence to serve the people who use it now. It’s not just their right, it’s their obligation to worship as they want. The church belongs to them, not to history. But oh, what a wonderful history it is.

[Throvnica Chandrasekar and Anton Schauble edited this piece.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Hidden Gem of a Mid-Century Modern Church appeared first on Fair Observer.

First of all, how could anyone trust something named “crypto”?  Those syllables connote mysterious, secret, hidden and locked up.  The very opposite of trustworthy.

Second, look at the people selling it. Not how they looked years ago, fresh-faced, energetic, and eager to disrupt stodgy governments and banks.  Believable.  Their story, originally inspired by anarchism, made the growth of crypto seem inevitable, and good.  But that’s a self-reinforcing story, as the book Narrative Economics” by Nobel Prize–winning economist Robert Shiller explains. Stories of inevitably growing wealth, like the famous Dutch tulip mania, disrupt economic common sense.  The book calls these stories “narrative contagions”, because their inherent promise makes them spread all by themselves.  The rise of Bitcoin is the first and best example of a narrative contagion.

But stories lauding crypto aren’t believable any more. It turns out, for example, that prominent crypto-booster Sam Bankman-Fried gave tens of millions of customer dollars to crypto-friendly politicians, and now the customers want that money back.  His crypto fund FTX is now bankrupt, and now he is under house arrest.

To judge crypto you can also look at the other crypto boosters and their agendas.  For example, consider the so-called “effective altruist” (EA) movement, a small crowd effective mostly in persuading rich people to take big risks today in hopes of making money tomorrow, which might solve world problems later.  Their reasoning is specious, and their track-record smarmy and self-promoting.  The EA crowd has been promised billions by various crypto founders, so of course they want crypto to succeed. They’ll have nothing otherwise.

Economic Perpetual Motion

As two more question marks, look at the two businesses which first made crypto seem worthwhile (if not actually legitimate), money-mining and money-laundering.  

The computational process called “mining” started with Bitcoin. Mining is successful when it solves a tough computational problem, in which case it generates one new Bitcoin. Money-mining uses loads of electricity—already half a percent of world production—making this “production” an environmental cataclysm all by itself. That energy use is paid for by the increasing rarity of new Bitcoin, algorithmically capped at a hard upper bound of about 20 billion coins.  Most of those have already been mined. According to supply and demand, the 10% or so remaining coins will continue to rise in price, giving the appearance of increasing value of the underlying currency.

The other business model, money-laundering, doesn’t work any more. Crypto’s deeply disruptive role in tax evasion, illegal drugs and human trafficking was thanks to encrypting the identity of crypto owners. But as reported in WIRED, five years ago a multi-county sting operation took down the world’s two largest illegal drug-markets (AlphaBay and  Hansa) simultaneously by breaking that secrecy code. While shutting those markets down, governments scooped up data on thousands of illegal buyers and sellers. The key to finding the culprits was a bag of statistical tricks for tracing supposedly untraceable, supposedly encrypted crypto identities, tricks so subtle and important even WIRED’s reporter was left to guess how they worked. That was five years ago, so the decrypting tools have probably been perfected. So much for anonymity.

In summary, crypto has an untrustworthy name, untrustworthy technology, untrustworthy business models,  and untrustworthy people.  Those all cast doubt crypto, and doubt is the enemy of trust. 

However persuasive that line of argument may be, it has a tiny flaw.  “Crypto is untrustworthy because people don’t trust it” sounds a lot like “I’m believable because people believe me,” yet another self-reinforcing narrative contagion. On its own, the phrase “crypto is untrustworthy” is only an evidence-based truism, but not as true as true could be.

On the other hand, the phrase “Crypto is untrustworthy, on principle” aspires to the highest echelon of truth, the truth of a Law of Nature. That’s where I come in.

The Bandwidth of Trust

To understand crypto you need to understand money, and to understand money you need to understand trust.  We can explain how trust works by sorting out things we already understand or trust—concepts, biology, communication and material value—along two simple metrics, to see where crypto fits in among them.

So please permit me a boast: I am one of only two people in the world scientifically authorized to explain trust in the language of technology; the other is my wife Criscillia Benford. Together on a two-year sabbatical, six years ago, we co-authored the first and so far only mathematical paper (60 pages, 100 references) explaining trust.  We explain trust as not a fixed certificate but as an ongoing interactive process.  Specifically, the real-time process of model validation and updating, a process well-understood by technologists.

The key to trust is interactive bandwidth. The better and faster the connection between you and the thing you want to trust, the more trust you can have.  Interaction is the feedback loop of examining, poking, and prodding by which people instinctively trust their eyes and other senses, but the idea works for people and machines alike. In some sense it’s been known forever, but only over the last few decades have technologists understood this interaction numerically.

 Mathematician Claude Shannon invented the concepts of bits and bandwidth.  Now, thanks to mathematical and technological innovations, we can quantify the “better and faster connection” on which trust depends as specific, quantified metrics like data format, continuity, latency, duration, noise, bandwidth, and so on.  In fact, those six metrics are among the eight named by our paper’s title, “Sensory Metrics of Neuromechanical Trust.”  Those metrics are used by a self-driving car looking at the road, and likewise by a human looking at the world. Those metrics explain trust in all its forms, anywhere in the universe. That’s the power of math.

Still, eight metrics is a lot of numbers to describe just one connection. Fortunately, we can simplify them down to just two for rough estimates. (Rough estimates are all you need, since differences tend to be huge.  For example, two humans face-to-face in good light exchange a megabyte per second of visible microexpressions, while a “Like” on social media is but a single biased bit, a billion-fold less trustworthy). 

The two numbers which best represent connection (and hence trust) are timing and complexity. Timing tells you about bandwidth and responsiveness.  Complexity tells you how hard the thing is to decode. In general, the most trustworthy connections are fast and simple. The worst are slow and intricate. 

Now we can use these two metrics to rank some familiar examples.  First by graphing some directly related informational concepts like symbols and categories, then by graphing a few examples from biology and technology. I’ll end by graphing sources of material value (including gold, shares, and crypto) so their trustworthiness is obvious in context.

Hierarchies of Information

Of the two metrics time and complexity, time is the simpler.  For any information flow, the more precisely time can be determined, the more distinctions can be made in a given period, and thus the more information can be transmitted.  This is the idea behind the concept of information flow per second, known as “bandwidth.” Bandwidth appears on the graph below as a bar showing roughly one megabyte per second (MB/sec) at a microsecond level of precision, slowing down to one bit per second at a one second level of precision. In fact that relation carries across the trillion-fold (million million) range from microseconds to years. Because trust is based on bandwidth, the farther to the left on the graph, the more trust, potentially billions-fold.

Complexity is more complex (of course!).  Complexity is how information is shaped in space. The simplest things are like blank canvases or points, building into line segments (built of dots), polygons (built of lines), graphs, diagrams and so on.  Likewise, a featureless medium is simplest, made slightly more complex by waves, even more so by grids (which have sharp edges), categories (which assign meaning to grid cells), rules (which assign meaning to categories), and so on. Because complex objects have more layers, unpacking or decoding them takes more time, and thus lowers the net bandwidth relative to something simpler using the same timing precision.  So on the graph each “stack” of concepts rises diagonally to the right, as complexity gets bigger, timing gets coarser, and bandwidth gets smaller.  Trust increases in the opposite direction, down and to the left.

Maslow’s Hierarchy of Human Needs

A first example of the relations between timing and complexity comes from life itself: what do people need to be alive, healthy, and fulfilled?  Seventy years ago—about the time Shannon invented information theory—psychologist Abraham Maslow posited a “Hierarchy of Human Needs.” Starting with basics like food and safety, his pyramid of what makes life work ascended from food up through friendship, esteem, and self-actualization. 

Those and other needs are easily sorted by timescale and complexity.  At the fast end, humans die in minutes without oxygen, a very simple molecule.  On the other hand, self-actualization may take decades, and is so complex it’s hard to even describe.  Everything else people need—safety, warmth, gravity, digestive bacteria, exercise—lies somewhere in between those extremes of timescale and complexity.  Here’s what that looks like on the graph: 

Even though these needs are graphed the same way we graph trust, the lesson here isn’t about trust, but about how humans have both simple and complex needs, and about how much longer it takes to know if the complex ones are being met, or to suffer if they aren’t.  Which, in a sense, may be about trust after all.  A person can trust whether they’re breathing much faster than whether they think their life is successful.

Hierarchy of Human Function

Insofar as trust is a human function, it ought to be related to other human functions.  So let’s graph (almost) all those functions at once, ordered as before by timescale and complexity.

The fastest, simplest functions in a human body are the ultrasonic nano vibrations coursing through our bones and myofascial tissue (these are like a “carrier wave” for sensation and control, and have far too high an information density to sense consciously).  These vibrations are the basis of “trusting your senses,” and indeed on the graph they reside in the high-trust zone of the lower left.  Other human functions with high time precision also have high trust. For example, auditory localization, vision, hearing, and touch need microsecond resolution to work their best, but microsecond mechanisms are inaccessible to human awareness.  That means (paradoxically) that our most important and trusted internal operations are effectively invisible.

On the other hand, the operations we humans are most proud of—reading, writing, math, strategy, enduring artifacts—can be sensed and kept track of, but by the same token they have low bandwidth and trust.  It’s easier to doubt a document than to doubt your eyes.

Hierarchy of Communications Technology

For a million years, paleo people communicated only with their bodies, for example using grunts, songs, caresses, smiles, and so on.  Those bodily communications channels make up the natural human data protocol, and thus are in the high-trust zone.

Historically, bandwidth and trust started going down when language and tools appeared. Those innovations inexorably moved attention away from the deep but unconscious diversity of messy natural signals, and toward standardized, repeatable chunks which are easy to recognize, and also easy to fake.  As algorithmic operations chunking, repeatability, and recognition all move up the abstraction hierarchy and down the bandwidth spectrum.  That is, they reduce trust.

To compress information, for example, one typically removes small redundant details.  But the redundancy of those details helps validate that the message is real, just like micro-expressions on someone’s face indicate whether they are telling the truth. Removing such details reduces trust.

Over centuries our communications have become more and more compressed. For example, spoken words became writing on parchment, then typing on paper, then email, then SMS, then tweeting, each shorter, faster, and more compressed.  The vanishing physical detail makes it hard to know if a message was even sent by a real person (half of Twitter posts are by bots). So such messages are that much harder to trust.  Likewise over history, voices in air transitioned to copper-wire telephone calls, then voice-over-internet, then mobile, again each version more compressed and more shorn of the expressive nuance by which we trust speech.

Hierarchies of Material Value

Now we can finally understand money (and crypto).  

For a million years our ancestors were foragers, eating what they found and carrying nothing.  When food and tools appeared so did exchange and barter, in which the source of value could be seen and poked close up—Nuts? Berries? Grain—to take advantage of trust in our senses. You could trust it because it was right in front of you.

The invention of “money” as an exchange commodity suddenly made impromptu validation even faster.  Gold, for example, has a sheen, weight, and hardness that is easy to validate and very hard to fake.  And solid gold is as simple as can be.  You can feel the weight, see the sheen with your eyes, and maybe even bite into a coin to check whether it is soft (made of lead, hence a fake) or hard, which proves it’s real.

Compared to gold, diamonds are slower to check (one needs an expert), and paper currency is more fakeable, even if decorated with holographs and color-changing ink.   More abstract forms of value like shares, derivatives,  and portfolios are yet more artificial, and thus dependent for their value on rules and technologies of validation. We can’t inspect shares with our fingers and teeth, and we can’t understand the complex rules by which banks decide who owns what, or even be sure those rules are applied fairly.  All those intervening steps make trust go down.

So when one graphs material value by these metrics of trust, crypto ranks not only worse than gold, but worse than stock portfolios and business contracts.  The same principles by which paper money is less trustworthy than gold also say that crypto is less trustworthy than paper, or even than owning shares.

The admired American investor Warren Buffett made these points when talking about Bitcoin: “It’s not a currency. It does not meet the test of a currency….. It is not a durable means of exchange, it’s not a store of value.”

In summary, the mathematical principles of trust-formation were hard-wired into the human nervous system millions of years ago exactly to deal with live humans and Mother Nature. Those principles work best on real things in real time, and work worst on artificial things after the fact. Crypto is the least-real, most artificial invention ever considered to be money, so according to those principles it can’t be trusted.  In short:  Crypto is untrustworthy, on principle.

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Truth About Crypto: It Is Scarily Untrustworthy appeared first on Fair Observer.

Attention, in the most basic sense, is a creature’s informational-management strategy. We use our attention to determine what matters, where it is, and whether I can trust it? Vertebrate attentional systems evolved over hundreds of millions of years to let a body use and trust its senses. The brain’s hardware learned to squeeze meaning from scenes like the savannah, scenes containing multiple tiny, faint cues. To a sensory system, faint statistical outliers are eye-candy, attractive,like sugar, precisely because they are rare.  Attention works properly only in a world of sticks, stones, sky, people, fauna and flora, and not much else. Man-made things distract and mis-direct human attention even without meaning to.  And now they mean to and are built to do so, automatically and at scale. 

At the finest level, tiny pixels use microsecond tuning to draw our eyes toward interesting things which aren’t there.  Video games anticipate our anticipation in order to dose us with dopamine. Social media synthesizes the illusion of friendship. Search engines synthesize illusions of meaning. Smartphones rule from our pockets.  Smartphones are the grandest intruders, allowing multinational corporations skilled at using science to design what we will see, believe, and love.

They have successfully commandeered and monetized the growing brains of children and are inflicting widespread damage, according to a powerful new book by the psychologist who saw this coming thirty years ago.  Decades ago Dr. Susan Linn was a child psychologist (and puppeteer!) who appeared on the famous US childrens’ show Mr. Rogers Neighborhood.   Seeing firsthand the damage done to kids by marketing and monetized play, she founded the Campaign for a Commercial-Free Childhood (now Fairplay). It is among the few child-advocacy groups accepting to follow neuroscientific principles, and not accepting corporate money. Now Linn is a professor of psychology at Harvard. 

The best possible book on the topic

With that background Professor Linn is the best possible person to write this book.  And she has produced the best possible book.  While her sentences are often professorial (of course!), there are plenty of cute anecdotes, appearances of charming children, wry observations, and tales of comically misguided products, like the video game advertised to make going to sleep exciting (p. 104).  For a relentless point-by-point compendium of why moneyed interests must be kept away from children’s play, Who’s Raising the Kids still provides a remarkably funny, easy read.  While it employs US examples for a US audience, her reasoning applies outside the US as well, and will probably be easier to act on in those other places.  This book is for the world. 

Most thoughtful people already know that commercial influences are bad for kids, so they don’t need to read this book.  They don’t need its ruthlessly clear thinking and comprehensive, evidence-laden summary of fifty years of scientific study, because their parenting instincts are already fine.  Besides, pondering such depressing content is a grim reward for reading what one already knows.  On the other hand, some responsible officials hoping to make their case may demand even more powerful evidence., Some might even hold out for the formulation of undisputed natural laws to provide them with the clout to successfully rearrange budgets. I’ll give them such laws at the end, since that’s my professional specialty. As a general rule, many parents already have the evidence. They don’t need even the best book imaginable to tell them about the obstacles to raising functional children provided by a market-saturated world. 

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On the other hand, if you are in a position to influence children or guide their experiences—as a superintendent, teacher, nanny, app designer, marketer—you must read this book.  Your ignorance would be a moral hazard when other people’s children are entrusted to your care. And when you finish digesting its contents, to double your investment. Mail your well-thumbed copy to your favorite venture-capitalist or corporate executive, since they need wisdom even more than you do. Ignorance is no excuse when truth is so important, and easily available.

Professor Linn’s barrage of evidence is overwhelming: the wasteful excess of crinkly packaging around toys, kids falling in love with characters from ads, apps designed to spy on kids. Her list of all the easy ways there are to make money from kids’ innocence goes on and on.  Like taking candy from a baby.

After this book, there should be no dispute that markets threaten children’s sanity. Only Self-serving industry will of course gripe about how impractical solutions are to protect the status quo.  Those gripes are true as far as they go, because the only sustainable solution is a tough sell in a pro-capital society. It implies neutralizing market forces present in domains affecting kids. So, in a word, this book is about changing everything.

This book is so good, the best possible review need only use Professor Linn’s own words. Which I will do. No reviewer could add anything more than praise to this magnificent work, except perhaps a commonsense explanation of how this crisis has been mounting for thirty thousand years, and what society must do to save future generations.  

Who’s Raising the Kids, Compressed

Herewith the titles and a few representative lines from each of the thirteen chapters of Who’s Raising the Kids by Prof. Susan Linn (To each quote I append in italics a dense comment using the technical language of trust-formation, to simplify a unification at the end).

Chapter 1: What Children Need and Why Corporations Can’t Provide It

 “The more a toy or app drives the form and content of children’s play and the more the characters or the toys kids play with are linked to popular media properties and franchises, the less children get to exercise curiosity, initiative, creativity, flexible problem-solving, and imagination.” (p. 19)

Comment: Children’s innate learning algorithms need autonomy and real life detail as inputs.  Standardization, broadcast, and synthetic attractiveness undermine those algorithms by restricting freedom and damaging data, and thereby undermine learning and trust.

Chapter 2: Who Wins the Games Tech Plays?

 “Technologies are problematic when they optimize profits at the expense of the health and wellbeing of individuals and the larger society. Yet no independent review of the potential harms and benefits is required before they go to market.” (p. 35)

Humans evolved to capture attention from each other in real life, and to defend ourselves from it. Now cheap and tireless machines capture our attention all the time, everywhere. They are inhumanly designed to dodge our defenses. Accumulated micro-distractions and micro-deceptions erode everyone’s trust and mental function. Yet regulators cannot agree either about how to limit the overall damage, nor even about how to measure it in the first place.

Chapter 3: And the Brand Plays On

 “When commercial values dominate children’s environment, kids are in danger of losing out on exposure to some of the best human values, such as altruism, generosity, nonconformity, and critical thinking.” (p. 69)

Our brains evolved to associate meaningful phrases with actual human values (e.g. Motherhood, God, Country).  When a child’s mind instead locks onto a slogan optimized for attractiveness by a focus group, the child fixates on something slippery which can never teach it trust.

Chapter 4: Browse! Click! Buy! Repeat!

 “When corporate executives talk about reducing friction, some of what they mean has to do with reducing external barriers to buying, but it also means reducing or eliminating our intra-psychic friction—the cognitive and emotional brakes that enable us to set limits on consumption. For that reason, kids are not just fair game for advertisers—they are essential targets.  Their immature capacities for judgment and impulse control render them especially susceptible to marketing messages.” (p. 81)

The younger a child is, the more innocent its brain, apt to believe the propositions it is exposed to, the longer damage to learning will last.  For a child to waste crucial brain-cells learning bad habits and things which are not true is a tragedy, while for a marketer those represent long-term investments.

Our Alexanders are not Jesuses, nor Mohammeds

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Chapter 5: How Rewarding are Rewards?

 “In nurturing environments where there are opportunities to explore the world on their own terms, young children are intrinsically motivated to learn, to gain competence, to strive for autonomy, and to satisfy their curiosity.” (p. 107)

Natural environments (unlike synthesized ones) can be instinctually explored in continuous space and time, exactly what a brain evolved to do. Only interaction with unbiased, natural statistics allows a brain’s zooming algorithm to converge on trustworthy solutions. Alternative statistical profiles, such as artificially “intermittent rewards,” undermine that algorithm by over-stimulating dopamine release.

Chapter 6: The Nagging Power of Pester Power

“Except for the fact that children and families are being harmed, there’s something darkly comic about living in a commercialized culture that thrives on business models dependent on encouraging obnoxious behavior in children. No sane parent would welcome people into their home whose every interaction with children is designed to instill in kids such intense desires that they nag incessantly to get them fulfilled.  Yet that’s exactly the goal of all advertising to children.” (p. 123)

Messages and interactions optimized to produce revenue from children must of course somehow free that money from the family coffers. But using children to communicate a sales pitch inserts family conflict and undermines trust.

Chapter 7: Divisive Devices

 “Whether with reluctance or open arms, we have invited into our homes powerful, seductive entities designed to generate profits by monopolizing our attention. And they don’t give a damn about our family relations or our children’s wellbeing.” (p. 131)

“Like all other nervous systems, ours evolved to forage, not produce. Humankind uniquely produces things that captivate our senses, and now they do” more than ever. (Sensory Metrics of Neuromechanical Trust, p. 2334)

Chapter 8: Bias for Sale

 “A society’s material culture simultaneously reflects and influences the values, norms, preferences, and taboos of that society. Stories and toys represent a significant component of the material culture belonging to childhood, and they profoundly influence how children make sense of the world around them, including how they view and experience themselves and others.” (p. 154)

Stories and toys sell better when optimized for pre-existing concepts and stereotypes. Oversimplified ones sell best of all. But when it comes to social values, pre-existing means backwards-looking, and simplified means caricatured. Backwards-looking caricatures describe regressive attitudes like racism, sexism, and mercenary individualism. Those are already built into mass-produced communication, but kids absorb them fastest.

Chapter 9: “Branded Learning”

“Because [corporate-sponsored teaching materials] are often slickly produced, require no up-front cash outlay, and can bypass school boards and be sent directly to teachers, they may appear to be a godsend to cash-strapped schools.” (p. 169)

Corporations have money and underfunded schools have young eyeballs, so an inevitable market-driven (but corrupt) transaction lets corporations disguise their advertising as educational material, offered to schools for free. But there is no such thing as free information. In this case kids and society pay the price.

Chapter 10: “Big Tech Goes to School”

“The value of quality, teacher-driven instruction is well supported by research. There is no credible research supporting industry claims that online, personalized learning programs improve academic outcomes. Test scores do not rise. Dropout rates do not fall. Graduation rates do not improve.” (p. 185)

Human brains evolved to learn from physical objects and physical people in real life.  Pixels and frames on screens are so chopped up, they only carry one millionth of the detail young brains need to trust their eyes, as long-established laws of neuroscience prove. So screen-based inputs of any kind not only don’t help reading and writing, they cause actual harm to seeing itself. 

Monetizing Children’s Brains Means the End of Our Species

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Chapter 11: Is That Hope?

 “In the United States, two types of laws would help to stop tech companies from exploiting children.  A national privacy protection law, which we do not have, and adequate laws protecting the rights of children, which we also do not have.” (p. 199)

As long as US law more successfully protects growing capital than growing brains, capital will damage children.

Chapter 12:  Resistance Parenting: Suggestions for Keeping Big Tech and Big Business at Bay

“Six principles of child development to help adults make decisions about introducing tech to young children:

1. Young children live and learn in the context of social relationships.

2.Young children use their whole bodies and all their senses to learn about the world.

3. Young children learn best and benefit most from direct, first hand experience in the world of actual relationships and objects.

4. Young children are active learners who learn by inventing ideas.

5. Young children build inner resilience and coping skills through play.

6. Young children make sense of the world through play.”

(p. 210)

All humans, young children especially, evolved for interaction in the three-dimensional real world, which is our native sensory interface. Synthesized inputs, or even real inputs selected for impact, provide fake data and thus undermine real learning. 

Chapter 13:  Making a Difference for Everybody’s Kids

 “I am for a world where children are universally valued for who they are, not for what they or their parents can buy. Where family and community values no longer compete with commercial values for precedence in children’s lives. Where kids have lots of “in the real world” time with their friends and with the adults who love and care for them. Where their friendships can flourish without interference from, and monetization by, tech and media companies.”  (p. 239)

The environments in which brains grow and learn best are the natural, socially supportive ones for which they evolved.  Because all experience is training data for a growing mind, commercial interference damages learning in often irrecoverable ways.  Monetizing children’s brains means the end of our species. 

Facebook Rebrands Itself After a Fictional Dystopia

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The Battle for the next generation’s sanity

This point summarizes Professor Linn’s book. The sensory and social needs of growing children are actively opposed by the needs of capital. Widespread and growing monetization technologies are already eating the brains of our young.  Legally. And sometimes the young even like it.

Attention is easy to harvest because humans offer it so freely. But that doesn’t make the ethics of attention-harvesting different from those of organ-harvesting. Both attack vital biological systems, and thus share a dysfunctional dynamic which, above a very low threshold, ensures that revenue can only derive from inflicting  harm.  As targets, children provide the easiest profit and suffer the longest-term damage.

In recent years bosses and hiring managers worldwide have privately lamented the latest generations’ poor social skills, low attention span and diminished motivation, to say nothing of their defective team spirit, absence of critical thinking and decline in physical endurance. Young people now don’t simply work as well as earlier generations. Studies confirm these mass deficiencies, which happen to be the same problems this book reveals.  Thus, the decision made decades ago, under US President Reagan, to expand the dissemination of kids’ ads has now exploded into what one should expect: sad, damaged, dysfunctional adults everywhere.  The economy is already hurting from how it abused human brains twenty years ago, long before today’s far more invasive technologies took hold.

Although Linn doesn’t stress this point, the class of guilty parties is obviously not limited to large corporations. .Tiny startups and lone influencers can also do damage as they desperately flail about to attract  revenue and attention. The problems Linn points to are deep systemic ones: How can society neutralize a wide class of market mechanisms which have been optimized for hundreds of years to produce revenue by any available means, including means that  have a damaging effect on  children? Is it reasonable to think we can stop capital from doing what it’s best at? Legislation—like the Five Rights bill in the UK and COPPA2 and KOSA in the US—is a start. But it’s not enough.

As of now, the biggest companies in the world have promised their shareholders money produced by  strip-mining the brain-cells of future generations. Can that be stopped? Seen from the coldly mathematical perspective of information flow through space and time, the problem is even worse than what Professor Linn describes. And the possible solutions will inevitably be more profound.

It Started with Cave Art and Loincloths

Allow me a parable. A long long time ago, in Paleo Paradise, people were only exposed to each other and Nature, and paid attention accordingly.  But human interests are fickle, so to manage them somebody, let’s say a proto-administrator, invented figurines and cave art for people to look at, and loincloths to keep them from looking away. Ever since then, humans have seen less and less of each other and the natural world our sensory instincts evolved for, and more of man-made things which exploit those instincts. In fact as a species we’re proud of those creations. We call them art.  When they make money, we call them entertainment or advertising.

The takeaway message is that attention has long been for sale, but it’s never been so cheap. The ancients had salesmen, but not rack-mounted computers serving a million times the harassing sales pitch for the price of a human salesman and with no qualms about the quality of the message.  A few decades ago new active technologies—radio, television, video, cable, internet—let machines represent live talking people. Recently, the ability of The Machines — designed to micro-monitor, micro-monetize, and micro-prod — increased hundreds-fold thanks to the omnipresence of mobile devices. As a result, machines now capture attention far too efficiently for human sanity and safety.  The open security holes of our nervous systems have been utterly hacked. Human communication is corrupt in every medium but the air we breathe.

Roughly, a species whose intimate, subtle social communications evolved through a million years of live campfire singing, dancing, and group hugs has in a couple generations become thoroughly immersed in ever-more-mesmerizing panoplie of blinking things, whose primary purpose is to capture attention and induce belief.  And those things work. The bandwidth and authenticity of human interaction has been dropping steadily since cave-times. Now humans know less and less how to feel, to move, to see, or to connect with one another in more than caricatured ways. The mechanism at the core of the problem is recordable communication. Things like texts, tweets, likes and videos are not even empty calories in terms of biological signals. They provide no calories at all. Our nervous systems are failing from informational starvation, and trust — the essential cement of human society — is dying by the year.

If you worry about Platform Capitalism and the Rise of the Machines, then think about this:  robot-toys, robo-calls and robo-therapists pretend to be our friends, but secretly they obey their spreadsheet overlords.  

The Science of Rebuilding Trust

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Grand Projects

Humanity has solved problems this hard before, or almost as hard.  Water-pipes made of lead, exploding boilers, crashing trains and cars, toxic food, fake accounting, risky drugs, filthy restaurants, the list goes on and on of tricks we’ve learned to keep the things we make from killing us. As a general rule, when society realizes that saving or making money here creates danger over there, it makes laws and sets up snap inspections. Think financial enforcement, or health inspectors who check that restaurant dishwashers use water that’s hot enough.

Killing bacteria by turning up a thermostat is straightforward.  Killing the influence of money in communication is far harder, since at present capital owns the major channels and doesn’t want to part with them.  In that light, here are some angles for regulators to use in protecting children from toxic commercial interactions:

Disclaimers don’t work; double-blind does.  Any self-respecting judge, I hope, would laugh out of the room the legal fiction that a printed disclaimer will insulate the unconscious against manipulation. The unconscious doesn’t work that way. Learning requires autonomy, so all manipulation harms it.  Fortunately manipulation can be measured objectively, as advertisers do, using randomized testing (“A/B testing”).  As long as regulators can look over the shoulder of marketers measuring ad impacts, honesty has a chance.

Disgorgement discourages damage.  Ill-gotten data, like ill-gotten money, should poison the well. If for example algorithms are trained on kids’ private profiles, or on racist historical data, not only should the data be purged, algorithms and workflow trained on it should be wiped clean.  As an incentive principle, the ease by which technology violates trust must be balanced by draconian consequences when it crosses that line.

Transparency brings balance.   Trust only works when everyone has the same high-quality information.  So private claims about ad “eyeballs” or behavioral impact — the kind of claims companies use to get money from investors and advertisers — must be equally available to the public and to regulators, because those claims are proportional to the public harm being done.

Health Not Test Results.  Until kids again become happy, energetic, social, curious, and motivated, they should get more music, art, live games, and physical activity, and less of everything else, especially technology.  Written tests of academic performance mean nothing compared to live 3-D tests of nervous system function.

This month, the US Senate is considering two laws which would help the situation enormously: the Children’s Online Privacy Protection Act (COPPA 2.0), and the Kids Online Safety Act (KOSA).  The Senators who vote should read this book.
In fact, Who’s Raising the Kids should be required reading everywhere, especially in countries (like France) with strong protections for public health. But also in countries (like India and Pakistan) whose advertisers seem proud of teaching kids to nag and pester parents (p. 117).  When well-paid grownups brazenly brag about wrecking kids’ relationships, children are doomed.

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post How Capital Eats Its Young appeared first on Fair Observer.

As a lifelong physicist, I most admire the uber-technologists whose primary accomplishments are not merely in marketing or software optimization, but in mastering Laws of Nature so severe that cheating can be deadly in every sense.  Rebooting and re-entry are entirely different realms.  Those who change humanity in those domains, deploying natural law within their lifetimes, are the Alexanders of today. They have conquered whole new worlds alone to make a lasting imprint.

So it pains me when they say things that are silly and destructive, things outside their core domains with lasting impact, but impact in the wrong direction. 

Alexander was a conqueror and administrator, not a spiritual leader. His specialty was making people do his will, not healing and transforming them as humans and spiritual beings like Jesus and Mohammed set out to do.  To my knowledge Alexander didn’t speculate aloud on how to pray or meditate, even as he remade cities in his wake.  Yet some new Alexanders talk of uploading our personalities in various file formats, and speak of so-called “digital communication” as if it bore some actual resemblance to real live human touch.  Such talk is an insult not just to human decency and common sense, but to the very laws of Nature on which such folk presumably build their empires. 

Facebook Rebrands Itself After a Fictional Dystopia

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For their children’s sake, I certainly hope they ignore their own advice in dealing with kids.  An algorithmically mesmerizing blinking piece of glass is not a substitute for loving lips and giggles. Parents know this, children need it.

I have done the bandwidth calculations now for years, the latest published just last week , the earliest published in a prestigious journal, showing implications of the rather simple idea that trust requires continuous re-calibration[].  I enjoy explaining these bandwidth calculations and implications in person to almost anyone, but especially to independent-minded technologists like myself.  For free, if necessary.  

An effective, potentially change-your-life explanation requires interactive 3-D proximity in a quiet location, AKA face-to-face. By the numbers, proximity bandwidth beats a kilobyte of explanatory text at least a billion-to-one. At the opposite extreme, here is an even more over-compressed (80 bytes), caricatured cartoon “explanation” of this very same deep point, the point the titans miss: trust is built from high-bandwidth neuromechanical interaction, nothing else.  From our eyeballs to our eardrums to our spines and souls, human muscle tissue vibrates and our brains reciprocate those vibrations at multiple scales.  Those vibrations constitute our informational oxygen. We need to be gentle with them.

Brains Explained: Vibration all the Way Down

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So my lord Alexander, I beg stop toying with the human spirit.  That is foolhardy and dangerous, and presumes that you can fix what you might break. You already have accomplished more than almost any human, pushing size and scale beyond the limits Nature set. 

But your approach will fail with human brains. When dealing with information,  the least rules the greatest. Near-infinite room at the bottom, but none at the top. Nanoscopic ultrasonic wavefronts, not big clunky chunky bits. Always moving, never stopped.  Fluid flow, not frozen memories. Nothing to be stored, much less uploaded.  Just like mere integers cannot hold real numbers, no simple set of propositions or stored digits could restore a human spirit or make up for lived experience. During Catholic Mass, the prayer “Our Father” rises up from murmuring human voices. It is not a list of abstract PowerPointed bullets up for rifling.

This clean and simple technical conclusion was written by Mother Nature eons back in equations you respect, equations like those of Mr. Newton. Written in her usual cursive hand. Nature also wrote them into our bodies’ inflammatory reactions to digital decalibration and damage, damage you may promote.

My lord Alexander Technologist, triple-check your technical understanding before deploying at scale. If your first rough estimate of what the human brain can do is off the mark by much at all, much less by millions-fold, or if you accidentally introduce a subtle poison, the damage to childrens’ brains could be considerable.  Don’t force anyone, especially kids, to hook their minds to interfaces which are bad for us.  Loneliness, anxiety and addiction are bad enough as it is.

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Our Alexanders are not Jesuses, nor Mohammeds appeared first on Fair Observer.

Mostly the story mocks simple-minded people. A thousand years ago an unnamed guru said the world is supported on a turtle, but couldn’t say what the turtle rested on.  A hundred years ago a little old lady, believing the Earth to be flat, made the same claim to scientist William James:

“If your theory is correct, madam,” he asked, “what does this turtle stand on?”

“You’re a very clever man, Mr. James, and that’s a very good question,” replied the little old lady, “but I have an answer to it. And it’s this: The first turtle stands on the back of a second, far larger, turtle, who stands directly under him.”

“But what does this second turtle stand on?” persisted James patiently.

To this, the little old lady crowed triumphantly,

“It’s no use, Mr. James—it’s turtles all the way down.”

Fair enough.  Infinite stacks of turtles, or infinite stacks of any real objects don’t fit well in finite space.  So the lady’s version of what holds up Earth lacks support, and thus falls flat.

But other infinite stacks work fine.  In computer science, for example, the concept of infinite regress shows up in iterative approximations, or when a program invokes itself (recursion).  In geometry, some patterns contain smaller copies of themselves, patterns inside patterns (fractals). In those cases, the phrase “all the way down” represents nested multiscale interactions, among the most elegant structures possible. That’s the kind of simplicity scientists love, because it lets one theory cover everything. Let’s call it a multi-scale theory. So simple it defies logic.

For example, music is built of multi-scale vibrations.  Beats, quarter-beats, sixteenth beats, fundamental notes and overtone harmonics, consonant chords of notes, predictable progressions of chords, repetitive sonata form.  I propose here that human bodies ring with similar multiscale vibrations, whose ultra-faint, ultra-high frequencies convey sensation and implement motor control.

Coherent vibrations explain bodies so well you don’t need anything else. Human bodies absolutely rattle with vibrations, from circadian rhythms down to myofascial ultrasound. Vibration all the way down.

The Vibrational Bandwidth Stack

Take this very moment, as you read this sentence. While the paper (or screen) is fixed in space, your eye must move in order to see its subtle shapes of bright and dark.  Muscles swing and vibrate the eye to release showers of fresh data, using all kinds of movements, ultra-fast atop slow. A few big lurches per second (called saccades) re-aim your eyeball toward interesting spots, like corners or edges, spots which promise refinement of your brain’s blurry hunches by zooming in.

Moving your eyes semi-intentionally is the normal process of looking. But being made of jelly, the eyeball also wiggles after each yank, adding subtle quick back-and-forth motions (micro-saccades) dancing around the region of interest.  Within the micro-saccades are even tinier and faster wiggles that only the eyeball itself can sense.

Same for hearing. The brain sends boosting signals to the ear, using its predictions to anticipate arriving sound.  Especially to locate a sudden scary sound like a twig-snap, a task honed by millionths of a second.  The brain doesn’t just predict sound into the ears, but into sensitive skin all over the body. When sound impacts you, the waves go everywhere. Ideally you hear sound not just with your ears but with your face, your neck, your chest, your gut and back.  Ideally, your physical experience is unified enough that “sound” and “feeling” merge, no telling the senses apart. Hearing and mechanical sense shouldn’t be separate, in fact their nerve inputs overlap enormously.

Hearing and seeing are external senses, not as important as awareness of one’s own internal configuration. Every animal must feel its body to live. The internal sense (interoception) is built from mechanical vibrations in bones and muscles, vibrations which constitute the information field of the body.

What do those vibrations look like?  We can build our way down from the big slow obvious ones, into the realms of invisible and inaudible. Any muscular motion is fair game, even if it doesn’t repeat. Here goes:

Breathing takes a few seconds per breath.  Waving at a friend takes a second or two per wave. Heartbeats and walking clock in at one to a few (beats/strides) per second, as does shaking someone’s hand. Those muscle motions happen faster than the “biorhythms” medicine usually talks about (like circadian rhythms and menstrual rhythms), but are slow by data-flow standards. Most motions slow enough to see use big external muscles like the bulging “heads” of biceps or quadriceps. 

Smaller, faster motions deep inside you are easier to miss. They originate from muscles close to the spine like the multifidus and psoas.  But they carry much more information. Aiming a laser pointer at a wall reveals body tremor wiggling ten or twenty times per second (Hz). A basso profundo might sing a low note severalfold higher, say 50 Hz, and a soprano a high note ringing fifty times faster at 1000 Hz, with harmonics even higher adding to vocal texture (children can squeak even higher than that). Singing proves humans can vibrate at least that fast.

The threshold of consciousness

But this is where consciousness fails. Frequencies higher than 10-20,000 Hz are beyond human hearing (technically ultrasound), so it’s easy to think our bodies can’t make or use such information. But as engineers know, higher frequencies carry more information, ad infinitum. In fact inside human bodies, ultrasound carries so much information, merely keeping track of it would tie our brains in knots.  Ultrasound is unconscious on purpose, for maximum throughput and bandwidth.

In fact, it’s a law of Nature (pointed out by physics Nobelist Richard Feynman in 1959) that the tiniest things store the densest information. Claude Shannon showed that fast-changing things carry the most bandwidth. In other words, the tighter the resolution in space and time of any signal, the more data it can carry.  So vibrations in a body aren’t created equal, not at all. Information is mostly carried by the smallest, faintest, fastest ones, which sustain and drive the others. That is, they form a carrier wave of interoception and control.

To find the central carrier-wave, we ought to look for precise timing signatures and low-amplitude motions. What are the tiniest, fastest signals in a body?  Which vibrations carry the most information? Let’s look as tiny as we can, at the quantum scale.

The quantum of muscular motion is molecular, as actin and myosin filaments slide past each other, consuming energy to tug a tiny bit.  Every whole muscle is made of thousands of such fibers which fire in concert. A single filament’s length is one millionth of a meter, that is one millionth of the hand-wave at our friend. The filament’s motion endures about one billionth of a second, almost a million-fold faster than anything humans can hear.  Yet because our muscles are made of those nanoscopic fibers, in aggregate those molecular tugs create everything we feel and do.

The principle of aggregating muscle pulses is like ocean surf, but backwards.  When a wave crashes in the surf, a big, single, heaving thing turns into millions of tiny hissing droplets.  Big breaks up into small, all by itself, which is all that can ever happen without adding energy. But life can add energy, so it can run that process backwards, amplifying little things into big ones.

Take a tight flock of seabirds, flapping as they skim the waves. Their vocal cries synchronize their nervous systems tighter than milliseconds, and their eyes see the flapping of each other’s wings almost as precisely. So all the time, each bird can see and hear exactly how her fellows flap, and can arrange her wing-flaps right in line, dead center. Meaning her brain can amplify the tiny, subtle correlations of collective resonance, then add her own energy to sharpen up the central peak. In this arrangement each bird takes in only tiny signals, but by timing magic makes the whole flock heave as one. Turning small and fast to big and slow is the opposite of surf.

So tiny muscle firings, synchronized and lined up just so, produce gross motions in our bodies, just like single flapping birds produce a flowing flock.  How could the brain resolve its timing sharp enough to make that work?  By recycling the “wasted” information from those same muscle firings.

The brain as frequency manager 

Human brains are special-purpose timing processors, encased in solid bone and kept at constant temperature, computing by using nanoscopic wavefronts passing inside neurons.  In function a brain is roughly a vibration-replicator, anticipating and sculpting vibrations, as fed by echoes from the recent past. Human brains send about a million neural pulses out to muscle fibers every second, and receive about million pulses back from neural sensors. Every tiny “pluck” between actin and myosin filaments, as triggered by a pulse, radiates ultrasound waves in all directions. If those plucks add up coherently—the brain’s goal—then some wavefronts will be strong enough to trigger pulses back, telling the brain what’s going on and how to make it better.  These are the same dynamics a “supercollider” uses to shape its packets of protons. It uses the process of tracking precisely-timed kicks.

Please bear with me while I calculate some nervous system bandwidths. Or skip the next four paragraphs, restarting with the phrase “grand mystery.” So let’s do the numbers: first interoceptive bandwidth, then visual.

How many interoceptive nano-vibrations might fit inside a human body?  Fifty kilograms of muscle roughly takes up fifty litres, each containing 10¹⁵  cubic chunks of one  micron on a side (the size of an actin filament, cubed).  Of course independent fixed chunks are nothing like smooth, ever-moving vibrations. But chunks make calculating information easy. By that admittedly clunky standard, at any one time a body contains 5*10¹⁶  volumetric elements (voxels), meaning roughly 10¹⁶ bytes of information capacity.  Now multiply that by frequency (10⁹ /sec) to get an upper bound on internal bandwidth of 10²⁵  bytes/second (ten million billion billion).  10²⁵  bytes/second is the maximum bandwidth we can hope for in a body. That bandwidth is the resource converting molecular tugging to motion.

In particular, precise synchrony determines whether motor output is efficient vs. inefficient.  In the efficient version, micro-tugs synchronize into macro-tugs. In the inefficient version, the microtugs are jumbled, they cancel each other, and dissipate as heat instead of force.  Sculpted microvibrations are also the best way for muscles to nudge clumsy blood-cells through narrow capillaries. And the only way to sense squishy soft mucus clogging squishy soft lungs, and the only way to aim muscular force to expel it.

How does visual resolution compare to the crazy 10²⁵  bytes/second bandwidth of interoception?  Imagine your whole 3D visual world has the same resolution as a high-definition TV. That is, imagine a Virtual Reality environment having HDMI spatial resolution (5 pixels/mm) spanning a cube 40m on a side. (This flight of simulation fancy is just for calculation, it isn’t how brains actually work….that’s actually the point). The total number of volume elements (voxels) in the simulator-cube is  (40*5000)³, i.e. 8*10¹⁵  voxels, or 8 peta-voxels.  That spatial resolution is insane by current standards of VR technology (and also MRI tomography). But it’s is still less than we calculated for interoception.

The brain as creative artist

The grand mystery is this:  our bodies, and also separately our eyes, have spatial resolution in the neighborhood of 10¹⁶  dots at least. But our spinal cords, and also separately our eyes, receive as input only 10⁶  neural pulses per second. The ratio between the two is ten billion to one. Meaning (roughly) that the brain synthesizes and confabulates ten billion dots for every actual data point it gets.  By this calculation, our brains make up 99.9999999% of what we see and feel.

Likewise, the nervous system runs at up to a billion “clock cycles” per second, but our conscious minds can only manage a few words or thoughts per second.  By this calculation, our conscious brains miss 99.999999% of our internal processing. Thus in terms of both data and time, humans brains basically fake it.

The proof of a good idea is how much work it does.  Here are some teasers for applying these principles of vibration and confabulation to your life:

• The spine is the center of everything. Nanovibrations run fastest down the center of the spine and myofascial tissue, making the spine the physical channel, akin to an optical fiber, containing the carrier wave.  A central spine is the perfect trunk-line for coordinating metabolism, interoception, muscular motion, and breath. In fact people with perfect spinal and breath control, like Harry Houdini and the Iceman Wim Hof, can “clench” their spines and breath muscles so that most muscular energy is intentionally “wasted” as heat to keep them warm (i.e. muscular activity for thermogenesis, not motion). A bonus is that according to deep geometric principles, when a spine is operating optimally it ought to feel ecstatically extended and inflated, enlightened in multiple senses. Spinal bliss is what humans ought to feel all the time.
• Emotions are vibrations too   Certain sounds made by many species, not just humans, originate in specific spinal zones, and carry emotions:  whining, roaring, laughing, gasping, snarling, moaning, crying. 
• Emotional connection cross-correlates vibrations  Eye-gazing, singing together, praying together, holding hands.
• Accelerometers can measure biorhythms. Silicon accelerometers are everywhere, even in smartphones (like the Sensie platform I helped design), small, fast, and cheap. While they are still far too slow to detect the carrier wave directly, by sheer dint of bandwidth they could still measure emotional connection via cross-correlation, or individual synchrony by algorithmic measures like symmetry and 3-D power spectrum.
• Energy is information. What sensitive people colloquially call “energy”—the various internal sensations including tingling, opening, connection, electricity, “chi,” and heat—in biophysics corresponds to vibratory information flow. Vibrations flow along meridians and concentrate in chakras. Those stripey sensations arise in the myofascial conduits tracing the spine and limbs, then are simplified into sensation by the brain’s often-mistaken motor data map (or mental whiteboard).  That virtual map tries valiantly to know exactly which conduit runs where, even without good data.
• Discomfort is data.  A brain can learn that map correctly (from healthy experience), or incorrectly (from trauma, constraints, overtraining, or lack of experience). A bad map has defects like wrinkles, kinks, or knots. Defects lead to inconsistencies, which create zones in the body the brain mis-locates, can’t control, can’t make sense of, or can’t even feel. A brain doesn’t like operating in such zones and wants to avoid them. But dodging discomfort worsens the problem by avoiding exactly the data the brain needs to fix its map. The good news is that “good pain” (intense neuromechanical discomfort short of tissue damage) delivers clean fresh data and improved motor function in direct proportion to felt sharpness and intensity. Every pop, click, opening, release, or even spontaneous cramp results from removing a map-wrinkle, acting and feeling like snapping back to grid. Each shift instantly increases motor operating space, often feeling weird or wobbly while getting used to it.
• Ultrasonic grounding = ultragrounding  The weirdest new trick for recalibrating the motor map consists of pressing heavy hard things against central bones, like draping one’s back across iron weights. Pinning down painful myofascial “trigger points” against a heavy inert object provides the brain a guaranteed “zero vibration” reference signal.  The pain might even feel sweet.  Beyond “foam rolling,” imagine “iron rolling.” Deliberate discomfort, pain on purpose.

In summary, multiscale vibrations describe virtually everything in a body, in particular how nanovibrations help it sense and move.  The better we know our bodies’ operating principles, the better we can fix and tune them up.

All that in about 2600 words.  Is that simple enough to defy logic?

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Brains Explained: Vibration all the Way Down appeared first on Fair Observer.

Nowadays, a similarly profitable fantasy builds on a similarly paradoxical expression: “virtual reality” (VR).  Turns out Nature says VR won’t succeed either, because VR will inevitably induce “simulator sickness,” as it always has.

The Industrial Revolution started with steam, allowing fuel (coal) to do the work of many men.  As the technology improved, more and more power became available. Part of that power came from burning more coal. Another part came from improved mechanical efficiency, that is by recovering and reusing waste heat, force and momentum.  Many tinkerers were convinced that by using clever mechanical trickery, such as lifting weights over here in order to drop them on lever-arms over there, engines could in fact “recover” more energy than went in.  Evidence made this hypothesis reasonable, because the trend of recovered energy had been rising upward steadily for decades. Hopefully it could pass 100%.

The idea behind perpetual motion was that if the trick worked — that if a machine could essentially harvest its own momentum to keep itself running forever — then even a tiny excess of power could be amplified and scaled, and no one would need to burn actual fuel any more.

Back then physics and physicists didn’t really exist, but thoughtful people ever since da Vinci have known perpetual motion was a fantasy. A hundred years ago, they proved it scientifically by finding a deeper principle at work, one which absolutely limited the amount of energy in play. The new science said that energy is not created, not destroyed, and certainly not free.  The total energy must be “conserved” (kept fixed).  No free lunch from Nature.  But optimistic tinkerers kept trying anyway, until the US Patent office stopped allowing applications altogether, killing the “technology” for good.

Virtual Reality or Unreal Virtuality?

That fantasy repeats itself with so-called “virtual reality.” According to the evidence, VR gets better every year.  An extrapolation of that trend would let VR replace the boring physical world we’re usually stuck in, literally creating whole new universes (or metaverses) and whole new streams of revenue, almost out of nothing. Free reality.

I know VR cannot work because I happen to know how nervous systems work. New technology won’t fix that mismatch, but at least new research explains it.  That research explains both human and machine learning in the same terms; neuroscience and data science account for both as signal bandwidth. So formerly fuzzy questions about how brains work now have mathematically absolute answers.  In the case of VR, as with creating energy, it turns out there are absolute limits on what brains can and can’t do, limits not provable before.

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There are many ways to prove that VR makes people sick; two will do for now.  One involves how different senses mix together in the brain.  The other involves how much time a brain takes to mix and make sense of them.

Vertebrate brains evolved 500 million years ago to do exactly one thing, a task which even now is far more difficult than memory or speech: making 3D pictures out of tiny input pulses (a computational process called “tomography”).  Our everyday experience bears this out. The sensory inputs into our bodies (and outputs from nerves into the brain) come from eyeballs, eardrums, taste and smell receptors, and especially from millions of vibration-sensors spread throughout the body. Airborne sound hits ears and skin together, and our brains combine them into a single unified experience so solid and believable that we know for sure the world exists, even behind us, even when we can’t see it. Lived sensory experience is unified by the hardware of our brain: that’s how brains work and what they do. Neuroscientists call the process “sensory fusion.”

Obviously, a brain fabricating a single unified experience is the opposite of fabricating two inconsistent, competing experiences, which is what VR forces on our brains.  For example, a gamer’s eyes may be convinced that he is flying high-G rolls inside a fighter plane aloft, because VR is so good at creating visual illusions, making every visible cue consistent with all the rest….looming, moving, twisting, occluding, dropping, all synchronized so the visual world makes 3D sense.

But vision isn’t everything to brains, not even half. In the gamer’s case, all the other senses agree that the body is not moving or flying, but sitting in a chair. Neural signals from the inner ear, the legs, the gut, the spine all confirm no barrel-rolls, no upside-down, no special forces pulling or pushing.  No jet engine sounds rattling the body, just injected in the ears.  In this configuration roughly half the brain is convinced the body is quite still, the other half convinced it’s flying hard and fast.  A brain can’t hold such a deep contradiction for very long, so “simulator sickness” makes the gamer nauseous. That problem hasn’t changed in 40 years, and won’t, ever, because brains can only feel one reality at a time, and the real reality is always centered in your gut, regardless of what the eyeballs say.

Vision and motion

Another insoluble problem with VR is how fast it responds to self-motion. In the regular real world (no VR yet), every time you move your body, neck, head, or eyeballs, the image into your eyeballs (and onto your retina) changes with that motion.  To make its picture of the world, the brain anticipates the physical shift before it moves its muscles, and uses that anticipation to predict what it will see. The brain uses an interactive process of continual exploration and zooming (neuroscience buzzword: “sensory contingencies”). Because the brain makes plans, then sends pulses. And then the head and eyes begin to move. The brain therefore creates internal expectations long before any motion could be visible from outside.

But at best VR can measure your self-motion from the outside, after the fact.  It can’t measure things which haven’t happened yet. (Even access to your brainwaves would not solve this problem, since even brain waves are merely delayed traces of yet smaller and more subtle processes). So even an ideal VR response would be fatally delayed, relative to how your eyes and brain normally work.  What VR shows your eyeballs is not exactly what would come from a real world, but milliseconds slower, and only approximate. The faster you move your head and eyes, the more weirdly a fake world slips under them.

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The core problem is not with VR, but with brains themselves because their task is nearly impossible already. It’s clear most humans see the world in high-resolution (HDMI or better in space, seamless motion in real time). But synthesizing high-resolution 3-D moving images is hard even for supercomputers and MRI machines. It’s even harder for the brain to synthesize so much data (teravoxels) if it gets a million pulses per second of input from two jiggling spheres of jelly (the eyeballs). That’s about a million data points synthesized for each single input pulse.  It’s a miracle that Nature can leverage such internal fakery, then erase the artifacts so perfectly the result seems not merely realistic, but absolutely real. Unfortunately for VR, that miracle is utterly dependent on the 3-D world actually being there. There is no mathematical way to make a consistent world-image from partial, delayed, corrupted data injected into only part of a brain’s input stream, while ignoring all the rest. Our brains need real-live 3D data like our lungs need air, and no amount of hype will change that fact.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

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Those documents show a growing global body count, including sad teenage girls, angry flag-wavers, sex traffickers and foreign dissidents. They prove that Facebook can’t be trusted even with its own security, much less with anyone else’s.

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Imagine if a few years ago, the weirdly-lettered Google had renamed its parent company not the bland abstraction, Alphabet, but the chilling numbers 1984. George Orwell’s novel, “1984,” along with Aldous Huxley’s “Brave New World,” came to represent the dystopian genre of literature. “1984” in particular deployed the concepts of high-bandwidth surveillance and technological manipulation, both now Google’s specialties, to show how awful such a world would be. Naming a company 1984 would have officially espoused the evil Google once foreswore.

Manipulative Interference

In his 1992 novel “Snow Crash,” Neal Stephenson imagined digital mind-worms and a manipulative, immersive, corporate-sculpted social network called the Metaverse. “Snow Crash,” with its virtual avatars, skins and real-estate booms, showed how monetized technological interactions make people miserable. A major point of the book is that people are easy to program. Stephenson’s for-profit Metaverse was the original evil social network, ruthlessly converting human despair into corporate revenue.

The Facebook version will be yet more dangerous — if they can actually build it. At the moment, Epic’s game “Fortnite” is closer to Stephenson’s high bandwidth, synchronous space. Facebook’s version will add wireless, geo-tracking, news feeds, face-reading and biometric scanning — all intrusive technologies that magnify exploitation a hundredfold beyond what Stephenson imagined 30 years ago.

The inevitable result, as mathematical analysis predicted and medical evidence continues to support, is that technological socialization inflicts deep psychic damage. The medical case is simple: Humans evolve to communicate directly with in-born high-bandwidth sensory systems. Any damage to that data flow damages felt connection, but unconsciously, like lead poisoning. Monetized and manipulative interference causes the most harm.

Worse, trying to socialize through technology has horrific impacts on children’s emotional health. Even Stephenson’s original Metaverse, evil as it was, didn’t strip-mine children’s attentional systems for short-term revenue, as Instagram Youth will likely do.  

Unfortunately, those activities are still legal in the US, while lying to investors and government officials is not. Since social media’s damage to children’s mental health became clear only recently, those activities have been incentivized, nay required, in the name of “adding shareholder value.” Blame for past deeds will be legally murky.

Preventing Future Damage

Preventing future damage is more important, and governments already possess the know-how. If Facebook were a person, its relentless, breakneck, reckless disregard for law and safety over decades would make it by any reasonable standard an incorrigible repeat offender, an addict, a sociopath. Its data flows, incentives and resulting behavior show it to be adept at growing fast and making money, but only by means of a toxic business model and lies.

The growing body count of Facebook and similar technologies present a blunt challenge to governance of any kind. Even if exactly the right laws were passed, how could such a company obey? It’s not in its DNA, its workflow or its charter. How can governments deal with hardwired intransigence when public health is at stake?

The bad news is, the bad stuff is easy to hide. There are myriad curlicue ways that a complex, real-time technology company like Facebook can make obvious short-term money while creating hidden long-term damage. The common thread is algorithms that track money but not damage. 

Such systems can be so well-automated, humans may not even know the harm is happening at all. The good news is, all the information necessary to find and solve the problem is right there in the database, if you know where and how to look. (Spying solo into numbers on behalf of CEOs was my main job for several years; database queries don’t lie).

The good news is, governments already protect public health just fine in other domains, through regular inspections. Elevators, building codes, sprinkler systems, water quality and restaurant sanitation all invoke the same common-sense principle that if some technology endangers human beings, the thing itself must be inspected by a neutral party. Inspect the thing in question, not the paperwork that might be fudged. Governments know that when saving money costs lives, legalistic disclaimers and self-regulation don’t work. Random inspections do.

A crack team of independent data scientists, given support and read-only access to the Facebook databases and file systems, could in short order provide public health answers the public needs but that Facebook executives themselves don’t know.

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Because damage done in ignorance is less culpable, some sort of amnesty will be necessary to grease the informational wheels, say immunity from prosecution for past deeds in return for new transparency, the way South Africa’s Truth Commission did. Right now, putting numbers on the body count and stopping it matter more than finding whom to blame.

Inspecting safety numbers is the same essential public-health service performed by a city inspector checking the temperature on a restaurant dishwasher. Toxic social-media metrics like “time on device” and “cost per conversion” already hurt children right now, and they’re already tracked. Best of all, their algorithmic influence can be turned off in an instant. Volunteers?

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

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But if by “upgrade” you mean what most people and most scientists mean, which is becoming better at productive activities — memorizing, multitasking, getting stuff done — then your answer could be found in a new book about neurohacking: “Smarter Tomorrow” by Elizabeth Ricker, the founder of NeuroEducate.

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This book hails individualists, early adopters, “quantified self” experimenters, NeuroTechX hackers and free thinkers with the idea that proactively seeking higher intelligence and more efficient cognition will make one’s life better. But “peace through productivity” is a contradiction for nervous systems that didn’t evolve to be productive or smart.

So, “Smarter Tomorrow” is only the second-best possible book on upgrading brains, awaiting agreement on how they work. But it is still worth owning for the writing, the science and the scientific method alone. I can imagine no better, more actionable summary of modern brain science.

The Book: “Smarter Tomorrow”

Ricker’s writing is likable in all kinds of ways: nimble, accessible, insightful and funny. The graphs, summaries and takeaways are copious and clear. Her research is expansive and well synthesized, spanning pretty much everything brains need: nutrition, sleep, exercise, diet, emotional health, daylight, friends, motivational tricks. I already knew some of the tricks, like using biofeedback to resynchronize breath and heartbeat, but others — blue light replacing caffeine — took me by surprise. She waves the banner of “evidence-based science” more proudly and successfully than anyone, making this book a fair reflection of published scientific results. 

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Her upgrade targets are psychological concepts like executive function, emotional self-regulation, learning/memory and creativity. Her neurohacking tricks are based on well-established neuroplasticity principles (which I’ve also written about) and are justified by peer-reviewed experimental studies across the gamut of experimental neuroscience, including test batteries, neural recordings, MRI and EEG. (The one missing strand of scientific support, information mathematics, is the strongest of all.)

“Smarter Tomorrow” is two kinds of manifesto. At the most personal level, it promotes acceptance of neurodiversity and scientifically-informed self-help. That personal vision is the most personally inspiring to me. To implement that grand vision, Ricker’s book also provides a technical manifesto explaining self-experimentation of the plodding note-taking variety — including how to use a scientific notebook. She offers practical advice to collaborate with fellow neurohackers, to self-document, to seek medical advice, to allow time for reflection, all the way to providing creeds and checklists for the reader to try. 

Fortunately, Ricker applies a wonderful inventiveness to the paradoxes of performing tests on oneself, especially those (like placebo tests) which involve tricking oneself as the subject. For example, the book even contains templates for measurements I thought were impossible, such as monitoring improvements in one’s own emotional regulation. In that same practical vein, Ricker dedicates whole chapters to how to choose a goal, how to motivate yourself, how to validate and track your progress. I almost wish I were the type to use such tests myself — they seem so good.

All of Rickers’ advice is as good and clear as it gets. Her book reflects current psychology and neuroscience almost perfectly. But from those sources, it also inherits a few key faults.

Two Authors’ Stories

Ricker passionately defends neuro-diversity by telling of her grade school reading teacher, Ms. Lecto. Her teacher’s personal confidence and attention saved young Ricker from a life of remedial classes (she ultimately got degrees from Harvard and MIT, and this book is the best explanation of experimental design I’ve seen yet). There is magic, Ricker asserts, in individual diversity and detail — magic that can help us help ourselves.

My life has a similar story with a similar message. I was never good at doing math, only at intuiting answers and sanity-checking them in multiple independent ways. After college, I took four years off and then began a very difficult graduate program (physics) in a very difficult place (Caltech). I was doubly behind my brilliant classmates at doing the math-intensive problems sets and tests we had to pass.

Enter my savior in multiple ways, Professor Kip Thorne. First, the mechanics and gravitation ideas he taught us gave me wonderful mathematical tools with names like “eigenmode” and “multipole,” tools that I only recently discovered connect vibrations in the human body with data processing the brain performs. One such weird shape, “quadrupole waves,” makes up the gravity waves Professor Thorne spent his career looking for. (He received the 2017 Nobel Prize for finding them.)

His quest was not evidence-based. There was no evidence then for gravity waves, only Albert Einstein’s mathematical prediction from a hundred years ago that they could and must exist. By believing math was true, evidence or not, Thorne inspired me to do the same. 

He also encouraged us students not to grub for grades in his class but to focus on creative research. I acted on those twin suggestions in my dissertation by using ever-true math to illustrate that neuroscience made a major goof: They didn’t know at all how neurons work. Neuroscience insisted then (and still mostly does) that the pesky noisy crackling in their beloved neural data is just noise, because it sounds like noise. So, neuroscientists average it out, blurring and removing the crackle to improve the signal they seek and ultimately publish.

Unfortunately, the mathematics of bandwidth says that “noise,” in fact, contains most of the brain’s information. Timing details always carry more information than averages. That’s how details work. In her story of learning to read, schoolgirl Ricker needed to manage her own learn-to-read process, which required managing more moment-to-moment details than her classroom permitted. Fortunately, the tutor, Ms. Lecto, provided young Ricker the freedom and bandwidth her nervous system needed, through both challenge and trust. In the story, Ricker’s academic career was saved by personal attention, autonomy and fast feedback. That is, by interactive neuromechanical bandwidth, the mathematical foundation of all trust.

That “bandwidth principle” has been my career. I once published a research paper provocatively titled, “Fine Analog Coding Minimizes Information Transmission,” using simple math to make a simple point. When one “does the numbers” on bandwidth, one finds that yes, “slow and careful” reduces uncertainty, but the slow part causes more damage to information flow than the uncertainty part helps. So, counterintuitively, “quick and dirty” actually increases information flow.

Likewise, in computer science, every database or printout call slows down real-time speed. Optimized code never audits itself. Taking notes slows you down. And so on.

Ricker knows this. Self-testing, she points out, only proceeds as fast as its slowest step. Her “laggard” example is a memory-enhancement supplement that takes months to kick in, slowing self-experimentation to a crawl. At the fast end, she offers self-tests only 15 minutes long, deliberately accelerated to speed your neurohacking quest. But that gesture proves the basic limitation of any method of self-experimentation, tracking and monitoring: Tracking hobbles the very biofeedback it is supposed to enable.

The trend that higher-bandwidth biofeedback produces better (stronger and more generalizable) “brain upgrade” benefits is obvious in hindsight in the book. Ricker’s childhood experience with Ms. Lecto had the highest possible interactive bandwidth of two human nervous systems coupled in real-time. That interaction had a correspondingly high impact on her nervous system. Of the solo therapies Ricker describes, the very best are exercise and yoga, which have the highest bandwidth recalibration (i.e., feedback) paths possible because no tech slows them down. Of the technological therapies, the best provide biofeedback directly from a relevant bio-vibration (say heart-rate-variability) to the low-level sensory system (say via a tone) without selecting, editing or quantizing.

Relative to those continuous, fast-changing tones, 15-minute, multiple-choice tests are yet a thousandfold lower bandwidth and don’t produce the same life-changing results, nor very generalizable results. The problem with “cognitive performance” as a measurable goal is that it takes so long to measure but is so narrow. Helping the nervous system from the start by knowing in advance what it needs works better and faster.

That’s how placebos work, as Ricker masterfully explains. A brain’s main job is as a “prediction engine,” anticipating and sculpting micro-vibrations into macro-vibrations, and experience into motion. A placebo of whatever sort is a (deceptive) information stream consistent with, and thus supporting, a chemical or surgical intervention. The placebo in the famous experiment was fake, but the algorithm of associative self-consistency is how prediction works in the non-deceptive real world, for which nervous systems evolved.

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That means expecting success (via faith in God or via “Bayesian priors” in math) is necessary for predicting well in any brain or algorithm, period. Second-guessing slows you down. As every athlete knows, confidence and flow work best in real-time. “Flow,” as Ricker describes, is the ultimate state of the nervous system. That is neuromechanically true, which makes flow useful in life. Flow is what nervous systems were born for. Flow is ultra-high bandwidth physical operation, but it only works in person.

At the clunky end, ultra-low bandwidth tasks include memorizing, thinking, testing and auditing. Anything categorized, anything symbolic or abstract, and anything called a “task” or a “decision.” Or anything employing digital technology, which messes up precise timing nervous systems rely on, and also compresses the sensory/motor interface enormously. Anything with interruptions (multi-tasking itself is a sin against nervous systems). Basically, most “cognitive enhancement.”

The Natural Test

The gold standard of human nervous system function is real-time inside bandwidth,  rather than outside getting-stuff-done results. So, the natural test of any upgrade intervention, whether from “Smarter Tomorrow” or elsewhere, is simple. Do I get better results using this (meter/electrode/test) for an hour versus an hour doing something equivalent with my body and/or another human being, no technology involved?  

My contention based on undisputed laws of information flow through space and time, and easily testable by Elizabeth Ricker’s protocols, is that in hour-for-hour straight comparisons against technological interventions, native real-life human collaboration will provide higher bandwidth and better results than tech every time. The placebo principle will be crucial to human success, in that subjects must be motivated to out-do technology and must believe that they can. That sounds like the ultimate battle, competing against machines on the home turf of our own bodies. A real fun game, with high stakes.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Neurohacker Today, Smarter Tomorrow appeared first on Fair Observer.

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This month, finally, we can read how it happened, and clearly enough to do something. But I’m not just writing a book review, because the interaction of math with brains has been my career and my passion. Plus, I know the author. So, after praising the book, I append an intellectual digest, debunking the hype in favor of undisputed mathematical principles governing both machine and biological information-processing systems. That makes this article unique but long.

Bringing AI to the World

“Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World” is the first book to chronicle the rise of savant-like artificial intelligence (AI), and the last we’ll ever need. Investigative journalist Cade Metz lays out the history and the math through the machines’ human inventors. The title, “Genius Makers,” refers both to the genius-like brilliance of the human makers of AI, as well as to the genius-like brilliance of the AI programs they create. Of all possible AIs, the particular flavor in the book is a class of data-digestion algorithms called deep learning. “Deep” as in “many layers of complexity,” not deep as in “profound and simple.” There’s a big difference.

Metz’s book is a ripping good read, paced like a page-turner prodding a reader to discover which of the many genius AI creators will outflank or outthink the others, and how. Together, in collaboration and competition, the computer scientists Metz portrays are inventing and deploying the fastest and most human-impacting revolution in technology to date, the apparently inexorable replacement of human sensation and choice by machine sensation and choice. This is the story of the people designing the bots that do so many things better than us. Metz shows them at their most human.

I won’t burden you with too many of Metz’s personal observations about these great minds but for a few illustrative examples. The father of deep learning, Geoff Hinton, dislikes “too many equations” (that’s my kind of scientist). Mark Zuckerberg, the founder of Facebook has a speech tic. Google’s founder, Larry Page, believes technology is good.

But this is also the story of the mathematical tools that those people discover or invent, math that will long outlast them. These technologists discover new principles before they program them into computers. Then, they tune up improvements until their creations sing or take over the world. I recognize them as my tribe and I thrill at their triumphs. I’ve been there too.

Along with the people and their math, Metz includes the kind of potent business insight he’s been long known for — the kind obvious only in hindsight. For example, he points out that Microsoft forced its own AI researchers to use clunky, closed Windows programming platforms. That rule so frustrated those researchers that they left Microsoft, and thus left Microsoft behind in the AI race.

Metz’s chapter titles convey his sense of drama. The chapters introducing the players have titles like Promise, Rejection, Breakthrough, Ambition, Rivalry and Hype.  The chapters about AI goes rogue are similarly telling: Deceit, Hubris, Bigotry, Weaponization and Impotence.

Tech Triumphs

“Genius Makers” describes the explosion of AI as yet another California Gold Rush, saturated in hype and money much like the state’s earlier movie, aerospace, cult and startup booms. For generations, California has specialized in mating money with persuasion, technology and scale. It moved fast and broke things.

Metz records AI’s recent history with the players. Everyone agrees these events were driven, or rather incentivized, by the universal pressures of money and persuasion in all its forms: publicity, reputation, image, hype, power.

Certain behaviors emerge when money meets persuasion: hucksterism, overselling, a focus on pleasing funders. Because money tends to flow toward anticipated profits more than demonstrated usefulness, those who wish to bend it lean toward shoddy metrics and calculation tricks. In fact, that bending is a law of information physics. Much like glass, money has a refractive index on messages, bending them toward the source that paid their fare.

Both honest reporting (like Metz’s) and common sense tell us that most humans, companies and probably governments would act in the same narrow, self-serving ways as the people in this book. Using that insight, one can dispense with the particulars of who did what. Not to remove the human element, but to focus on the core question apart from all the hype and bogus claims: What is this technology, and how will it impact us?

The most important point is that AI is not based on brains at all. The best quote comes from computer scientist Alex Krizhevsky: “Deep learning should not be called AI … I went to grad school for curve-setting.” He points out that deep learning is really just a form of math called “non-linear regression.” Mathematical inference for complex statistics, not a brain at all.

But what a form of math deep learning is! It was founded on the most reliable scientific principles possible, those of thermodynamics and information theory (which share crucial concepts in common, such as entropy). Those twin principles doubly illuminate the target of an ultimate inference engine, so researchers could hit it directly.

The specific tasks set for AI varied from general to specific. The most general goal of AI, in common to all tasks, was to “learn” (i.e., map and distill) the underlying structure of a target data space upon exposure to its data. More specific tasks were to recognize examples from the target space, categorize them or use them to control future data.

Researchers took on practically every commercially viable or publicity-worthy task possible: face recognition, speech recognition, speech synthesis, speech translation, text translation, image classification, image analysis and image synthesis.

What makes a task commercially viable? Something humans aren’t good at. Humans are very good at seeing, hearing and touching the real world. The further from it or the more abstract the task, the worse we do. In general, AIs are the opposite. So, an AI that analyzes spreadsheets or computer programs might be profitable, but not one competing on our native turf — say, identifying crosswalks or talking sense because humans are cheap and plentiful and we do those well already. The most profitable AIs, and thus those likely to take over the world the fastest, replace humans at what they’re paid to do, like “picking” items out of Amazon crates (a problem now solved).

Although it’s typically not profitable to pay AIs to look at pictures (unless you’re Facebook), it can be profitable for AIs to show pictures to people. AIs are very good at observing what grabs people’s attention. Now, they can also synthesize fake, weirdly-interesting pictures and videos. Or they can choose which ads to show, which is where most of the money is made.

AI does two things well: recognition and control. In recognition, the input is data like an image, video or a sound, which its output describes later. Recognition is tricky for mathematical reasons because the so-called “curse of dimensionality” makes it hard to follow slopes and gradients, so they thus need lots of data to train.

In control, inputs and outputs are simultaneous, as the AI interacts with a continuous world: either a virtual game-world like Breakout or Quake, the real world of a grasper, drone or self-driving car. Stuck in 3-space, continuous control not only can use gradients, but it has to. Physical control is made difficult by physical effects like grit, momentum and lighting artifacts. Both recognition and control systems can suffer from the data disease of “overfitting,” a kind of invisible rut in which the AI learns to connect its data dots so well, too well, that it gets confused by new details.

Good training data was (and still is) essential to training any learning system, whether human or AI. The most efficient forms of learning, “supervised learning,” use hand-picked and hand-labeled data. Labels make learning easier because the AI only has to gather statistics for predicting the labels. 

The more difficult task of “unsupervised learning” forces the AI to discover structure in the data on its own, without knowing what the humans think the answer is. Biological learning is unsupervised. In fact, my post-doctoral fellowship at the US National Institutes of Health resulted in a 1995 paper at the Neural Information Processing Systems (NIPS) conference explaining how the brain learns to correct itself using predictions.

The best training data is not evidence but math. In the rare cases when a task is completely rule-based, as with games like chess and Go, an AI can generate legal and legitimate examples internally much faster than it could gather data from outside. That means the AI can gain “experience” at hyperspeed, faster than any human could. Thus, the world Go championship now belongs to an AI, and will forever. The performance of the program AlphaGo became god-like after playing millions of games with itself, teaching itself from scratch using trial and error.

Next, after good training data is the algorithm that learns from it. The first AI, the 1958 Perceptron, just measured a few statistics. The next innovation added signals to reinforce a job well done. Multiple layers stacked up next, so that one layer fed the next. Those static recognition nets later learned to reconstruct sequences. Finally, all those methods were supercharged with statistical modeling and estimates of belief (“Bayesian priors”), which could fill in blank spots.

The laggard in AI is hardware. Even modern AIs are millions-fold less efficient than humans in using data and energy, which is why they need so much. So, companies save a lot of money by optimizing the hardware to match the task, like using special-purpose computer architectures, and even special-purpose chips.

Musk Sounds the Alarm, Marcus Calls Their Bluff

It is a testament to Metz’s deft writing that none of the dozens of geniuses he profiles looks bad in his book. But only two look really good, for standing up alone to speak the truth.

The loudest, most famous and probably most brilliant is Elon Musk. Alone among tech titans, Musk made his mint not in the virtual world of software, but in the physical world of recalcitrant materials and crushing forces: rocketry, electric cars and solar electricity. He takes on mother nature, not man-made protocols. He can’t bluff his way past artificial milestones like the software moguls can, so he has to know his physics cold.  Anyone who can build a working rocket or a high-speed car has my attention when he talks about instability and explosion.

And talk he does. Musk knows how fast and furious runaway exponential growth can be, and he evidently warned a lot of bigshots, up close and personal, that scaling-up the automated manipulation of human beings is a very bad idea, capable of wiping out humanity: “One has to be thinking of ethical concerns the moment you start building the system.”

I only wish Musk hadn’t used the term “superintelligence” for the machines that might take over the world. That vague term plays into the myth that AI is intelligent like brains are.  The immediate threat is not superintelligence but sub-intelligence, as a swarm of soulless, hidebound spreadsheets around the world overrule more and more human decisions about spending, hiring, lifesaving, imprisoning and causing war. Relative to human judgment, it’s possible that spreadsheets have already taken over the world.  Spreadsheets are machines. And spreadsheets are the bosses of the robots and AIs, not the other way around.

The other bold critic of the AI boom is the neuroscientist (not merely neural-net expert) Professor Gary Marcus. He calls out the claim that AI works like brains because he knows that brains do something AIs can’t, which is to learn efficiently. He says, “Children can learn from tiny amounts of information.” Marcus makes a point I’ve tried to make for years: “Learning is only possible because our ancestors have evolved [innate] machinery for representing things like time, space, and enduring objects.” (I’ll explain how that works toward the end.)

The most scientifically pertinent observations in “Genius Makers” come not from AI’s promoters or apologists, but its detractors. Krizhevsky says AI can’t have mathematical intelligence, Marcus says it can’t have human intelligence and Musk says any intelligence will be dangerous. I say deep AI is approaching a mathematical optimum for three specific technical tasks: 1) navigating purely rule-driven hyperspaces like Go; 2) learning multilayered statistical structures like ontologies; and 3) learning low-dimensional dexterous robot control, like warehouse picking. It’s already better than humans could ever be. That’s the problem. That’s why I think those three geniuses are right.

The Bad News Now

Unfortunately, none of those three accomplishments are good for humans as a whole. The first takes away the most honored boardgame in history. The second find ways to distract and fool us more effectively. The third replaces low-paid human labor with even cheaper machine labor — everywhere soon.

Even after scrapping the distracting term “intelligence,” it’s clear something enormous has happened and will continue happening, as energy and hardware inefficiencies are optimized away.

AI’s thirst for data is something yet again because good training data must be flawless. But unsullied, gold-standard data corpuses are a thing of the past. Now, much of the content on platforms like Twitter is created by bots, not people. Most text on the web has been optimized to please Google’s so-called “quality score,” so it can’t be a reference for human communication, nor for anything else. There are only so many trustworthy data sources in the world and most of them are now corrupt. Even if we invent another, it still takes time to trust.

The most commercially successful hidden AIs have been auto-advertising and auto-interrupting algorithms. The most annoying are robo-calls, the bottom feeders. I estimate these calls cost the recipients tens of billions of dollars in wasted time, stress and attention, in order to yield the robo-deployers a tiny fraction of that value. AI makes robo-calls possible in three ways: AI picks your phone number from a list, it concocts the (fake) origin number to show you and it runs the interactive voice pretending to be human. Deep AI can only make those deceptions more effective.

Next up are phone menus and automated services that replace live human helpers with bots. Bots cost such a tiny fraction of what people cost, but they only deliver service half as good. That lopsided ratio seems like a net benefit to bean counters who don’t count human costs. To customers, it spells frustration or despair. Among the worst phone-mail offenders is the original phone company, Ma Bell. At the top end are retail voice bots like Alexa and Siri, which already sound too human for psychic safety (in which case their popularity is moot). Those, and the ads and the deepfakes, are the AIs that work.

The AIs that don’t work, and won’t ever work accurately enough for institutions to be honest about their performance, include face recognition, moderation algorithms to remove otherwise-profitable hate speech, medical diagnostic algorithms, educational-technology algorithms, hiring algorithms and therapy algorithms. Unfortunately, it’s economically and legally impossible for organizational sponsors to be honest about the inevitable failures of such programs.

One large organization profiled in “Genius Makers” claims to make information accessible and useful, but, in fact, it reflexively hides evidence of its own failures, selectively dissembles to manage its image and breaks serious promises to cozy up to power. That’s rational behavior, economically. That’s the problem.

Unavoidable Paradoxes

The “deep” part of deep learning isn’t even the technology’s multilayer statistical algorithms, but the intellectual contradictions it lays bare. Take these examples, for instance.

Can parasitic economies be permitted? Many jobs now involve “sales” — that is getting the attention of people and/or persuading them. When humans do it, that works fine because they can only distract, misrepresent and/or coerce so much. But as robo-calls and robo-scams get cheaper, more effective and harder to limit, the market price of interrupting and manipulating people goes to zero, so intrusions and deceptions multiply and peace of mind becomes progressively impossible. Now that machines can influence people so much and so well, there may be no way to stop them from overdoing it collectively. Micro-deceptions can be invisible when produced and consumed (thus hard to regulate), but they still add up in our brains. Economically, an economy of attention or deception is as unsustainable as an economy of organ harvesting. Death by a million milli-cuts.

What does it mean to disrupt communications? Communication systems work best when they change the most slowly because that lowers the uncertainty in meaning. Activities like rebranding, which redefine the words and images, overtly undermine the very contract of communication. Ever-shifting media and interfaces undermine it less obviously, but disruption still disrupts.

Is trust a bubble about to pop? Trust is quickly undermined and slow to rebuild because of its statistical sensitivity to errors and outliers. In particular, human trust in commercial activities — say, trust in printed money — has accumulated over centuries of human-to-human and human-to-shop interaction. Insofar as trust needs human interaction, its replacement by mere trustworthy markers will create a rickety fake system that bleeds out real trust, yet cannot restore it. The obvious villains are glitchy, stupid and venal AIs. But even a perfectly-working AI can’t convey human trust.

Is it fair to ignore edge cases? Being statistical, AIs are trained on the centroid and can’t accommodate the filigreed detail of diversity, nor can they know when they’ve encountered it. AI makes outliers truly invisible. That disempowers almost everyone, since everyone is an outlier somehow.

All physical representations are fake-able, but digital ones the most. In “Genius Makers,” computer scientist Ian Goodfellow says: “It’s been a little bit of a fluke, historically, that we’re able to rely on videos as evidence that something really happened.” The principle, “the more modifiable, the more fakeable” is true of every physical and virtual medium. If the trend of fakery continues, nothing on a screen will be trustworthy and much of paper will be suspect. 

Is “human intelligence” about symbolic skills that set us apart from other animals or about neuromechanical infrastructure shared in common? What AI does well are things that make us proud of human brains: memory, symbolic analysis, language, categorization, gameplay and story. Animal brains do none of those things. But our brains’ informational needs for authenticity, autonomy, continuity and diversity are effectively animal. Symbolic activities, which clunkily use the sympathetic nervous system, tend to damage neural bandwidth and mental peace (see below). On the other hand, most animal activities like socializing, moving and resting are good for us.

How does one deal with conceptual paradoxes like these? We are facing not just conflicting evidence, but conflicting first principles. So, we have to start from scratch, find which principles are really first and treat them accordingly. For example, Albert Einstein voted for thermodynamics as the most unshakeable physical theory, even over his own theory of relativity.

Ordering first principles is where physicists excel in general. So, below, I’ll spend two short sections on math, before redescribing life and brains from the ground up. This exercise is something Silicon Valley might call a clean-room reinstallation of our knowledge base. The language has to be technical, but you can skip those sections if you want.

However wonderful the arc of nervous system evolution proves to be, at the end of this exercise, we’ll discover that our best-credentialed, best-paid computer scientists collectively (including me) have made the grossest, dumbest goof that software types can ever make: We forgot about the hardware on which our software runs.

My Life Building Technology

Cade Metz might have been born to write this book. In which case, I was born to write this analysis. Here’s my case.

My parents were both nuclear physicists. I grew up as a radio and electronic hardware hacker in Silicon Valley before we called it either hardware, hacking or Silicon Valley. My kid brother had a patent in high school. In 1978, Ed and I pirated the public-address system at Menlo-Atherton High School to broadcast a bootleg announcement canceling final exams. I worked summers at the high-tech plastics factory Raychem, whose rubble now supports Facebook’s galaxy-sized headquarters. 

Like most of the players in Metz’s book, I’m a middle-aged, white male. I try to be sensitive to the most common strains of human racism, and I’m deeply concerned about the algorithmic versions.

After college, I worked at the original Bell Labs as a “laser jock” doing nuclear physics with plasmas. There, I heard John Hopfield present his famous paper about continuous neural nets, showing how they mimic crystallization. His insight inspired me to study such things at Caltech two years later, where he sat on my dissertation committee.

While I studied various types of neural nets, my PhD thesis in physics and theoretical neuroscience explored real neurons, not abstract, artificial ones. In practical terms, instead of producing code to get grant money as AI researchers do, we theoretical neuroscientists had to explain evidence to get grant money. To most neuroscientists, evidence is more important than mathematical sense.

So, I found few friends when that dissertation used math to prove, in effect, that neuroscience was wrong. More specifically, I used big data and to show statistically why “neural noise” must actually be fine-grained information in disguise. Fortunately, for me, that crazy idea did find the two right friends.

One was electronics guru Professor Carver Mead, co-inventor of the integrated circuit. He gave my dissertation its best sound-bite: “One man’s noise is another man’s information.” The other was neural-net graybeard Terry Sejnowski. He invited me to present my dissertation to him, Zach Mainen and Francis Crick. Two years later, Mainen and Sejnowski experimentally confirmed my main prediction in an article that got thousands of citations.

After my postdoc, I moved back home for an industrial job in Silicon Valley. I worked my way up at various startups from a programmer, through staff scientist, to software architect and, ultimately, Silicon Valley’s first “chief algorithm officer.” In every role, I was a sole contributor, crafting my own database queries, writing my own code, creating my own graphs. I had a root password and my job was to tell the CEO and attorneys what was real. (On the side, I sometimes wrote for The Register, as a colleague of Cade Metz.)

That practice gave me lots of experience ranking and testing data-processing principles, in addition to what I already knew about brains and neurons. Those threads merged in a research paper — “Elastic Nanocomputation in an Ideal Brain” — that shows brains must be 3D physics engines.

My wife, Criscillia (who understands the informational structures of narrative and media), and I took two years off to lock into the permanent scientific record our further discovery about the informational interactions brains need. We found that human brains work thousands-fold faster than neuroscience notices, as they must in order to build trust in the senses, and are far more sensitive. I believe our 59-page essay, “Sensory Metrics of Neuromechanical Trust,” is the most scientific explanation of human trust there is. (As an example calculation, we compared the bandwidth of spoken words, about 11 bits/second, to the bandwidth of vibratory social signals, which flow a hundred-thousand-fold faster, in the megabit range.)

Here are two sections explaining brain-like computation for technologists, based (of course) on first principles.

The Quantization Fallacy

The quantization fallacy maintains that the only information that matters is that which is measured. That is to say, quantized and preserved. People who are good at rules and categories — like mathematicians and programmers — are especially vulnerable to this idea, even though it flies in the face of math itself.

No concept in number theory is more basic than the distinction between real numbers and integers. The integers are countably infinite, the real numbers uncountably infinite — in fact, transcendental. Integers have “measure zero,” which means if the integers were somehow removed from the real number line, you couldn’t measure the difference. But no matter how many integers one has, one can’t reconstruct even a single real number from them.

If real values can’t be quantized and the real world is continuous, then those facts together impose an ironclad constraint on representation. They mean one cannot even, in principle, reconstruct a continuous reality from any fixed set of numbers, real numbers or not. So, the mere process of picking a specific spot in space or time, the very process of quantization itself, necessarily and irreversibly destroys information, the same way rounding-off does. Our brains may perceive a smooth, seamless world, but that’s because they hide the pixilation errors caused by neural pulses. The tradeoffs between real and integer, between analog and digital, are as subtle as quantum mechanics and similarly slippery.

When Claude Shannon wrote down the equations of information flow, he calculated real-valued information from real-valued probabilities. No one questioned or questions the fact that information can flow continuously on continuous waves (otherwise, we could neither see nor hear).

Shannon did his calculations using quantized messages. For deliberate, point-to-point communication, you want the same message you sent to appear at the far end of your information channel. To ensure that happens, you have to in a sense freeze-dry the message into some fixed form before transmission, whether in an envelope or a bit, so it doesn’t disperse and decay on the way.

The principle that information is natively continuous also applies to storing and calculating. Digital computers do use fixed bits, but vinyl disks and photographs (not to mention cave art) do not. Yet those store continuous slivers of real life, and analog circuits can process such slivers seamlessly. Yet those, like all quantized or recorded information, represent not just an infinitesimal portion of the real world, but the most malleable, systematically-biased and thus unreliable piece of it. 

Recorded information isn’t really real, hence not completely trustworthy. That means “evidence,” measurements and tests are grossly overrated compared to basic mathematical principles.

Life and the Brain

In the beginning was life, that is self-regulation, plus self-replication. The process of self-regulation (homeostasis) ensures a creature ingests and expels just the right amount of what it needs, using built-in circuits that avoid both “too little” (in which case it seeks more) and “too much” (it backs off). If both extremes are possible in its world, then the creature will have both kinds of circuits. But if only one is likely — say, not enough sugar but never a surplus — then the creature doesn’t need hardware to avoid the surplus. So, instead of a two-sided regulation circuit, it uses a simple one-sided circuit seeking something rare — a circuit we might call “appetite,” which can easily fall into ruts if it learns the wrong things.

All of life runs on entropy, that is the diversity or scrambled-ness of combinations. Thermodynamics says entropy will always increase (become more scrambled) over time. But that only applies to a sealed-off system, away from any energy source. Lucky for us on Earth, we have the sun on one side and dark space on the other. That means life has energy to run those two basic operations, self-regulation and self-replication, both of which rearrange matter in ways that lower local entropy instead of raising it. 

But there’s a catch. As Mickey Mouse learned in “The Sorcerer’s Apprentice,” once autonomous self-replication starts, it’s hard, if not impossible to stop. Furthermore, entropy-reduction mechanisms tend to accelerate toward singularities instead of dying out slowly. That simple observation says that life will cover the Earth eventually and then ever-fancier kinds of stuff will cover that. That is the same end-game of universal sameness envisioned by two geniuses in “Genius Makers.” Elon Musk envisioned an Earth covered by paper-clip factories, and Ilya Sutskever saw an Earth covered by Google offices. (In fact, most of Silicon Valley is already covered by a near-uniform coating of asphalt, concrete boxes and solar arrays.)

The next form of life was single-celled animals, that is creatures that move. Any animal’s most fundamental choice is to dial a balance between saving energy by staying put versus using energy to move elsewhere (say, to get resources or avoid damage). In thermodynamic terms, narrowing or focusing one’s search space lowers data entropy, while spreading, blurring or diffusing it raises data entropy.

After animals came multi-celled animals and, eventually, vertebrates. Each more elaborate body structure came with more complex motor-control hardware, built out of and atop the older, simpler, more basic layers. Biological hardware evolves like the technological type, iteratively and incrementally, starting with metabolism, then vertebrate spines and then limbs made out of mini-spines attached to the main one, all of them meant to be wiggled with ever-increasing precision and elaboration. In such a real-time control system, memory and symbols have no place. Bandwidth is all.

Our immediate ancestors were quadrupeds, then primates, then bipeds. All of those bodies are made of bone and muscle, continuous and springy, not hard and hinged like robots. We bipeds, in particular, could run long distances to chase down prey because our loping gait can be so energy efficient. Mechanical and computational efficiency were our paleo superpowers, a far cry from the wastefulness of digital AI. 

How could our ancestors be so efficient? Let’s pose the problem technologically. Suppose we had a biped “robot” with realistically elastic, anatomical tendons, muscles, joints and so on, like in the series “Westworld.” What kind of robot control would it need?

That robot brain would need to do two things: Make a picture of the world from its sensory input and then use that picture to control its body and world with output. That is, it needs a simulator to turn data into a world model, and a controller to turn the world model into motion.

First, the simulator, because if a creature can’t sense its shape or surroundings, there’s no point using muscles. As bodies contain solid, liquid, gas and in-between, the simulator needs to model all those states of matter — that is, to create both visual and felt 3D images of them in physically reasonable configurations and motions. In other words, a brain must contain a physics engine, a “visco-elastic simulator,” as part of its 3D-image-making (“tomography”) hardware, so it could synthesize either feelings of springy flow such as mucus or of hard brittle bone, each from a handful of neural pulses.

Such a gadget could simulate muscles and potentially learn to control them, probably as follows. Suppose the muscles are strung along a vertebrate spine like active rope, each tiny fiber tightening a bit from a motor-neuron pulse. The mechanical waves from those tightenings travel up and down the muscle bundle, occasionally bending and reflecting like sound does in cables. Sometimes, a passing pulse will knock loose a previously-tightened fiber or trigger a mechano-sensor to send the brain a pulse at just the right time. (Those pulses update the ongoing simulation.)

Such a simulator (e.g., brain) could synchronize those pulses to ring the muscles with pure tones or chords. The idea that a body’s squishy meat could sustain pure vibrations seems silly, but that’s because dead meat damps vibrations. But this would be active meat, whose activity exactly cancels the damping. Call it active anti-damping, in which new muscle firings restore vibrations’ lost energy in order to sustain a continuous, vibrating “carrier wave” that serves as an ongoing reference to the current body state.  The metaphor is that of a supercollider, monitoring coherent vibrations and kicking them back into shape using specially-timed output pulses. This is the “innate machinery” Gary Marcus spoke of that brains use to make sense of space and time.

Here’s how hardware optimization works in brains. The higher the timing precision, the higher the physical precision. So, a brain operating with microsecond timing (e.g., temperature-stabilized) could potentially maintain a phase-coherence in spinal phonons (sound waves) beyond the ultrasonic into the megahertz range. All it takes is a circuit that learns to maximize the amplitude and frequency of the vibrations it reflects.

Such precision is thousands-fold higher than neuroscience ever looks for, so there is no experimental evidence of it yet. But such precision must be there, being dictated by both the laws of math and by the laws of information flow through space and time. There is simply no other way to move a piece of meat. It’s written in the physics. Neuromechanical vibrations are the only information channel with enough bandwidth to feel and control muscles efficiently. No fluid, chemical or electromagnetic channel comes close.

With such a simple structure, lots of functions come for free. Limb control results when high-frequency vibrations, dialed strong enough, aggregate into slower and larger ones. This down-conversion produces motions big enough to move a limb and slow enough to see. (Ordinary body tremor is halfway in between.) Thus, a simple, jelly-management simulator could control a vibrating body just by controlling the amplitude, frequency and specific phase of its physical “vibratory eigenmodes.” 

Spines vibrate at the highest frequencies when straight, so spinal straightening comes for free. Eyeballs are made of vibrating jelly, so vision comes for free. Deep sensations come from midline muscle groups, like those of sadness in the head, nausea in the gut and sex in the pelvis. Each locus has a different set of fluids, spastic contractions, sounds and sensations. With these native hardware modes, something like felt emotions come for free. As vibrating bodies naturally resonate in proximity, high-bandwidth social interaction comes for free. (Predicting, for example, that flocking birds synchronize their flight through their tiniest, fastest flutters first.)

When Analog Brains Meet Digital AI

All this means that human brains must be analog, not digital, fully continuous in 3D space and time. They can’t possibly be using finite-element simulation based on separate neurons, blocks or nodes. The mathematical requirements of tomography mean brains must calculate with tiny wavefronts moving through a kind of jelly, computing in the spaces inside and between neurons.

Once the vibrations are in place to move a 3D body through a 3D space, then quantized states like episodic memory, recognition and symbols can take hold. They would have to be made from continuum waves, like individual transistors can made from continuous silicon. But you can’t do the opposite, making a continuum from chunks.

Exposing sensitive brains to unnatural environments that hack their appetites and trust is hard on them. No creature evolved to resist what it wants, nor to constantly fend off deception — especially children, whose immature nervous systems are so sensitive to training data. Long-established principles of neuroscience hold that early learning and mis-learning matter. Exposing children to AI bots before they’ve learned real people can’t be good.   

The Final Frontier

I know lots of people like the geniuses. I went to a university filled with crazy-smart people like them, so I know how much they trust that math is real. The good ones can’t stand paradoxes. Like many of the heroes in Cade Metz’s book, the ones with the most integrity eschew megabucks and impact in favor of living peaceful lives and building human-friendly tech. Nerds or not, they care more about humans than about shareholder value.

So, once those people realize brains are analog and hyper-sensitive, building their trust from subtle interaction, they’ll ditch the dumb idea that only metrics matter. They’ll ditch artificial intelligence whose main job is to fool us and exploit our trust. Then they’ll invent new tech that helps our brains instead.

Their voyage into data space and hyperspace will explore strange new worlds of analog vibrational control, like toroidal body maps. They’ll seek out new, life-enhancing tuning tools and new civilizing ways for humans to interact. They’ll boldly go where no technologist has gone before, into the uncharted blue ocean of analog human self-awareness and connection, as understood by laws of information physics. They’ll be the most important geniuses of all, and I can’t wait to collaborate with them.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Unbearable Shallowness of “Deep AI” appeared first on Fair Observer.

The better-known story of pole is of women empowered by owning their athleticism and sexuality. Netflix released a documentary a few weeks ago — “Strip Down, Rise Up,” directed by Michele Ohayon — which tells that story remarkably well. 

Since I’m not a woman, I can’t speak about transformations in women’s hearts and studios. But having pole danced with and taken lessons from several of the stars in the film over many years, I can vouch that the documentary portrays them and their “pole journeys” better than I could. In person, they can tell you how pole transformed their lives, and you can see how gracefully they move. Everyone thinks they’re younger than they are.

I appear for a few seconds in the film in clips Ohayon shot at the 2017 US Nationals competition. (My performance there with doubles partner Michele Fabrega came third behind two amazing couples half our age.) I’m one of the few males interviewed — briefly while wearing briefs — in a documentary focused entirely on women.

And what a nerdy male voice it is! It sounds exactly like what I write on Fair Observer, not what you’d hear from a dancer flushed with the rush of performance: “I’m a theoretical physicist and neuroscientist. I do pole to fix my spine.” Yeesh!

The Biophysics of Human Grace

But that awkward, nerdy scientific point is worth considering. Pole does indeed fix spines, and that’s how it makes even middle-aged people more graceful, energetic, sensitive and emotionally calm. The particular socio-physical activity of pole transforms participants’ bodies and nervous systems in the same ways that yoga or Pilates do, only more so. Ask a pole dancer if you don’t believe me. 

Or better, look at one. Close up, in real life, from the front row, while they strut their stuff. Look especially for subtleties of muscular engagement, for whole-body squads of muscles that elongate in concert, mixing stretching and strength, for a genuine, effortless smile as she floats up past gravity. I challenge anyone to find a more perfectly functioning human. You can see with your own eyes that pole works.

Meanwhile, here below, follow the specific biophysical benefits, arranged as previous my articles in a list. Each point is distinct — and distinct from what other sports offer. Each of them could be a whole essay on its own. The fact there are so many accounts for why pole is a near-perfect physical activity for improving human function. Of those many perfect points, only a few offer room for improvement.

If you’re impatient with detail, the gist is this: The full human neuromechanical hardware/software stack, starting with 500-million-year-old sea-snake spines to hominids climbing trees with friends, faces its fullest challenge doing pole. No other sport comes close to touching as many aspects and angles of our bodies and nervous systems in good ways. Athletes and intellectuals know that a challenge — like discomfort and even pain — is part of what a body needs to thrive. As a general principle, all healthy, challenging full-body activities improve range of motion, strength, confidence, physical sensitivity (“interoception”), physical balance and emotional balance. All come directly from physical recalibration.

What follows is my scientific list of specific benefits. If you find this perspective persuasive, by all means, check out the much larger biomechanical and computational tapestry of which it is an inextricable part. Science and technology indeed have a simple, actionable description of what humans are and what is good for us.

1. Spines Can and Should Wiggle

The function of vertebrate spines, since snakes evolved in the sea, is to wiggle with wavelike undulations. That neuromechanical hardware was in place before fins, before legs, before arms. The best pole dancers can wiggle the tailbone (“twerking”), wave the head, flip long manes of hair and even do body waves aloft. The biomechanical objective, like the expressive one, is to use the spine and breathing to drive the limbs, and not the other way around.

2. Twisting Beats Pushing and Pulling

When spines evolved 500 million years ago, in sea snakes, their highest-leverage motions were twists, not bends. That is still true of all spines. Twisting the spine intensely is very good for us. But we humans spend more time exercising our arms and legs, mostly because it’s easier to apply force with them. Weight machines in gyms that twist the body, for example, are rare and hard to use compared to things you push and grab.

Poles change that. Many pole poses (like “ballerina”) actually support your body weight by twisting your spine around the pole, forcing the spine to exert a full-body twist and feel the results on itself. That’s like a weight machine for snakes.

3. Spinal Traction and Hanging Makes Us Feel Good

Since our ancestors once climbed trees, our spines enjoy being tugged straight, and they benefit from it — like “cracking the back.” Chiropractors get paid for doing that, but poles do it for free whenever you hang. Furthermore, if you are hanging inverted, head-down suspended by the squeeze of your thighs, your spine is both exerting and tugging in ways no chiropractor could ever manage.

4. We Need Play and Reciprocal Purpose

Our species evolved to spend all day, every day, clambering around with our fellows like chimps, trying things out and sharing advice. A pole dance studio during open-practice hours is like that, like a playground. Learning new tricks, practicing routines, stretching while you watch everyone else, offering suggestions and congratulations. And, of course, dancing for and with each other for fun.

5. We Need to be Seen

For the first million years, before inventing shelters and clothes, our primate ancestors saw and touched each other’s bodies at close range all day. That constant carrier wave of visual and mechanical interaction underlay the collaborative instincts that kept those tiny kin groups alive against steep odds. Ancient and modern people alike thrive on seeing other people, the more of them the better. Perhaps the only exposure better than sitting front row in a pole showcase or competition, watching every shape and age of body show off its self-rediscovery close up in skimpy clothes under bright lights, is to be one of many strong bodies doing that same thing together, being seen and seeing simultaneously.

6. We Can and Should Climb “Trees”

Before our ancestors walked upright, but after they stopped walking on all four legs, they climbed trees. If you watch a monkey or ape swing branch to branch, you see the creature’s body weight suspended where the inner shoulder blade attaches to the spine, so the animal can swing efficiently with little effort or fatigue. The best pole dancers have nearly that same ability: holding on with just one arm, they can swing around the pole for many revolutions, the spine centrifugally straightened like a tetherball on a rope.

Dance poles themselves are like idealized tree limbs in three ways. First, their width (typically 45mm) is exactly the right size for most human hands to get the best grip.  Second, that width is exactly uniform along the entire length, so one can grasp the pole above and below, even without seeing it, confident of where it will be and how it will feel. No natural branch is like that. Finally, the pole is made not just of strong metal, but of a specific metal (brass, chrome or stainless steel) and a special polish (mirror grade) known to maximize traction of skin on metal, so you don’t slip off.

7. Yoga Cubed

However wonderful yoga is (I just became an instructor), it is limited to the surface of a mat. Pole has everything that yoga does. In fact, pole uses yoga poses in warm-ups and routines. Pole also has a vastly wider floor area to play with and more things — like cartwheels — to do on it. Best of all, the pole itself literally brings in a whole new dimension: the third dimension above the plane, the “Z-axis” skewering the X and Y of a flat mat. Even keeping your feet on the floor, having a pole at hand (so to speak) adds a brand-new dimension to yoga and stretching poses because you can lean on it, pull against it, hook an elbow or knee, etc. And, of course, climbing the pole and wrapping around it offers an entirely new physical geometry for recalibrating the body. If nothing else, a pole is the perfect “yoga prop.”

8. Weird Positions and Torques Comprise “Motor Entropy”

“Entropy” is the official term for the information carried by diverse combinations of pretty much anything. So, the “motor entropy” of an activity describes all the different arrangements of hands, elbows, knees, neck, twisting, torquing, pushing, pulling, splitting, suspending and spinning that a body can do. No other sport can push and pretzel a body in so many different ways, which means no other sport can provide a greater variety of the training data a healthy body needs. Learning to deal with diversity in all its forms is what learning is for. Learning helps us conquer uncertainty and fear.

9. Fear of Death Motivates

Imagine hanging upside down meters above a hard-wood floor, suspended only by your burning inner thighs squeezing the metal pole for dear life. Imagine how the visceral fear of imminent death motivates a very strong grip, in spite of the pain. Over years, I’ve never seen anyone fall.

10.  Parasympathetic Expression and Flow

Of course, any pole activity can be treated as just an exercise, and not a dance expression. But in its highest calling, the spine expresses itself directly, as our ancestors have danced around fires for a million years. Then, the body is not following remembered instructions using the sympathetic nervous system (evolved for sudden problems), but in a state of spontaneous flow, employing the parasympathetic system evolved for continuous, real-time use. Dance is most beneficial to the dancer when the motions and emotions are spontaneous.

11. “Grounding” Way into the Ultrasonic

It’s well-known that one can calm the nervous system by breathing and meditation exercises. It’s less well-known that pressing parts of the body (especially its sore bony spots) against heavy stone or metal can accomplish the same thing. The principle is simple: The dense, uniform object provides a low-vibration “reference signal” to help the brain know what zero vibration is supposed to feel like. That gives the brain a tangible target when reducing body tremors, so it can calm the nervous system. The harder and heavier the object, and the less squishy stuff between it and bone, the higher into the high-bandwidth, ultrasonic zone the calibration can go — and the better it works.

Just touching something as unyielding as a solid metal pole helps recalibrate and realign. It can be a meditative practice to press the forehead, sternum, tailbone or entire backbone against the metal and wait for the body to adapt to it.

12. Only a Well-Tuned Hand Can Hold a Spinning Thing

I have always been amazed that the skill of swinging around the pole by one hand (which took me eight years to learn, in spite of so-called “strong” hands) can often be done by teens and even many adults on their very first try. That’s because that particular unnatural ability — to strongly squeeze a smooth cylinder while it spins — is the opposite of ordinary hand strength in several ways.

First is the angle of the hand, which when spinning around the pole wraps more like a spiral frond than a clamp, and squeezes together the sides of the thumb and index finger (“lobster claw”) instead of regular grasping. Then there is the moving surface contacting skin, which prevents the nervous system from its usual trick of locking in its ultrasonic tactile sensors to the surface micro-texture. That difficulty makes it much harder to feel just how the hand is engaged. Hard but not impossible, obviously. A sufficiently youthful, graceful, uncrusty nervous system, such as that of a teen or a dancer, still has its native tactile bandwidth and range, and thus its native ability to swing like a monkey or even better.

13. Spinning Makes You Pay Attention Differently

The spinning challenge above happens when the pole stays still and the dancer spins. There is another way to spin. Few non-polers know that dance poles can also be set to spin in their mounts with ball-bearing smoothness (and with near invisibility, since a shiny spinning pole still looks still).

As soon as one is spinning with the pole, you have to focus on it while letting the room spin around you. As with playground and amusement park rides, spinning constantly for a couple of minutes can make you feel dizzy (some pole studios offer ginger candies to alleviate nausea). But by the same token, spinning is also exhilarating (as children prove daily) and a potent form of fresh, unusual sensorimotor data, as with the rest of pole.  

14. Warped Gravity Challenges Interoception

Spinning pole is weird, but even weirder is that it twists gravity. As with spinning ballerinas, the farther from the axis of spin, the more outward force. That extra sideways force makes it easier to hold on, but it also means the felt “force of gravity” bends inside your body by about 30 degrees. That warped gravitational field is hard to notice if arms and legs are both touching the pole. However, if as one spins, the legs and torso swing free, then trying to move or shake them feels weird and confusing — but weird and confusing in exactly the way that challenges and awakens one’s nervous system. Feeling comfortable on a spinning pole is the mark of a master and usually also of a graceful, symmetric and physically-aligned body.

15.  Self-Awareness Moves From Physical to Spiritual

In the language of the nervous system, “sense of self” translates to interoception, or internal self-awareness in the most general sense, from the prick of a pin or pop of a knuckle up to the kind of soul-quenching transcendence sometimes induced by spine– and breathing-intensive activities. Many of the most fluid dancers report ecstatic states, such as time not merely stopping but ceasing as even a concept. The frequency with which such experiences occur (I enjoy them frequently myself) not only means that people can better appreciate the benefits of pole, but also that science finally has a playground/laboratory where physical mechanics intersects with spirituality and where human physical perfection can be understood and trained.

16. Female Energy

The documentary didn’t make the above points because it didn’t make points — it told stories. In particular, it told the stories of women whose victimization by men — by a girls’ athletic coach, by male porn consumers and by a man who thought pole was a sinful activity for his wife — was remedied by the practice of pole dance itself.

Healing sex-related abuse by males works best with men removed, for obvious reasons. So, of course, I’m never in such studios myself, but I have met many amazing women who have, so I’m certain there’s female magic involved. As a biologist, I’ll call it resonant social vibrations.

17. Pelvic Pleasure

Practicing pole works the pelvis, the most mistreated zone in modern bodies, in two ways. One is mechanical and the other is sensual.

Mechanically, pole stretches and opens the hips like ballet or yoga, but even more so, involving not just stretching but strength and unusual angles. Often, a pole pose supports the entire body through one or two hip joints, sometimes upside down or sideways.

But what makes husbands disown charming, graceful wives over pole is that pole started in strip clubs, and tricks named after professional strippers are taught in studios everywhere. Moreover, much of the personal transformation work involves not just athleticism, but also owning one’s sensuality and sexuality, in particular by enjoying sexy sensations while dancing.

I know of nowhere else in modern society that people are invited to feel sensual in a social group. Those are two of the most powerful primate affections.

For millions of evolutionary years, sensuality was central to social experience and bonding. So, that’s what our bodies evolved to expect and want. That quintessential primal urge is suppressed by civilization. But only buried, not yet removed… give us another few million years.

So, of course, pole’s social sensuality is psychologically potent. But by the same token, that deeply physiological vulnerability can trigger reactions, sometimes aimed at similarly vulnerable men who happen to be nearby. Here is a philosophical conundrum unique to pole, at the nexus of two unlikely nouns “body shame” and “dance belt.”

The sexiness-related asymmetry in pole between female and male (and more so heteronormative male) is both the sport’s pride and its flaw. Countless women have been helped by using pole to recover from things men did. But single-sex classes for men don’t work in the same way and coed classes rarely even try.

The one other problem with pole — at least in America — is a business model opposed to pole’s deepest social benefits. The business model is teaching classes. So, a would-be dancer must enroll as a student, go to a scheduled class, pay a lot of money and spend an hour or more taking instructions and trying to learn new things.

But primates like us didn’t evolve to take lessons. We evolved to freely dance and play (see points 4, 5, 15 and 16 above), and that’s what drives us to pole in the first place. Many pole dancers love to dance freely in groups, but that option is seldom offered because it doesn’t make as much money as classes. Money, and the market differentiation it imposes, force studios and instructors to compete. And money separates students from instructors and from each other. Our species has danced 10 times longer than we’ve talked. What if people just want to dance? 

From my perspective, pole is factually and scientifically a near-perfect way for people to upgrade not just their whole bodies, but their nervous systems and even spiritual lives. Furthermore, that fact provides yet more evidence for a mathematical, neuromechanical perspective on human function that has many other successes already. The sport is magnificent, the documentary “Strip Down, Rise Up” is magnificent and the science explaining why it’s magnificent is magnificent. Together, the message is simple: Humans really need climbing and physical fun.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post 17 Physics Reasons Pole Dancing Benefits Humans appeared first on Fair Observer.

Can We Build Social Trust in an Online World?

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I applaud and validate President Biden’s distillation of the problem of finding and keeping the truth, and of trusting it together. Human trust is based on high-speed neuromechanical interaction between living creatures. Other kinds of trust not based on that are fake to some degree. Lies created for money and power damage trust most of all.

A Moment of Silence

As Biden showed in his first act in office, the first step toward rebuilding is a moment of silence. Avoiding words, slowing down, taking time, breathing, acknowledging common grievances and recognizing a common purpose are not just human needs, but necessary algorithmic steps as well. Those are essential to setting up our common strategy and gathering the starting data that we need to make things right.

The next step, as Biden also said, is to recognize corrupting forces such as money and power — and I would also add recognition. The third step, as I propose below, is to counter those three forces explicitly in our quest for public truth, to do the exact opposite of what money, power and careerism do, and to counter and reverse every information-processing step at which money, power and recognition might get a hold.

Instead of using one panel of famous, well-funded experts deliberating a few hours in public, employ a dozen groups of anonymous lone geniuses, each group working separately in secret for months on the same common question. Have them release their reports simultaneously in multiple media. That way, the unplanned overlap shows most of what matters and a path to resolving the rest — an idea so crazy it just might work.

Since I’m describing how to restore democracy algorithmically, I might as well provide an example of legislation in the algorithmic language too. To convey data-processing ideas clearly, and thereby to avoid wasting time and money building a system that won’t work, technologists display our proposals using oversimplified examples that software architects like myself call “reference implementations” and which narrative architects like my partner call “tutor texts.”

These examples are not meant to actually work, but to unambiguously show off crucial principles. In the spirit of reference implementations, I present the following legislative proposal, written to get to the truth about one particular subject but easily rewritten to find the truth about other subjects such as global warming or fake news: The Defend the Growing Human Nervous System With Information Sciences Act.

The Defend Act

Over centuries, humankind has defended its children against physical extremes, dangerous chemicals and infectious organisms by resolute, rational application of the laws of nature via technology and medical science. Now is the time to use those same tools to defend our children’s growing nervous systems against the informational damage that presently undermines their trust in themselves, their families and their communities. Therefore, we here apply information science in order to understand how man-made communication helps and hurts the humans whom God made.

The human race has discovered elemental universal laws governing processes from combustion to gravitation and from them created great and terrible technologies from fire and weapons to electricity grids and thermonuclear reactions. But no laws are more elemental than the laws of data and mathematics, and no technologies more universal and fast-growing than the mathematically-grounded technologies of information capture, processing and dissemination. Information science is changing the world we live in and, therefore, changing us as living, breathing human beings. How?

The human race has dealt with challenges from its own technologies before. Slash-and-burn tactics eroded farmland; lead pipes poisoned water; city wells spread cholera; radioactivity caused cancer; refrigerants depleted ozone. And we have dealt with epidemics that propagated in weird and novel ways — both communicable diseases spread by touch, by body fluids, by insects, by behaviors, by drinking water, by food, and debilitating diseases of chemical imbalance, genetic dysregulation, immune collapse and misfolded proteins. Our science has both created and solved monumental problems.

But just as no technology is more powerful than the information sciences, when deployed against an immature, growing, still-learning human nervous system, no toxin is more insidious than extractive or exploitive artificial information.

The Defend the Growing Human Nervous System With Information Sciences Act aims to understand first and foremost the depth and texture of the threat to growing human nervous systems in order to communicate the problem to the public at large (not to solve the problem yet). This act’s approach is based on five premises about the newly-discovered sciences of information.

First of all, there is an urgent global mental-health crisis tightly correlated over decades with consuming unnatural sensory inputs (such as from TV screens) and interacting in unnatural ways (such as using wireless devices). These technologies seem to undermine trust in one’s own senses and in one’s connections to others, with the youngest brains bearing the greatest hurt.

Second, computer science understands information flowing in the real world. Numerical simulations faithfully replicate the laws of physics — of combustion, explosions, weather and gravitation — inside computers, thereby confirming we understand how nature works. Autonomous vehicles such as ocean gliders, autonomous drones, self-driving cars and walking robots, select and process signals from the outside to make trustworthy models, in order to move through the world. This neutral, technological understanding might illuminate the information flows that mature humans also use to do those same things and which growing humans use to learn how to do them.

Third, the science of epidemiology understands the information flows of medical research. Research has discovered and countered countless dangerous chemical and biological influences through concepts like clinical trials, randomization, viral spread, dose-response curves and false positive/negative risks. These potent yet neutral medical lenses might identify the most damaging aspects of artificial sensory interactions, in preparation for countering them in the same way they have already done for lead, tar, nicotine, sugar, endocrine disruptors and so on. The specific approach will extend the existing understanding of micro-toxins and micro-injuries to include the new micro-deceptions and micro-behavioral manipulations that undermine trust.

Fourth, the mathematics of management and communication understands the information flows of businesses. The economic spreadsheets and prediction models that presently micromanage business and market decisions worldwide can, when provided with these new metrics of human health and damage, calculate two new things. First, the most cost-effective ways to prevent and reduce damage. Second, such spreadsheets can quantify the degree to which well-accepted and legal practices of monetized influence — advertising, branding, lobbying, incentivizing, media campaigns and even threats — potentially make the information they touch untrustworthy and thereby undermine human trust.

America has risen to great challenges before. At its inception, even before Alexis De Tocqueville praised the American communitarian can-do spirit, this country gathered its most brilliant thinkers in a Constitutional Convention. In war, it gathered them to invent and create a monster weapon. In peace, it gathered them to land on the Moon. Over time, Americans have understood and made inroads against lead poisoning, ozone destruction, polluted water, smog, acid rain, nicotine and trans-fats. Now, we need to assemble our clearest thinkers to combat the deepest damage of all: the damage to how we talk and think.

Finally, we humans are spiritual and soulful beings. Our experiences and affections could never be captured in data or equations, whether of calorie consumption, body temperature, chemical balance or information flow. But just as we use such equations to defend our bodies against hunger, hypothermia or vitamin deficiency, we might also use them to defend against confusion, mistrust and loneliness, without in the process finding our own real lives replaced or eclipsed. In fact, if the human nervous system and soul are indeed damaged when mathematically-synthesized inputs replace real ones, then they will be freed from that unreality and that damage only when we understand which inputs help and hurt us most.

Informational Threat

The Defend Act tasks its teams to treat the human nervous system as an information-processing system with the same quantitative, scientific neutrality as medicine already treats us as heat-generating, oxygen-consuming, blood-pumping, self-cleaning systems. Specifically, teams are to examine human informational processing in the same computational terms used for self-driving vehicles that are also self-training and to examine our informational environments, whether man-made or God-made, in the same terms used for the “training data” consumed by such artificial foraging machines.

An informational threat such as the present one must be met in new ways. In particular, the current threat differs from historic ones by undermining communication itself, making unbiased discussion of the problem nearly impossible in public or in subsidized scientific discourse. Thus, the first concern of the Defend Act is to insulate the process of scientific discovery from the institutional, traditional and commercial pressures that might otherwise contaminate its answers. Thus, the act aims to maximize scientific reliability and minimize commercial, traditional and political interference as follows.

The investigation will proceed not by a single dream team of famous, respected and politically-vetted experts but by 10 separate teams of anonymous polymaths, living and working together in undisclosed locations, assembled from international scientists under international auspices; for example, the American Centers for Disease Control and Prevention will collaborate with the World Health Organization.

Each team will be tasked with producing its best version of the long-term scientific truth, that is of the same truth each other team ought to also obtain based on accepted universal principles. Teams pursuing actual scientific coherence thus ought to converge in their answers. Any team tempted to replace the law of nature with incentivized convenience would then find its results laughably out of step with the common, coherent consensus reported by the other teams.

Choosing individual team members for intellectual flexibility and independence, rather than for fame or institutional influence, will ensure they can grasp the scope of the problem, articulate it fearlessly and transmit in their results no latent bias toward their home colleagues, institution, technology or discipline.

Each team will contain at least two experts from each of the three information-science fields, each able to approximately understand the technical language of the others and thus collectively to understand all aspects of human informational functionality and dysfunctionality. To ensure the conclusions apply to humans everywhere, at least one-third of each team will consider themselves culturally non-American.

Each team will operate according to the best practices of deliberative decision-making, such as those used by “deliberative democracy”: live nearby, meet in person a few hours a day over months in a quiet place and enjoy access to whatever experts and sources of information they choose to use. Their budget (about $4 million per team) will be sufficient for each to produce its report in one year, through a variety of public-facing communications media: written reports, slide decks, video recordings, private meetings and public speeches. Between the multiple team members, multiple teams and multiple media, it will be difficult for entrenched powers to downplay inconvenient truths.

Released simultaneously, all public reports will cover four topics with a broad brush:

1. Summarizing the informational distractions and damage one would expect in advance, based only on the mathematical principles of autonomous navigation mentioned above, including not only sensory distractions but also the cognitive load of attending to interruptions and following rules, including rules intended to improve the situation.

2. Summarizing, as meta-studies, the general (and generally true) conclusions of scientifically reputable experimental studies and separately the general (and generally misleading) conclusions of incentivized studies.

3. Providing guideline formulae of damage and therapy, based on straightforward technical metrics of each specific information source such as timing delay, timing uncertainty, statistical pattern, information format, etc., with which to predict the nature, timescale, duration and severity of informational damage or recuperation from it.

4. Providing guidelines for dissemination, discussion and regulatory approaches most likely not to be undermined by pressures toward the status quo.

Within two years of passing this act, for under $100 million dollars, the world will understand far better the human stakes of artificial input, and the best means for making our children safe from it again.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Science of Rebuilding Trust appeared first on Fair Observer.

One of the few virtues of the “Wonder Woman 1984” film I saw recently is that it shows a woman flying up in the air like a bird or a plane, just like 50 years ago we saw Superman fly through the air. Last month, I saw dozens of real human beings fly many stories into the air, lifted aloft from their surfboards by airfoil-kites powered by wind. Amazing to see and, I imagine, amazing to experience. But the age-old dream of human flight is simpler: Can people fly in calm air, using their own power?

Like a Bird

The fact that birds fly shows that we might be able to, too. We’re just heavier, so it’s harder, which is in fact a very general rule. Insects can fly with wings even tinier than their tiny bodies, but big birds like albatrosses and condors need wings way bigger than their bodies. Fortunately, that relation is such a simple, universal concept — weight per unit area — that with a little physics, we can calculate how much harder it might be for people to fly than condors. Then maybe, with some clever materials and design, we might bridge the gap. We might redo the Icarus story, using carbon fiber instead of wax and feathers.

Let’s say a condor weighs roughly 15 kilograms and a human 60, making a nice round ratio of 1:4 in weight. The heavier-is-harder principle, called wing-loading, is based on body area. It says it will be twice as hard (square root of four) for us to fly, all else remaining equal.

So before getting to new stuff, let’s see what might actually remain equal. Condors and humans are both warm-blooded vertebrates, so it’s a good guess human muscles can generate as much average power-per-weight as condor muscles. And given the aerodynamic elegance that nature has evolved into soaring birds’ wings and feathers, it’s unlikely we humans could do much better than them for either lift or propulsion. So the shape of the next Icarus will have an aerodynamic efficiency at best as good as that of birds. What might be improved by a factor of two?

Birds are made of meat, bones and feathers. Not Kevlar (stronger than tendon), carbon fiber (stiffer than bone) or plastic like Mylar (smoother and lighter than feathers). And they can’t inflate themselves like a balloon to the size of an airplane. So let’s imagine using our fanciest modern materials to build an ultralight mechanical “bird.” The size of an airplane, smooth and tightly-inflated, containing an ultra-light lattice woven entirely and seamlessly from carbon fiber. This wing’s stiffness would mostly come from inflating the plastic.

That would leave the carbon-fiber lattice to accomplish four other goals: deforming in response to wind, to keep the wing from crinkling when bent; stiffening thin parts of the wing which pressurization can’t stiffen; “flapping” and “banking” the wings using human power; and carrying micro-vibrations from wing surfaces into the fingers and toes of the pilot, who would then “feel” the wings’ airflow much like birds do, using nerves in skin and bone.

Designing and building such an intricate, delicate airfoil would be expensive and unprofitable. Clearly, it would only hold its shape on calm days. But it could be built — and it would work. And when that mystical structure exists and is hooked up just right to a strong person pulling and pushing, it will fly like a bird, not a plane. That person will swim through the air.

Gossamer Albatross

We know something like that can work because a simpler, clunkier version was done decades ago, on a shoestring no less. In 1979, professional cyclist Bryan Allen piloted the flimsiest and best-designed airplane ever, the Gossamer Albatross, across the English Channel, to win the famous Kremer Prize, barely, on the first try.

He sat inside on a bike-frame, his legs pedaling the propeller. The whole plane weighed half as much as the pilot. It had been designed by aerodynamics genius Dr. Paul MacCready and a dozen crack engineers, one of whom (Stanford professor and venture capitalist Dr. Morton Grosser) wrote the book, “Gossamer Odyssey,” about the project. That plane was constructed like a regular plane, by stretching skin tight over flimsy compressible struts. A tiny breeze could snap it in half.

That single historic episode from four decades ago gives us a crucial data-point. It gives an example of a structure which, just barely, humans can fly for a while on their own. Presumably, every improvement on that structure would translate to less pilot effort. Twice the efficiency would mean half the pilot power, which would mean athletes of normal strength might fly it. Below, I propose four technical innovations that together could provide that improvement in efficiency, so humans might fly.

First, skip the propeller. Propellers spin, which is convenient for motors and drive-shafts. But spinning wastes energy because it moves a little air fast, rather than a lot of air slowly, much like flapping does.

Then, match the drive-train to the human. The drive-train on a bicycle, from foot through shoe through pedal through chain to wheel, is a wonderful way to power spinning wheels. But it isn’t designed to extract the most consistent, stable power from a human body, spread equally over all the muscles. Rowing machines do that better by using the back and arms, but even they still don’t take advantage of the original vertebrate power stroke — spinal twisting. Worse, when rowing, the rower has to clench the fists full-time to grab the oars. An optimum full-body power stroke would open and close the hands in concert with spinal extension and breath.

Let the human feel the airflow. Birds can take advantage of updrafts because they can feel the wind whispering on their feathers. If there were a sensitive vibrational conduit from wing skin to human skin (or fingernail), like thin carbon fibers, our nervous systems could learn to fly by feel.

Finally, gain tension from pressure, not compression. The Gossamer Condor, MacCready’s first attempt at man-powered aircraft that won him his first Kramer Prize in 1977, was built like an old-fashioned plane, with a thin film (plastic) stretched over spars and ribs, which could snap. The more of the film’s tension can be supported by pressurized gas rather than compressed shafts, the lighter and less breakable the structure will be.

I’m a physicist, not a fundraiser. I can’t make the project happen, but I know many innovators could. And I do know I might, just barely, be able to fly in my lifetime if I keep strong and healthy. But someone else will have to take the lead. Any takers?

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post What If Humans Really Could Fly? appeared first on Fair Observer.

How Do People Learn?

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All growing nervous systems learn to trust their senses by interacting. To calibrate our models of the world, humans need to sense it with ultra-precise timing, in the microsecond regime. Digitization and compression destroy those microseconds. High-quality training data from the real world needs to come first, fast and furious, long before the weird stuff. Like vitamins, minerals, and oxygen early in life: too little, too late, too bad.

Trust-building interaction between scientists is why science works when it does. But few readers take the time to contact authors like me, and when they do, few authors can respond. Of course we can’t: The nature of broadcast is to limit reciprocity, one-to-many. Unfortunately, limiting reciprocity limits trust. To correct my earlier article, and to bolster trust in science through a dollop of reciprocity, please let me address Paritosh’s quite legitimate points in the order he made them.

A Polemic Against Online Education

Paritosh’s first claim was that the article is a polemic against online education. This is true. A polemic is an attack, and my article did indeed attack online education. But “polemic against online education” describes the article too narrowly. The word “polemic” doesn’t distinguish between a baseless attack based on aggressive opinion versus a self-evident description based on undisputed principles. My article made its case based on 10 universal principles of plasticity, first discovered in the 1950s by experimental neuroscience and later confirmed by harder disciplines like physics and computer science. I used these principles to scientifically characterize how real-life interaction enables children to learn, while online education prevents acquiring real skills.

Furthermore, my article was far broader, scientifically characterizing all forms of artificial input to children’s nervous systems. Decades of neuroscience and machine learning have established that a brain only matures properly — during its critical period — when exposed to the kind of inputs it was designed to, or evolved to, process. For growing human brains that means continuous sensorimotor interaction with real life and real people. Artificial inputs, especially the mesmerizing sparkles of screens and digital algorithms, disrupt and damage learning pathways.

I helped write the neuroscience research which demonstrates mathematically that even the very best screen-based interaction is degraded thousandfold to millionfold, and the worst is outright toxic. I’ve done the numbers. They’re scary, but most scientists and doctors don’t know about them yet.

The long-term damage is to trust. All humans learn to trust our senses and each other based on the incredibly data-rich, ultra-precise signals contained in real-life sensory-motor interaction. If our training data is corrupted by digitization, we fail to learn. Children reared by screens or computers cannot learn to trust each other — or even to trust their own senses.

No Solution

Second, Paritosh argues that my article contained no solution. This is also true. It’s hard enough to explain 70 years of neuroscience and its mental-health implications in “only” 4,000 reader-friendly words. That is already several times longer than most Fair Observer articles. I doubt anyone wanted an even longer article.

But there is a solution to education during COVID-19, one suggested by my research-and-life partner Criscillia Benford: skip screens, go outside. Outdoor education worked during the tuberculosis pandemic a hundred years ago, even in cold climates, so it can work again now. America has a burgeoning movement to promote outdoor instruction.

Conducting Classes During COVID-19

Finally, Paritosh wanted to know how could classes be conducted during COVID-19 if face-to-face learning is perilous? Now is the first time parents must choose between their children’s formal education and mental health. Until now, classes took place in real life, so kids automatically received both authentic sensory input and instruction together, at once. It wasn’t either-or. Instruction didn’t require exposure to damaging technology, and kids’ nervous systems benefitted from the real-life classroom experience.

But now, education and real life seem to be separable. I say “seem” because screens and technology are only healthy for adults whose nervous systems have already matured. Adults, having already learned to read subtle inflections and micro-expressions from people in person, can then use those skills to fill in human nuance in the gaps between pixels and frames. Children, who still need to learn that skill from real things and people, could never acquire it by looking at blinking pixels instead. Cameras and microphones, computers and carriers, speakers and screens subsample, skip, clip, compress, scramble and delay too much bandwidth and subtlety to nourish a growing brain.

Informational damage matters to growing nervous systems, especially when it’s subconscious. Our most critical processing is all subconscious, precisely because it runs too fast to track. But subconscious means we don’t feel the damage until it is too late.

The intrinsically mis-calibrating effects of artificial inputs on growing brains mean so-called educational technology cannot possibly work for children. There is no evidence it works. And there is evidence it doesn’t work, evidence it damages kids’ brains, and lots and lots of math which says it could never work in the first place. A mis-calibrated nervous system is broken, and can’t learn much of anything. It needs real life, and nothing but, until real life is etched into its very synapses.

Picture the first day of class. Faintly familiar voices echo in the hallways, shoulders and backpacks bump, squeals of recognition. Seated squirming, shifty silences as names are called, whispers in the back row. Every sound and motion coming from a live person, every reflection and echo three-dimensional. Those children’s continuous, overlapping, cacophonous, multisensory experiences aren’t a distraction from their development, not merely a prerequisite for it — they are the meat of it, comprising gigabytes of sensory-motor reflections digested reciprocally in real time. Those nano-interactions are the atoms of neuromechanical trust, which is, in turn, the substrate of any lesser form of trust. And trust, in turn, is the substrate of education.

For centuries, learning meant nurturing young humans to live together and in society. Now it means passing standardized tests. Back then, learning meant training good habits and suppressing bad ones, supporting physical grace, mental clarity, moral fiber, social subtlety. Books and writing were optional, written tests unheard of. 

But as society scaled and learning morphed into education, optimizing the process required metrics and written tests. Standardizing education then required standardized tests, which, in the age of teach-to-the-test, become ever more meaningless, yet profitable, the longer they exist. In our current tragicomic situation, passing tests is so important that a handful of multiple choices can mark a child for life. Ironically, during a pandemic, we ask the child to forgo actual life in order to master online material. We behave as if test scores matter more than life itself.

The presence of COVID-19 changes the requirements of physical socializing, but not the requirements of growing nervous systems. In the classrooms of the future, will need more separation and airflow, but kids will still need to see and hear each other and their teachers with maximum sensory detail to learn the social instincts homo sapiens depends on. For supple social animals like us, physical and social interactions are not only more important than the “educated” skills of reading, writing, memorizing and calculating — they are required prerequisites. They have to come first for the others to work.  

So, in the future, children will learn social interaction bundled in blankets, in a tent or on a lawn in the sun as they have in many places for thousands of years. But they can’t learn social skills from screens, and making them try to is cruel. Lucky parents will send their kids to outdoor classes, not indoor isolation. But unlucky ones, faced with forcing their young ones to fixate for hours on a blinking piece of glass versus missing out on instruction and tests, must ask the hard question: Is my child a living, breathing being needing nurturing, or a receptacle for “content” that won’t stick?

For years, I have been talking with parents, teachers, scientists and readers like Paritosh about the dangers posed to human brains by attractive artificial inputs. For us to trust each other, we need authentic two-way interaction. But we also must agree on underlying principles. For me, I unapologetically choose uneducated but healthy children over educated but mentally miserable ones. To those who choose differently, I have nothing to say.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Can We Build Social Trust in an Online World? appeared first on Fair Observer.

For a decade. I researched with media theorist Dr. Criscillia Benford — my wife — the problem of how brains react to artificial inputs. Her explanation of how business incentives and psychological vulnerabilities interact in educational technology agrees entirely with the neuroscience news I have because they spring from our unified, quantified understanding.

Should Schools Rely on Ed Tech?

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This article is long and dense because it provides what anyone who cares about kids — parents, teachers, governors — needs to defend children’s budding brains against this summer’s looming threat. If these ideas make sense to you, a better understanding of it comes from a second reading — on paper in good light, with a pencil in hand. That’s the whole point: Brains work best hooked directly to the senses, with time to digest.

Decades of experiments have outlined several general principles governing learning, which together we neuroscientists call neuroplasticity, principles based on the presence, quality, duration and order of sensory inputs and sensory-motor interaction. Unfortunately, many of us are muzzled by obligations to colleagues, employers and investors. At the moment, I have no such obligations, so I am free to give you 10 widely-recognized principles of learning, along with what those principles say parents and educators must do, immediately, to protect our children and their descendants. But first, allow me to praise our human species. 

Human Species

We are the most elaborately, intimately social animal ever to roam the planet. Dog-eat-dog doesn’t hold for pack animals, like dogs, whose nervous systems perform synchronized hunting to survive. Humans dominate the synchronization Olympics. Our distant runners-up are bonobos, constantly cuddling and caressing in countless ways, collaborating, conspiring and cooperating through high-bandwidth neuromechanical interaction among all possible pairs. Their hands and bodies are built for touch, and their brains for processing it. Humans have all bonobos’ physio-social circuitry and then some: white eyeballs to show where we look, bare skin sensitive to bare hands, perfect balance for expressive dance, octaves of various vocalizations for singing, intricate facial expressions and eyebrows to amplify them. Forget words, tools and symbols. Homo sapiens excels at continuous connection.

Neuroscience studies animals because animal nervous systems are like human ones. That essential similarity is why we perform experiments in the first place. We already assume by default that what applies to cats and dogs applies to us. The principles of neuroplasticity below were discovered 50 years ago through grisly experiments on kittens. Since then, during the computer revolution, they have been rediscovered in various mathematical forms by physicists, signal-processing engineers, data scientists and machine learning specialists. When human brains acquire skills, we say they learn. When autonomous computer models like neural nets and self-driving cars acquire skills, we say they self-calibrate. But the underlying principles are the same. 

The successes and failures of both learning and self-calibration depend on data quality, speed and timing in straightforward ways, ones that ultimately originate in laws of information flow through space and time. The mathematical generality of those laws means that neuroplasticity concepts are universal, applying everywhere in the universe to all self-calibrating instruments, even artificial ones. If robots existed on other planets, these laws of neuroplasticity would explain how they learn too.

Below are 10 principles of learning, followed by guidelines on their use defending children everywhere.

1. Critical Periods Are Critical… Period!

Babies have to learn to walk before they learn to run, to communicate before they learn to read, to grab before they learn to write, and to hug before they learn to love. Learning takes time, and it must build on previous, simpler learning.

Each little chunk of the brain is hard-wired to learn from specific inputs. If those inputs don’t show up in time, during a critical period for acquiring that skill, the brain gives up on those inputs and makes do with other ones. That’s actually a good strategy. A baby born with a bad eye, for example, will learn by age 2 to use only the good one.

The strategy can backfire if an otherwise good eye isn’t aimed right, as with lazy eye or wall eye, in which case the brain learns to ignore a functional but misaimed eye. A typical treatment is to cover the good eye, a therapy forcing the brain to learn to use the weaker one. During critical periods, it is important not to deprive the brain of its native inputs, and especially important not to replace them with anything worse. As athletes and coaches know, it’s at least 10 times harder to un-learn a bad habit than to learn it right from scratch.

Critical periods contain and constrain the essence of neuroplasticity, by turning the often-vague term “developmentally appropriate” into very specific guidelines regarding the presence, quality, duration and order of sensory inputs and sensory-motor interaction. The shortest critical periods, say, for vision in kittens, take weeks. The longest ones, for emotional nuance in humans, take decades, well into young adulthood.

Learning after a critical period is not impossible. But the longer after the critical period a child goes without acquiring full function, the harder the child will have to work to improve, and the less improvement it will make.

2. Primary Processing Precedes Perception

The simplest, most granular processing is the processing closest to raw input, such as edge-detection among pixels in computer vision, or their human equivalent, orientation columns, in the primary visual cortex of mammals. The general strategy is to learn these low-level features first and fast, harvesting the most information from the tiniest pieces using the highest bandwidth. More abstract, broader, slower features build upon those, so of course, they are learned later and more slowly. Or not learned at all, if the low-level primary features weren’t learned right first. 

The fastest and most granular low-level computations, denoted in microseconds and micrometers, occur 100,000 times faster than conscious thought. We need that deeply unconscious raw data most, yet by its nature, it is easiest to damage and impossible to sense directly.

3. Sensory Fusion Is the Rule

The structure of brains is simple. Most brain regions and micro-regions (cortical columns) share the same five-layer structure and all nerve fibers transmit the same pulses. The sensory wires aren’t labeled by where they came from. Because a piece of the brain can’t tell which input came from where, sensory input from different sources is inevitably mixed together into a single, coherent, multi-sensory perception. If any sources or senses are missing, or mistimed, the integrated whole will suffer.

4. Learning Requires Constant Objects

Those of us with brains know they make sense of the world, and those of us who live in the world know it is filled with 3D objects. Babies learn about individual objects by moving their eyes and fingers (and maybe lips and tongue) across them as the object stays still. If the object itself moved too fast, the baby couldn’t learn about it at all. Still, once it’s out of range, the baby may forget.

After a year or so, babies learn that objects continue to exist even when not observed. This crucial discovery is called object constancy, a foundational stage of cognitive development. If for some reason a child never learns this fact — for example, if instead of looking at a live face, they looked at face-shaped pixels — they would never learn the difference between pixels and real life, and could never learn to trust their senses. Babies can’t yet tell the difference between broken-up representations such as images and continuous real-life objects right in front of them. Exposing babies to both, intermixed, impedes learning object-permanence.

The brain’s basic need for truly continuous targets means a baby couldn’t learn to perceive motion if it lived in a stroboscopic world. Or in the screen world, which flashes 10 times faster and is also flat and pixelated. Screen-based images are not objects. They are blinking dots, micro-timed to provoke object recognition in mature visual systems, yet utterly incapable of calibrating immature systems. Do check this reasoning with someone who programs self-driving cars. Please don’t experiment with your children.

5. Perception Comes From “Serve and Return” Timing

Trust in one’s senses comes from interaction, not transaction. (My wife and I wrote the singular peer-reviewed article about the physiological basis of trust.)

At the finest internal level, every mammal brain sends out pulses and gets pulses back. It uses the out-and-back pulse timing — with exactness down to microseconds, thanks to temperature-stabilized brains  —to make 3D pictures of a target region of space, whether containing muscles inside the body or surfaces outside it. A brain’s precision in spatial mapping is directly proportional to the timing precision of its pulses.

In psychology, this autonomous back-and-forth interaction, say a smile initiated by the baby and reflected by the mother, is called serve and return. In neuroscience, it’s called sensorimotor contingencies. In medicine, it’s called biorhythm synchronization. And in spatial imaging, it’s called time-domain ultrasonic tomography. All represent the same sensory algorithm but at different timescales.

6. Big Brains Need Play

Serve and return only works if the brain gets to choose when to serve. In other words, implementing a brain’s learning algorithm requires timing autonomy. The brain fiddles with its sensory-motor world in order to detect significant returns. The exact timings of its micro-actions, like private keys in cryptography, let the brain distinguish what it caused from what would have happened anyway. For immature mammals, this exploration looks like play. Play is children’s work. (Such work, including make-believe, is harmed by commercial coercion, as described in the book, “Consuming Kids.”

The better a brain becomes at predicting returns, the smaller and more frequently it serves.  Practice and success dial down amplitude into the deep subconscious of the microsecond realm. This virtuous cycle starts in the womb as the baby learns to anticipate the mother’s heartbeat, voice and body tremor, ultimately synchronizing its biorhythms with hers. Ideally, the two signals match, a sonic synchrony undergirding the mimicry humans do so well later in life.

In fact, the same continuous active synchronization underlies all animal society. Gnats swarm, fish school, birds flock, packs hunt, mates dance and humans cuddle, play, wrestle, cry, laugh and sing. The tiniest flickers will always synch first, but they’re damaged by digitization the worst.

7. Natural Appetites Need Natural Statistics

The principles above, which derive from the physics of matter and energy, tell us brains need continuous physical targets nearby to return them good sensory data. The principles below, regarding attention and motivation, derive instead from a brain’s hard-wired expectations of what will be common vs. rare as it grows up.

In particular, brains are hard-wired to seek rare things to make sure we get enough. Our native appetites for sugar, fat and nutrients are well-known, but our native appetites for certain informational patterns — saturated colors, shiny things, novel shapes, sudden changes, sharp contours and recognizability in general — also correspond to their rarity and usefulness in evolutionary times.  Those expected (and formerly rare) patterns are collectively part of the “natural statistics” of the environment the brain was born to explore. Our senses enjoy “interesting things” because they are rare in nature. But if saturated, a brain becomes desensitized and dependent, as if in thrall to a kind of addiction.

8. Dopamine Drives Decisions

Dopamine is the motivating neurochemical that makes us want to learn, by rewarding difficult predictions. But as theoretical biologist Thomas Hills proved in 2006, the principle of dopamine preexists the chemical. Even bacteria have circuits rewarding successful prediction as they move about, and dopamine descended from those. This computational purpose of dopamine is to focus resources and make decisions. By design, patterns of inputs that capture dopamine circuitry control the nervous system via its most basic motivations. If the controlling pattern comes from an organic animal or inert object, we say the nervous system is learning useful habits. If the pattern is artificial, we say the nervous system is being hacked. Utter defeat.

Dopamine can be elicited, or rather administered, by countless artificial stimuli from drugs to porn to gambling to video games to social media. But dopamine only works as designed when its owner moves autonomously in a natural environment.

9. Data Asymmetries Permit Parasitism

There was informational warfare long before humans — perception vs. deception. Colored plumage, colored flowers, lures, camouflage and bandwidth arms-races. Whichever creature has more, better, faster information always gets to manipulate or prey upon the others. We humans have always been the ones to conquer or domesticate other animals. Now, by the numbers, “edu-tainment tech” is domesticating us.

10. Covert Biometrics = Adversarial Biofeedback

The most beneficial bio-measuring technologies, such as cochlear implants, heart-rate monitors and stress biofeedback, provide the user with real-time, high-quality, unbiased data streams their nervous systems could not ever provide. Those signals boost the user’s self-knowledge and remain under the user’s control. The worst forms do the opposite, secretly monitoring heart rate, blood perfusion, pupil dilation, typing speed, emotional affect, the target of gaze, stress levels, etc., and then using those signals to replace natural ones or subtly alter the user’s experience. The signals are far worse than useless because they actively impede perceptual learning. Not only do corrupt return signals lower perceptual accuracy all by themselves, but their unpredictability also destabilizes the algorithm for learning object constancy. Exposure to such signals makes self-awareness, motivation and choice progressively impossible.

The principles listed above directly answer many important questions about what happens when young humans are exposed to artificial input, including and especially educational technology. Since the COVID-19 pandemic has throttled most human interaction down to screens, parents are rightly concerned. It’s worth stating these heartfelt human questions and their answers using the uncontested neuroscience principles outlined above.

While the principles have been known for decades, their implications for growing minds are only recent. Furthermore, most of us are embedded in cultures or situations where this unambiguous advice is impractical, much like medical advice to avoid chemical additives and preservatives can be impractical. I personally regret how I exposed my own kids to technology just a decade ago, before I knew better. And in my own life, I still can’t follow all the advice below.

So, the following advice does not judge any given parent or parental choice. Instead, it provides for decision-makers a clear, compact, unambiguous description, directly traceable to decades of scientific certainty, about which inputs are healthy vs. harmful to growing minds. No sugar-coating.

How Can I Know If My Kid Is OK? 

If your kid can remain happy and functional interacting socially with adults and/or peers for 24 contiguous hours each week, with everyone completely tech-free, they’re fine. Any dependence on tech, being driven by dopamine, will share the typical symptoms of dependence and addiction: malaise, tantrums, skulking, wheedling, compulsive use, impaired reasoning, lying.

Which Ages Are Safe for Screens and for Tech, in General? 

No child should be exposed to artificial stimuli before the skill is established organically and the critical period has long passed. Thus, even the most visually skilled child should avoid screen exposure until about age 4, and then only for picturing real things; should avoid cartoons and video games until they perceive the 3D mechanical nuance of real-life people and animals, say age 8; should avoid interacting with people by video until they master emotional face-reading, say age 12; and should not manage emotional relationships (like romance) remotely until they can in real life, say early 20s.

The learning of dexterity follows similar rules. A child should establish fine-motor coordination first, using paper and crafts, before learning to write, say earliest age 7; should write easily and well before learning to type with moving keys, say earliest age 10; should type well before using any touch-screen, say earliest age 13; and should not operate computers by automatic motion-capture or face-reading until adulthood, if at all.

The above rules assume the technology is optimized for human benefit (in terms of quantifiable results and not just good intentions — for example, by minimizing all artificial enhancements, even video edge-enhancement and cartoonification). But finding such ideal tech is rare. Absent that, the most general observations possible about kid-safe tech are, as before, based directly on the neuroscience principles (numbered in parentheses): Immature nervous systems will become miswired by technology that (3) separates image, sound and/or touch, which (4) generates artificial stimuli, which (5) superimposes timing variations on human outputs, which (6) undermines or coerces autonomous outputs, which (7) synthesizes unrealistic reward profiles (e.g., “gamification”), which (8) elicits dopamine responses, or which (9, 10) does not display all monitored biometrics directly to the child and preserve them for the child’s benefit alone.

Examples of “bad” educational technologies can easily be found by reading ads proclaiming how they elicit dopamine or make assessments using biometric signals. An example of a “neurosafe” technology could be a video/audio recording or teleconference platform with stereo sound and high-definition video, each separately registered to reality, and to each other, at microsecond resolution. Neurosafe technology preserves and protects maximal human bandwidth in native human format, not in formats convenient for monitoring, manipulating, or monetizing.

What Is the Best Thing I Could Do for My Kids Right Now?

Get your whole family away from all technology for at least 24 continuous hours a week, then try to expand. Reminding yourselves collectively what real life feels like is the first step in reclaiming it. The adults, being grownups, have to go first — primarily because kids imitate and second because only we adults have both ability and willpower. With your family, try any kind of fun active play. That is, any attractive, symmetrical neuromechanical interaction, such as back-and-forth, billiards, badminton, baseball or banter. Those provide more benefit than games, which move symbols on boards according to rules. Which, in turn, are still better than tech. Inventing brand-new forms of voice-based fun — say, laughing games — is best of all.

Triple-bonus points for a massage, especially a scalp massage, which can even be done in quarantine. Kids can learn to massage as sensitively as adults, and competence in giving pleasure is the best skill a human could ever learn. In particular, fingernails pressed gently into or dragged along the midline — brow, crown, occiput, sternum, lower back — help wake up the most emotionally central myofascial pathways on a human body. Supportive touch both relaxes and feels wonderful.

Never give kids tech to keep them busy. Their nervous systems need your live attention, and nothing else will do. Read to them, play with them, talk to them, do chores together.

What Kind of Education Is Best for My Child? 

Small-scale (mesoscale) learning, like homeschooling by attentive tutors, gives groups of children a good social experience. Small-scale learning can also be educationally optimal, but only if it maximizes each child’s ability to confront, appreciate and autonomously interact with the real diversity of the physical world and the people in it. (As opposed to the opposite motivation, protecting children from dangerous people and ideas.) Unfortunately, the modern caricature of “traditional values” mocks the constraints imposed by honor, family, integrity and respect, providing nothing in return. That view forgets those attitudes that are essential for human social function. Societies don’t last long without them.

A handful of internet sites keep honor and integrity alive by avoiding the corrosive influence of ads and corporate sponsorship. Otherwise, the old innocent internet is dead, replaced by bots, incentivized propaganda and surveillance. In such a corrupt environment, nothing worth asking can be honestly asked, nor honestly answered. Fake-ness reigns.

Yet real life still exists and feels wonderful. The more you and others like me rediscover real life, the more time you will spend there. Therefore, the less of your life you will spend online, or recording it for online consumption. Collectively, that out-migration will leave the internet as before, filled mostly with bots and humans posting criticisms to provoke yet more online discussions. Sadly, technophiliacs and neuroscientists alike share an allergy to simple, unambiguous conclusions, regardless of the obvious truth. Like the internet, both those groups cheer discussion for its own sake in an endless loop.

What Can Schools Do? 

Proponents of education technology love open discussion, but only as long as their technology is presumed safe by default. Now, neuroscience has turned the tables. The medical burden of proof lies in meticulously proving how tech could be safe in the first place. That will prove difficult because all reasonable evidence-based investigations, so far, agree with fundamental neuroscience, fundamental data science and plain parental common sense in concluding that technological interference with organic brain development is dangerous at best, toxic at worst. 

Meanwhile, schools and their vendors are suddenly commencing a bold new experiment on children’s brains en masse, one with irreversible results. Since proponents brag that tech affects minds, then technology must be evaluated like a drug. In America, drugs must be proved both safe and effective before being dispensed. Let proponents prove their case according to medical safety standards, not bureaucratic line-item calculations. If ed tech were a drug, they can show why it should not be banned.

School and the Pandemic

Now let me warn our species. This summer, an unholy alliance of risk-averse, spreadsheet-bound bureaucrats and risk-loving, pixel-pushing disaster capitalists is poised to take our schools, and thus our children’s brains, by storm. It doesn’t matter if the evil is in the people or in the spreadsheets they obey, the result would be catastrophic for homo sapiens. 

Never in human history has an entire generation of innocent young humans, rich and poor alike, had the nipple of loving neuromechanical connection yanked from their mouths, to be replaced by a dripping pap of pixels laced with dopamine, administered under glass.

Never before have games been gamified and children’s play been played, for profit. Never before have the unfurling neurons of babies been clear-cut for short-term revenue and long-term prediction. Never before have all our young ones been experimented on with profitable mind-altering drugs and profitable mind-altering technology, at once. Not even once before in history has any single parent, much less an entire generation, looked into screens instead of into children’s eyes, then watched in horror as the children imitate that disconnection for the rest of their lives.

The disaster is more potent than attractive technology undermining attraction, more chilling than cold spreadsheets overruling warm, live hearts. It is the worst possible calamity to strike the most elaborately, intimately social animal ever to walk the planet, we humans who love continuous connection. It is an infection of communications itself, an infection whose violent, virulent, viral spread is fueled by data, dough and dopamine.

Left unchecked, this infection of disconnection will fill the world with psychic orphans (like the abandoned Romanian babies), impervious to love and unaware that it exists. Such cold souls could not nurture a lost generation. Please prove me wrong.

*[An audio version of this article can be found on the author’s website.]

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Monetizing Children’s Brains Means the End of Our Species appeared first on Fair Observer.

Presumably, that same obviousness applies to love vs. hate, both as principles and as messages. Hate seems to be rising everywhere, much of it transmitted through profit-making media. Could speed and money be part of that rise?

Is This Column a Coherent Perspective?

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First, let’s take speed. Love grows slowly over countless micro-interactions, so it takes days and years of physical proximity for real love to evolve and grow — deeply-connected love, the kind rooted in the continuous-time nervous system, the parasympathetic (“rest/digest”) nervous system. That reciprocity could not possibly accumulate through a one-way medium, whether broadcast or narrowcast.

Fear, on the other hand, can travel quickly. (See here for an example of a gazelle’s white tail flashing alarm to the herd.) Alarms, like fear, travel just fine through one-way media because they are one-way messages aimed at the exception-handling nervous system — the sympathetic system (“fight/flight/freeze”). And they travel fast.

Now, take money and why love makes less of it. Love is subtle and becomes more so over time. After a while, love isn’t “news” or even still exciting. What mostly grabs attention and money are (again) surprise and alarm, which tilt toward fear, anger and hate. Alarming and divisive messages, being sudden, trigger the sympathetic system and with it our attention, engagement and resources.

Of course, we pay attention to sudden bad news and become anxious or fearful because that’s how the system evolved. But it evolved in the natural world where the only news came from fellow creatures nearby.  Our paleo ancestors didn’t have the internet.

“User Engagement”

Today, such paying attention is called “user engagement,” and that’s how firms such as Facebook make money. User engagement pays the bills. So, it’s no surprise that Facebook and similar tech companies try their best to make us pay attention, mostly by selecting and rearranging what we see to make us more interested. The algorithms which do that — which optimize user-engagement metrics and thereby boost profitable messages — also boost divisive messages.

In fact, as you might expect, they also boost actual divisiveness among the people who see those messages, which in large enough numbers have boosted actual attacks and killings in parts of the world. In an article for The Wall Street Journal, Jeff Horwitz and Deepa Seetharaman documented that Facebook has known for years that user-engagement revenue was blood money but kept chasing it anyway.

Unfortunately, what’s good for Facebook revenue is bad for human beings. Our alarm-detecting sympathetic nervous systems evolved to be used sparingly on rare occasions, not all day, every day. Humans evolved to play, cuddle and forage without interruptions, rules or deadlines. We evolved for a world with familiar people nearby and without news from afar. And without video recordings. Innocent paleo humans weren’t meant to know all the horrible events anywhere in the world all at once. And we certainly weren’t meant to see them in graphic detail.

In sum, hate in America is growing so fast because modern communications and monetization systems — in combination — are exploiting and saturating the alarm-producing parts of our nervous systems and starving the love-producing parts. This endgame is the engine of capitalism vs. human sensitivity.

If our brains evolved to mostly love but technology transmits mostly hate, which will win in the long run? Meanwhile, what will happen to the budding nervous systems of babies and children who grow up never knowing peace of mind?

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Hate Makes More Money Than Love… and Moves Faster appeared first on Fair Observer.

My own lofty, earnest hope is that the 20 articles I have written for Fair Observer so far (most under the column dubbed Tech Turncoat Truths or TTT), when assembled in that fashion, should provide my fellow human creatures with obvious, intuitive principles protecting ourselves. Not protecting money or power. 

Why I Created This Column

In writing this column, I have hewn as close to the scientific ideals of non-bias, simplicity, clarity and coherence as I can. That’s easier than it seems because their unifying reference frame is neuromechanical trust — the trust humans have in our senses and ourselves. I am co-author of perhaps the only peer-reviewed quantitative framework explaining how humans (and even machines) form trust, the 60-page Sensory Metrics of Neuromechanical Trust. An additional, equivalent set of principles can be found in the “Warrants” section of the paper, 9.5 Hypotheses on the Informational Structure of Life. Both sets of principles comprise one of very few “grand unified theories” claiming to explain life, nervous systems, communication and economics. Of those grand theories, it is probably the only one explained directly to the public by an original author, no middlemen. I would be delighted to hear of any others.

That theory, in turn, itself originated in the capstone of my neuroscience career — a research paper describing the physical structure of an “ideal brain.” In physics, the word “ideal” means not “best” but “idealization,” like an ideal gas made of simple particles. The function of an ideal brain, by the way, is defined as its hardest computational task. In brains, that task turns out to be simulating accurate, moving 3-D images of body and world using vastly insufficient sensory data. For such a near-impossible computation, the only plausible brain hardware would involve a nanoscopic medium I call simulatrix, which would compute with wavefronts. Experiments have not discovered simulatrix, but neither have they looked for it.

In all this work, my equal partner has been narratologist Criscillia Benford, whose mathematical understanding of commercial media in general (and multiplot novels like “Bleak House” in particular) is as broad as the ideal brain project. Fortunately, our two frameworks agree. We separately pursued those for a decade, before collaborating for another decade without ideological agenda or institutional funding. Our two approaches overlap so well because her understanding of human symbolic communication, my understanding of the brain and our mutual understanding of neuromechanical trust can all be grounded, in common, in the mathematical “information sciences.”

Two DIY Sanity Checks for Scientific Coherence

Transparency, objectivity and coherence are hard to get right in any perspective. But if you do get them right, it becomes all the harder for others to tamper with your ideas after the fact. So in evaluating a potentially coherent perspective, clarity and transparency ought to be the first things a reader looks for, even before checking facts or consistency.

First, if a scientific perspective isn’t clear and transparent, you can’t even check if it makes sense, much less use it even if it is. So as a first step, read a few TTT articles, besides these this one and its twin. Do they make sense to you? If not, save yourself the trouble of reading further.

Second, do they at least look like they might be intellectually coherent, as if they really did draw on the same few simple source ideas? To do that test, ultimately you’d have to read each article, list ideas in them and compare pairs of ideas across the articles. That takes way more time and thought, so save it for later.

As an easier first step, one can at least look at what disciplinary subjects each article covers. If the pool of source ideas is, in fact, small and deep, different disciplines should be equally represented and equally interconnected. I believe that is the case, so below I’ve taken the first step to make it even easier.

TTT Articles Span Idea-Space

These articles are all grounded in the laws of information flow, which connect scientific disciplines as diverse as neuroscience, computer science and economics. In the table below, each article is labeled by the quantitative scientific disciplines it invokes. Each article is inter-disciplinary but in different ways.

For each of the preceding 18 articles, I have checked the major quantitative disciples it involves. Inspection shows that every discipline is connected to every other one at least once. This does not mean the articles are true, or even internally self-consistent. It merely does show that TTT’s subject matter is not biased toward any particular discipline, and it links disciplines roughly symmetrically. That means that if the ideas do prove self-consistent, they could at least be a candidate for a coherent perspective.

If they pass these first two steps with you, the next step for you is to decide how much you care about ideal scientific truth. The more you want to know about ideal science, the more you will want to behave and think like an ideal reader. But whether or not your reading is ideal, you’re still a perfect human being, just as you are. The truth is simple and true, but you don’t need to know it to live.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Is This Column a Coherent Perspective? appeared first on Fair Observer.

Away from fake and fast, at the upper end of science, the laws of nature are true and eternal. But weirdly, while discovering such laws counts among humanity’s most amazing accomplishments, they are too old and boring to be news. Science textbooks are expensive and obscure. Online hosting fails the laws of nature entirely, because grand laws arrive so rarely, command less interest and are hard to monetize with advertising.

Worse is a feedback loop wherein the more society considers the hallowed high ground of science as “true,” the more valuable science becomes as a tool of persuasion, and the more monetization tries to wrest control of it. So “scientific truth” becomes even more tempting to misrepresent. As a result, there are few or no places online to find clean true useful science, unsullied by marketers, lawyers and bureaucrats.

News as Data Points

In science terms, what we call pieces of news are in fact data points, one of two crucial components in making sense of information. The other component is predictive models. Every responsive, self-regulating system feeds on data points. Your brain, your computer and your society all have to ingest data points from a changing world in chunks in order to turn it into useful information.

What kinds of data points? Brains ingest neural pulses. Markets ingest stock-transaction “ticks.” Societies ingest news articles. But two effects limit how useful those points can be. First, because quickness matters, reporters (and editors and fact-checkers) often make mistakes on deadline, so news is noisy. Further, because a viral story can make so much money whether true or not, and because “fake news” is cheaper to make than trustworthy news, more and more of news is more and more fake.

For example, during the US election four years ago, a Macedonian teenager earned 10 times the local wages by creating clickbait stories for extremist news site with the sole purpose of going viral. Fake news is very cost-effective, because it costs nothing to gather — yet it gathers more clicks. As a result, in terms of information science, media bias is real, but not toward ideology, rather toward money and power.

The fact that news can go stale and be replenished makes it an evergreen moneymaker in online media, which thrive on high throughput, agility, change and detail. But readers seldom pay online, which forces online media to grab the money first byinserting ads and popups, extra pages to create extra clicks, groveling appeals to repost/follow/like and “sponsored” (incentivized) content, all just to pay the bills. They also surreptitiously sell your reading data so that other companies can manipulate you even better. The core problem is that incentives — all incentives — mathematically corrupt trust, in direct proportion to how well they work. Incentives change things in a particular direction, while truth doesn’t change and is neutral.

So as an information source, online “news” has two structural problems: its quick-and-dirty gathering process makes the result narrow and noisy, and monetization makes it biased. Such corrupt input needs a lot of cleaning up, say with a predictive model.

Science as News

Is news about science more trustworthy than news about events? Almost never, and for all the same reasons. Most science you find in news media is, like regular news, not truth with a capital T but selected data about specific recent events, experiments and conjectures, still noisy and biased toward monetization.

The vast majority of science, and the news about it, works as follows. Scientists work for organizations with budgets and agendas. Those organizations want their research to serve those agendas (hello, incentives!), making the experiments themselves biased, even before publication. Then comes scientific publication, in which tradition, along with anonymous and often biased peer reviewers, impose obfuscated jargon, irrelevant detail and muddled explanations, ending with the obligatory weasel-worded conclusion like “this experiment might mean something, so more research is necessary.”

Such research reports are scarcely comprehensible even to specialists, much less to lay people. Reporters deal with this by speaking to the scientist who did the experiment or by merely reading digests. This quick-and-dirty reporting happens because news is time-sensitive. The result is science news that has already been corrupted by cascading steps of translation and selection optimized to boost reputation, attention-capture and revenue before it ever reaches you, the reader. At present, science news provides interesting but shaky data points, but no way to make sense of them — just like regular news.

Ideal Science

At worst, politicians invoke the trappings of science as a mask, like the meaningless dials and numbers on a COVID-19 dashboard. At best, politicians respect that scientific laws (like viral spread) are real and adopt objective metrics and data-driven targets to support human welfare. The right scientific metrics resist political and commercial tinkering, because they are transparent and obvious. The best of those metrics are based on what I’m calling ideal science.

Ideal science isn’t its gummy practice, which mixes in guesswork, experiments, mentoring and grantsmanship. Ideal science is exactly the opposite of news: old, plain and obvious. It combines experiment with mathematical law, distilling the result into the most powerful of predictive models, the universal laws of nature, like the law of gravity. These laws are so universal you don’t need to worry about the difference between Chinese and European versions. They last forever. And they predict the future, as spacecraft navigation proves. Or black holes, which were finally confirmed to be real nearly 95 years after being mathematically predicted by Karl Schwartzschild.

Prediction also drives the scientific method: First make predictions from data and models, then update the models, get more data and try again. Continually confirming predictions is also the principle brains use to explore their worlds.

What makes universal laws so potently predictive is precisely that they avoid specific details about the world and instead relate details together. The best-known laws describe relations in the physical world, including the laws of gravity, electromagnetism, quantum mechanics, heat and relativity. Of laws describing life, evolution is the best known, and on the horizon are other informational laws describing self-regulation, brains and communication. The power of such laws comes from their simplicity, as captured by idealizations such as ideal gas, absolute zero, perfect vacuum and frictionless surface. These idealizations generally appear as simple equations that can leverage data from the past into predictions of the future, the way gravity’s F = GmM/r2 guides spacecraft.

The universal law of math dominating today’s news is epidemic spread. As the separate dots of COVID-19 caseload increase percentage-wise day by day, they stay close to the predicted rising whip-like exponential curve of epidemic spread. The dots give us the curve, and the curve gives us the future. So as an idealization of how data might predict the future, fitted curves — and fitted curves alone — allow precisely smooth predictions from a few uncertain chunks. At times like now, with so many economic and social parameters so far out of kilter for months simultaneously worldwide, idealized predictive models are the only way to plan ahead. We’ve never been here before, so we need a map.

The map we seek has one new “color” (i.e. kind of natural law) never included before: the laws of information flow through space and time. Those laws are already used everywhere in technology, under names like signal processing, data science, algorithmics and computer science. The human side of those same laws includes symbolic communication, the brain’s reconstruction of 3D reality and neuromechanical trust. The extended information sciences are as close to “eternal truth” as science can get, besides gravity. They inspired most modern technology; now they can help us humans, too.

The Hyperdimensional Jigsaw Texbook

The predictive models of ideal science are what we need, but they face corruption by monetization pressures. So they can’t appear as news about science. But they might appear as science about news, in an unorthodox new form disguised as news. The base material for this new information structure would be freestanding “news” articles, each keyed to the hook of a recent event but collectively outlining universal principles, nay laws, which both precede and outlast the event itself. As if one used news about an extra-high tide to illustrate gravity in general.

Those articles together could form a tightly connected, intellectually interlocking network of mutually-supporting scientific claims, a textbook built of pieces like a jigsaw puzzle. Any motivated readers, putting them together, might solve the puzzle of the truth they seek. On the other hand, if those same readers agreed there were major contradictions, they would thereby know the whole was bunk. Even more than agreeing with experimental evidence, coherence and self-consistency among ideas mark them as coherent candidates to match reality.

If such a virtual “textbook” explained only one subject, such as economics, it would refract truth only along that axis, with few ways of cross-checking built in. By cross-linking those ideas to a different discipline, such as mathematics, cross-checking is much easier, so there is an extra axis to establish trust. By showing links between a half-dozen different quantitative disciplines — say economics, mathematics, physics, neuroscience, biology, computer science — the result (in mathematical terms) is a six-dimensional hyper-crystal, an informational structure far more solid and stable than mere three-dimensional diamond. So we can call our novel ideal-science-in-news structure a “hyperdimensional jigsaw textbook.”

Who might be the ideal creators of such a jigsaw textbook? While the voice of an author is easier to understand and more coherent, the research itself should come from multiple individuals, if only for extra pairs of error-catching eyes. Ideally those authors would ground their claims in root principles, scientifically expressed, ideally from their own synthetic works. Ideally, these authors would be intellectually independent, uninfluenced by funding or agenda. Their results should be consistent with information science and obvious in hindsight. That’s the ideal. That ideal supports human welfare by providing transparent principles, objective metrics, data-driven targets and especially a conceptually coherent framework for evaluating them. Transparency, objectivity and coherence are hard to tamper with.

Ideal Reader

Most news readers, like most news reporters, are rushed, distracted and prone to avoid dense intellectual material. They have no interest in any textbook, much less an idealized hyperdimensional jigsaw textbook. Might anyone?

Let’s imagine an ideal reader for any ideal jigsaw textbook (not just mine). Truly ideal readers of Fair Observer, of course, would so enthusiastically support the mission of diverse, unbiased, high-quality reporting to subscribe with their own money. Of those readers, the most motivated (and least busy), understanding the problems of reading on screens, would print each article out on paper because reading comprehension is severalfold better that way. They would read each printout slowly in good light and mark the paper up with questions and observations.

They would meet with other like-minded readers in person to discuss each article, enjoying the interactive bandwidth of common intention in a quiet place, and would cherish the collective “aha!” when some point resonates, or would roll their eyes when points go flat. They would make and share backup copies of whatever articles they cherish as both PDF and paper copies, so the knowledge could survive censorship, crisis or net outage. If they liked one article, they would read others since all derive from the same principles.

And most of all, they would look for conceptual contradictions, in groups to minimize their own contradictions. In any accumulating jigsaw textbook like this, as article after article comes out, each invoking similar mathematical principles across a wide range of subjects, it ought to be progressively harder to avoid bits of one article contradicting another. I claim and expect you will find no contradictions, because the truth is actually simple, and actually true. I hope you find it useful.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Ideal Science for an Ideal Reader appeared first on Fair Observer.

After a few minutes after getting used to that new sonic space, for a few seconds at a time, I felt a visceral sense of immediacy. High-quality livecast stereo creates an acoustic “tunnel” connecting the sound fingerprint of one breathing human being, say the priest, to the ears and possibly the soul of another. By ignoring the laptop screen and instead focusing my full attention on the audio sound image, my nervous system felt teleported into the presence of voices, incantation, songs, bells and cavernous echoes.

In my head I named the experience “spiritual communion,” but minutes later I discovered spiritual communion is an official Catholic term. So let’s just call my “being there” experience audio telepresence. In this case, a one-way telepresence experience listening to mass. Then, a few days later, two-way telepresence stereo phone calls. The good news is, audio telepresence is both cheaper and better than video telepresence. You can even try it at home.

Simulating Meetings

“Video telepresence” is a fancy name for simulating meetings by putting high-definition screens around a table. In Silicon Valley, a single such room costs about the same per hour as a novice attorney. Sitting among high-definition screens obviously provides more detail than a laptop ever could, so it looks far better to the eye. Better for your brain’s sense-making, the audio speaker for each attendee is placed with the screen, so the sound and image come from the same place.

But by the exacting standards of the nervous system, best measured in micrometers and microseconds, even the fanciest screens are abysmal approximations of live three-dimensional life. A 10-megapixel screen is still dozens-fold too flickering, flat, shiny, grainy, lagged and sonically scrambled to pass for real to your real brain.

No visually-based teleconference, not even the very best teleconference using augmented reality, can signal the real presence of a fellow nervous system. The pixelated prop might fool your conscious eye, but not your unconscious biorhythms. Those subtle signals can’t synchronize or “connect” as well with someone else through pixels as in real life. Screen-based attempts at connection only drive the deep sensory conflict deeper into the unconscious, as virtual reality also does, which makes people sick. New experiments back this up. Participants in a study of emotion-reading given sound, video or both proved to read emotions best using only sound, without video.

Many people older than 40 remember feeling deep audio connections through traditional copper telephones wires, whose analog acoustic properties play far better with our analog nervous systems than does anything digital. A typical teen or even adult could spend hours in a dark room, staring at the ceiling with a phone to the ear, trading secrets. Back then, jazz musicians “jammed” together over the phone. Those phones actually connected people on the nervous-system level, so they enjoyed telephone calls more, unlike people who grew up with mobile phones. That’s the kind of connection I want to revive via acoustic telepresence.

Escape from Quarantine

Acoustic telepresence connects you not just with a person but with a place. Through the magic of stereo, using two independent sound channels, your ears can hear the locations of sounds, left through right, near through far. So a stereo transmission of real sounds from a real place, such as an echoing cathedral, can sound to your ears and skin as if you’re in that place, right where the microphones are.

The key to success at acoustic teleportation, as with enjoyment of theater, is the willing suspension of disbelief. You have to want to feel you’re there, to will it. To get the nearly spiritual result of being out of body, you need to start with a nearly spiritual commitment to use the infamous placebo effect to your own full advantage. Believe it works, and it will.

By willfully feeling a different reality, you will also have exercised autonomy over your most important “muscle,” your attentional system itself. Deliberate attention-control during stress helps defuse it, as with the hugely successful eye movement desensitization and reprocessing therapy. In that sense, teleporting yourself through acoustic telepresence counts as an escape from quarantine.

The experience is even better used as a two-way telephone. If each of you has a stereo microphone (into the computer’s USB jack) and speakers or headphones (out of the headphone jack), you have the ingredients for a two-way stereo conversation (via any videoconferencing platform which supports stereo, such as Zoom — check your settings). The trick is that after saying pleasantries, you don’t use the video, only the audio. You close your eyes and try to feel the other person speaking right there in front you and let the other person know that’s your plan.

Meanwhile, they might look at you while speaking, just to see your nods of recognition and understanding. That listen-versus-view pairing works way better than both people watching the screen, I promise. Last Friday, after three consecutive hours of shared acoustic telepresence, I felt not fatigued as with Zoom, but energized. Just talking, eyes closed, is way more relaxing than preening at a screen.

Good Hardware

Acoustic telepresence requires both a good attitude and good hardware. I’ve fussed on this project for months, so here’s how I set up my rig. You probably won’t have all the pieces, but maybe enough to experiment yourself. First, stereo sound departs the laptop via a 3.5mm plug into the headphone jack and goes into a microtime-amplifier circuit (US patent 7,564,982), because sudden microtime differences, such as twig snaps, provide the best cues to sound location.

That cleaned-up audio signal then drives the aux input of a vintage stereo amplifier (non-digital, circa 1975), because digitization of any kind destroys microtime signals. The amplifier’s output enters copper wires, not microtime-destroying Bluetooth. Those wires drive two 1970’s walnut cabinet speakers, because speakers, unlike headphones, provide a coherent sound field for the entire body.

The tech specs of these particular speakers (frequency, linearity and phase) presumably mean they reproduce their inputs accurately. The speakers are placed close together, each aimed slightly inward to directly face the center of the sofa because the best microtime signals come along the speaker cone’s line of sight, where the sound wavefront is distorted the least. As a physicist, I believe this entire acoustic arrangement, whether driven by a laptop computer or by a vinyl LP record player, provides the best “phantom sound image” available. As a human, with my eyes closed, I believe it sounds real.

Besides hardware, here are a few neuromechanical tricks to help improve your experience. At first, by all means, watch the video to get a sense of the person and place before diving into acoustic immersion. Then, satisfied by the screen, close your eyes aim your attention at the source of sound itself. Try to hear the speaker as if in front of you, and the sounds as all around you. Try rebalancing your spine, such as by slightly lifting your chin or leaning forward, because your entire front body is sensitive to sound and works best when open and engaged. As you align, you may feel the sound image “pop” suddenly into presence.

Just months ago, people could connect instinctively, just by being there. Now, in lockdown with only online filaments, you have to try hard to feel connected to any person or event. But with good audio, it’s still possible and feels like an amazing accomplishment when it works. Now, more than ever, we need interpersonal connections and accomplishments to remind ourselves we’re human.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post A Better Way to Connect in Lockdown appeared first on Fair Observer.

Making the Best of Social Distancing

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Nature, on the other hand, hardwired breathing into the smooth, continuous parasympathetic nervous system (feed/breed, rest/digest), in order to be full-body and instinctive. After heartbeats, breathing is the second-most important muscular activity and the most mechanically complicated because it has to make the body bigger by making some muscles shorter — like an umbrella, sort of. Our bodies evolved for a lifetime of running and climbing, always using the smooth, fluid, baby’s breathing we were born with. Even today, people who use their whole bodies daily — workers, athletes, martial artists, dancers — keep their breathing muscles in good condition. They have better posture and fuller, more continuous breath.

But those of us who push pixels for a living can sit and hold our breath whenever we want and we don’t even notice. Once a brain mixes up breathing muscles with skeleton-control muscles, it learns the habit of either holding still when breathing or holding the breath when doing something important. This is an example of reasonable short-term motor learning leading to a bad, long-term outcome.

As with other muscles, our breathing range of motion gets smaller with age and disuse, as the sympathetic system’s interruptions become habitual. My own body’s habit of sympathetic breathing is ensnared with various other minor maladies like spinal misalignment and pelvic tilt. Since discovering this biomechanical tangle, I have deliberately worked to bring conscious breathing into yoga, walking and meditation, but it’s hard to relearn an instinct once it’s gone. 

COVID-19 and Breathing

I’m convinced for two reasons that a more intense version of breathing training — let’s call it “full-contact breath prophylaxis” — could save many lives worldwide, starting soon. The obvious reason breathing training could help fight the novel coronavirus known as COVID-19 is that improvements in immune and lung function directly reduce mortality, and even the simplest breathing practices like taking walks accomplish those improvements. So, presumably, super-intense preventative training before people get sick would benefit more people. Already, author J.K. Rowling credits breathing training (see here) with helping her recover from COVID-19.

The other reason sympathetic breathing matters is that COVID-19 impacts the nervous system. If a virus can cause neurological damage to the senses, as COVID-19 damages the sense of smell (anosmia), it might also cause neurological damage to muscular control — partial paralysis.

While I am not a medical doctor, my experience as a neuroscientist suggests that if the novel coronavirus partially paralyzes breathing, it might explain not only the tendency toward pneumonia, but also why so many COVID-19 patients need mechanical ventilators. (A situation known as diaphragm paralysis causes similar symptoms.) And if the paralysis affects the sympathetic system more than the parasympathetic, it might explain why more men than women suffer. (I’ve been told men use our sympathetic “pinger” systems more than women — it’s certainly true for me.)

While this sounds bad, it could actually be very good news, by enabling new forms of diagnosis and preventative treatment that don’t compete with existing ones. Breathing training doesn’t require a medical degree, just physical self-awareness and a willingness to help. So, in principle, it could spread around the world in months, first optimized by dedicated professional teams, then taught en masse by video and finally practiced in person everywhere. Bonus points for making people feel better immediately, as with yoga and exercise.

Right now, the people who best understand the biomechanics of effective breathing — practitioners of “alternative” medicine in all its forms — are stuck at home wishing they could help. Here’s how they can.

Heal Team Six

Imagine a crack team containing the following biomechanical specialties: spine-straightening (chiropractic, osteopathy, massage, Rolfing); breathwork (holotropic, Wim Hof method, Alexander technique, singing, chanting); neuromechanical trust (partner dance, animal therapy, contact improv); fluid motion (dance, Feldenkrais, yoga, martial arts); energy work (reiki, acupuncture, chi-gong); and verbal and non-verbal collaboration (circle meeting, T-group, moderated discussion). 

These disciplines are common in the San Francisco Bay Area, but Heal Team Six could be anywhere in the world since their task needs neither medical training, COVID-19 expertise nor money, just the ability to breathe and teach others to do so. The team’s task is to create deployable diagnostics and interventions. The diagnostics might include a language of how the act of breathing and muscles feel inside the body (interoception); homebuilt gadgets to measure the power, volume or speed of breathing; smartphone apps that infer motor deficits from accelerometer data; or any of a dozen human-to-human tricks for seeing or feeling if someone isn’t breathing fully.

The most potent, intense intervention one could imagine would be full-contact prophylactic breathwork, based on straightforward motor training principles.  Practitioners would teach people to breathe intensely before they get sick, a skill and habit that then helps both prevent and recover from pneumonia. (I almost died of pneumonia at age 25, and I don’t want anyone to suffer that.)

The “diaphragm” being trained is, in fact, a collection of some muscles that must co-activate to pull as well as others that more crucially must relax to let in air. Once Heal Team Six understands which felt muscular sensations matter most for potent breathing (perhaps the sternum, throat, lumbar spine, sides and pelvis), they can train the client to feel sensation and move those places. Furthermore, they can coach the client to feel and, ultimately, isolate the overlapping suites of muscles in the head operating head tilting, sinus-clearing, ear pressure, swallowing, eyebrows, eyes, vocalizing and sniffing. The more those various actions can operate independently, the larger fraction of the breathing muscles can be recruited while still concentrating on other things, defeating interruption by the sympathetic nervous system.

All of this complex coordination can be trained like any other muscle combination, especially if three intense practitioners are touching all the relevant spots all at once. A single client’s nervous system — surrounded, supported and cheered at once by three eager coaches — will be so overwhelmed that the client will learn much of the muscle-patterning by vibrational entrainment alone and the rest by their own efforts.

Imagine the following scenario playing out over a few days. First, the team would make sure the client’s spine can move and feel. Then, they would find which parts of the torso need more motion during breathing and practice activating those one at a time. Next, they would accustom the client to put pressure on many parts of the torso from multiple people at once. Finally, several people would touch those spots, while breathing deeply and loudly themselves and cheering the client on to do the same. From the outside, it would probably look and sound like a bellowing hippie huddle. From inside, it might feel amazing — just ask a dancer, monk or yogi.

This process would be far more intense, invasive and intimate than almost any physical activity short of military training. But desperate times call for desperate measures. Perhaps the most challenging aspect will be not physical but social because many bad breathing practices result from social pressure not to slouch, push out the belly, stick out the tongue or make faces, and clients will likely need to confront those taboos head-on by making their faces and bodies awkward, embarrassing and ugly, with rolled eyes and creepy grimaces. Against ingrained social aversion, being cheered on will help enormously.

Even unnatural motor patterns can be trained, and breathing is the most natural motor pattern one might imagine training. So, there must be a way to improve our breathing really well, really fast. Heal Team Six will find that way and teach it to the world in time to get us air.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Does COVID-19 Kill People Who Tend to Hold Their Breath? appeared first on Fair Observer.

I’m familiar with Zoom, and I believe it might pull this off. From what I’ve heard, almost uniquely in Silicon Valley, Zoom has a corporate culture, founder and workforce more people-centered than money-centered. So, uniquely, Zoom might be able to avoid the siren-song of giving customers what they say they want and instead give humans what nature says we need. Implementing that principle will require saying “no” to the short-term wishes of both customers and investors, and saying “yes” to nature’s long-term plans.

Making the Best of Social Distancing

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In particular, operating Zoom as a public utility optimally connecting human beings with each other — as opposed to optimally extracting revenue from them — will require principled commitments to audio fidelity, remote resonance, algorithmic neutrality, non-adversarial business models and videoconference etiquette. Lucky for us, Zoom has already started on some of those projects. If this works, people will look forward to Zoom calls as “special,” the way they used to look forward to long-distance phone calls back in the day. And global loneliness might finally, finally decrease.

Zoom is on the right track. Because of global work-from-home and school-from-home rules due to the novel coronavirus, Zoom’s user base recently grew twenty-fold, from 10 million to 200 million, most of whom aren’t even business customers. 

I’m one of them. In the last weeks, I’ve participated in Zoom-enabled parties, yoga classes and meditations. Serving as a real-time gathering spot makes Zoom the closest to a global social lifeline we have, and the technology best poised to reconnect human nervous systems according to the laws of nature. (This conclusion might seem odd, given that I’ve spent the last several years stumping for non-screen human connection.)

Audio Fidelity: Stereo and Microtime

The challenge: Humans connect emotionally through unconscious timing signals that can’t be noticed, digitized or monetized.

It is beyond question that the human nervous system creates perception and trust from ultra-high-precision interactions (see: Sensory Metrics of Neuromechanical Trust).  Likewise, humans’ remarkable abilities to hear where a sound came from depends on microsecond sound signals, as do our abilities to read emotional nuance. Those “microtime” signals are why LPs and copper-wire phones create so much better emotional experiences than CDs and digital audio.

These facts create three problems for Zoom. First, Zoom’s core brand is not audioconferencing but videoconferencing, so people using Zoom naturally pay more attention to screens than sound, although they should do the opposite because sound is wired deeper into us than screens. Second, computer sound as digitized by cheap built-in microphones is nothing like the sound from a good freestanding microphone. Third, while the sound from a good stereo microphone pair has much higher quality than from just one, Zoom’s most recent software release paradoxically makes stereo sound harder to use. I hope that decision is reversed soon because audio connection synchronizes people better than video and stereo synchronizes better than monoaural.

My back-of-the-envelope calculations suggest that the single improvement of using stereo microphones, all on its own, would increase human re-synchronization at least tenfold, merely due to better audio signal quality. That solution is available to anyone for about $20. There is one other semi-secret sauce solution — a proprietary analog circuit that approximately reconstitutes the microtime structure of the original source, even after that structure has been erased by digitization.

I have been experimenting with one such circuit courtesy of the patent owners (US 7,564,982). Most simply, this circuit measures the left-right channel microtime difference, amplifies it and re-inserts it into the headphones or speaker pair. To me, it sounds like the source is a living breathing person nearby, as if whispering next to me in the dark. That personal experience, along with biophysical understanding, tells me that such microtime amplification could improve remote connection dramatically.

Algorithmic Transparency: No Tracking or Photoshopping

The challenges: Enhanced self-presentation undermines communication, while eliminating tracking improves communication.

The baseline protocol for human communication was burned into our nervous systems way back in paleo times, before clothes and words. Everyone could see every inch of your body and hear your every grunt, and you couldn’t do anything to stop it. Contrast that case of “too much information” with Apple’s technology called “Facetime effects,” the image-processing trickery providing extraordinarily unnatural control over users’ appearance, all the way to replacing oneself with a boring but attractive cartoon avatar.

The problem is that if everyone gets to hide parts of themselves, then no one gets any honest information, and authenticity degrades into mere performance, absent genuine signals. Cartoon communication isn’t human communication, even if it’s what each separate individual might like to do. 

There was no privacy in paleo times, but also no recording and tracking. Paleo people didn’t even have words or cave paintings to record anything, much less up-to-the-millisecond biometric data including your gaze, heartbeat, skin temperature and anxiety level. Humans communicate most naturally, and trustingly, when they know they are not being recorded. Zoom has already been in trouble over privacy concerns, and it has responded by disabling invisible data-tracking and attention-tracking technologies.

On the visible user interface, Zoom is doing two things right and one wrong. On self-photoshopping, for example, Zoom allows only modest airbrush-like “touch up” effects, powerful enough to let someone feel comfortable enough, in close-up videos under bright lights, not to worry about makeup. Minor algorithmic makeup makes real facial expressions easier for everyone to see, so it’s just the right amount. But self-photoshopping could go too far, for example, if customers were offered a powerful “attractive and engaged” appearance via paid algorithmic trickery. (Once a platform starts monetizing fakery, it’s game over for an ecosystem of authentic communication).

Zoom users can also airbrush their backgrounds, using a virtual green-screen to block views of messy kitchens. That means you don’t need to clean up the house before your call, which is also just the right amount of user-control. Unfortunately, Zoom allows users to replace messy kitchens with moving backgrounds, such as flames, which on the Zoom interface distract horribly from the grid of tiny, barely-visible human faces (in front of the flames) that I’m trying to look at. Gratuitous moving backgrounds are a perfect example of how a legitimate preference of one user undermines communication for everyone.

Remote Resonance: Winner-Takes-All Audio vs. Symmetry

The challenge: Unlike “presentations” (such as webinars) in which one person talks and everyone else listens, human social resonance requires all-to-all transmission of subconscious signals.

Zoom’s current platform is designed for broadcast. When one person speaks, that sound stream is automatically selected for everyone to hear, while all other microphones are automatically muted. That’s the perfect solution for one-way communications.

But humans are two-way because we resonate. Or at least we try to. On my Zoom-enabled “group meditation,” I attempted to lead a minute’s worth of what primatologists call co-vocalizing, or what yoga people call “OM-ing.” I would chant a long vowel like “ahhh… ohhh… mmmm,” and in principle the others would hum along.  But it didn’t work. First, I couldn’t hear them because, of course, their microphones had been turned off while I was humming the sound.

But, weirdly, they couldn’t hear me either. It turns out that Zoom’s audio algorithm only detected a long, boring hum from my own microphone, decided the hum was background noise and then canceled it. So, my fellow meditators saw me with eyes closed and open mouth, yet they heard nothing. My own humming sound had been automatically erased. So much for interpersonal resonance.

A solution promoting resonance would be for Zoom to include a “resonance mode,” in which everyone’s microphone is on just a little bit, with no single sound stream dominating. The exact opposite of the current default, and for the exact opposite purpose: for unifying and synchronizing vibrations instead of separating spoken words.

I am collaborating with one team dedicated to human sonic resonance, the people running the Integratron “sound bath” center in the California desert. We are hoping to find ways to link resonant experiences like their sound baths remotely using stereo audio, Zoom and the microtime amplifier circuit.

A Non-Adversarial Business Model

The challenge: When carriers like Zoom pay for variable bandwidth but collect fixed subscription revenue, perverse financial incentives reduce the bandwidth customers receive and thus damage human communication.

Communication doesn’t need to be so bad. Over 40 years ago, even long-distance calls connected people well because voices were carried by dedicated copper wires the entire way, with an implicit service-level agreement of microtime phase fidelity. That was expensive, so Ma Bell invented computers to digitize and packetize voices, thus birthing much of the computer revolution. I was there: In 1985, during “divestiture,” I worked at ATT Bell Labs Murray Hill.

Once human bandwidth could be compressed into more cheaply recognizable packets, the race was on to minimize network bandwidth costs by ever-more-efficient voice compression. Unfortunately, that dynamic creates perverse network incentives to reduce bandwidth between communicating humans, although the humans themselves need as much bandwidth as possible. That incentive structure nearly guarantees that our (expensive) need for high-bandwidth interaction will fall victim to the network’s ever-present need for lower costs.

To operate in the best long-term interests of human communication — as opposed to any short-term metrics, especially monetary ones — Zoom needs to establish a long-term revenue model designed to enhance human communication. That is, a model which provides as much bandwidth as people need, in the form they need it, with transparently auditable metrics to prove it’s working. No one knows the structure of such a business yet, but that’s what innovation is for.

Better Videoconference Etiquette

The challenge: Human conversational habits evolved for in-person interaction and fail in various ways through screens.

Attending to screens for hours on end is really hard on us. It also doesn’t work very well because screen interaction is so unnatural. The thousands-fold discrepancy between our high-bandwidth 3D needs and the puny trickle of pixelated “content” is why telecommuting is so hard. Our social instincts need to know who said what, who laughed and who stayed silent. On video calls, it’s hard enough just to hear the words at all.

Here’s one example of rules of the road (aka “etiquette”) that might keep our conversations from crashing: stop looking at faces and concentrate on audio. 

Here’s why. At first, the video image of someone talking is the perfect way to recognize their face, mannerisms and mood, and to prove to yourself that this is a real live person talking. But once that truth is established, and you trust them, it makes more sense to close your eyes and listen to the words than to look at their face, because our circuits synchronize much faster on audio frequencies (milliseconds) than on screen refresh rates (tens of milliseconds).

Nature’s rules for optimum communication tell us to start with video, then move to audio while checking a face only occasionally. As long as everyone agrees on that solution, no one will even worry if you’re not looking at them on-screen. And that reduced expectation of on-screen “performance,” more than anything, will let people relax during video exchanges, which are one of the weirdest human interactions ever invented by humans.

Let’s hope we learn how to use these weird tools right and that their makers make them right for us to use.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post How Zoom Can Make Videoconferencing More Human-Friendly appeared first on Fair Observer.

Now everyone gets to taste that isolation in what may be the most widespread and sudden change in human behavior ever. In an instant, everyone stays home, and stays apart, worldwide. This is on top of an existing (anti)-epidemic of self-isolation, accelerating over the last decades, already making people alienated and lonely, in dire need of social exposure. Now, adding insult to injury, comes enforced social isolation to combat the virus. Necessary, but sad.

At the same time, a huge portion of the economy is abruptly shutting down, rendering many people even more desperate. The American economy just slowed down by a tenth — about $200 billion a month — mostly taken from the underpaid service workers who need the money most. 

What good might possibly come from this triple-threat of COVID-19, isolation and destitution? A wake-up call on many fronts, from how to be happier as humans (rather than as consumers) to designing economies to keep us happy (rather than consuming). It will be a bonus to find which technologies help our nervous systems and which hurt.

Below follow several ideas to make the best of the crisis as derived from the same mathematical principles informing my other articles in Tech Turncoat Truths.

Enjoy!

Keep your immune system strong by taking care of yourself and your housemates. Sleep in, eat well, take walks. Have family time, laugh, play games. Get to know your neighbors at two-arms’ length and appreciate how much they help our common project too. Enjoy a suddenly-cleaner outdoors and suddenly-quieter towns. Stop paying attention to fear-mongering news. If parents stay calm, small children will follow and may remember this time at home as the most fun time of their lives.

Geometric Math Informs Decisions

Right now is proof that science can trump politics. Because the exponential mathematics of epidemic spread is absolute and unavoidable, the collective response has been fast, forceful and followed by nearly everyone. Both the problem and solution are clear.

Anti-science presidents and enemy nations are now collaborating on preventing a relentless, fast-gaining enemy. Mathematical enemies must be fought mathematically. That fact is being used right now, and that fact ought to be used to restore social balance post-coronavirus and redesign future business rules around information science. Both human nervous systems and economies contain instabilities akin to the spread of pathogens, and both human and economic systems have been systematically corrupted. The same exponential mathematics used to combat COVID-19 can explain those problems too.

For example, the ideas now guiding global economies depend on an oversimplified understanding of information flow and trust because those ideas were invented before information science was discovered or trust was understood. Once economics grows to include the costs of information flow, its limited bandwidth, the crosstalk corrupting content and human nervous systems’ weaknesses, economic science will have both the mathematical heft of epidemiology and its problem-solving power.

To that end, protecting humans will require tilting legal and regulatory systems toward laws preserving human life and dignity, and away from laws preserving capital. At present, the tilt is the opposite.

Microtime Will Help

Human brains need microsecond-level interaction for proper function, which happens best in proximity. If you can get close, then walk side by side, stand back to back, link arms or talk face to face. If you need a couple of meters of social distance, then sing or talk from that range, but still nearby. I predict that people interacting neuromechanically will thrive the most during quarantine.

After proximity comes voice connection. Just a few minutes chat every few days is fine to resynch emotional circuits, the way parents call kids. Stick to small talk because it’s all about the familiar sound, not the words. Unfortunately, text carries no trust-forming microtime. Every time we trust the written word, our reservoirs of trust deplete. So don’t use text channels to argue or work through emotions.

The global shock of COVID-19 to our economies and social lives is so great that the world must change. If we pay attention, we can make the change for the better.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Making the Best of Social Distancing appeared first on Fair Observer.

Just now, COVID-19, a regular coronavirus, is spreading like a regular epidemic. So far only tens of thousands are affected, not tens of millions, but already public health is a top priority. Stopping viral spread trumps profit, property, even personal autonomy. If quarantine is necessary, so be it.

Chronic loneliness already affects hundreds of millions of unhappy, unhealthy people. Two years ago, former US chief medical official, Surgeon General Vivek Murthy, declared loneliness to be an “epidemic.” Insofar as the word epidemic means “accelerating health threat,” yes, there absolutely is an epidemic of loneliness. A quarter of Britons don’t have a best friend.

And not only does loneliness make one unhappy — it damages one’s health. Loneliness makes people sicker and promotes chronic inflammation, which in turn promotes other illnesses like cancer and heart disease, and makes them too listless to seek out company, making loneliness feed on itself.

It’s not just loneliness. Accelerating year on year, people all over the world are also becoming more depressed, anxious, fearful, hateful and so on. The common thread is physical and emotional separation from other people. Isolation, alienation and anti-sociability are spreading worldwide, fast.

A month ago, I described a major cause for this runaway dynamic: remote communications like broadcast and wireless — technically, disconnection — transmit fear and anxiety far better than affection and support. The gist: any kind of sudden alert, like a gazelle’s white tail flashing alert of a predator, transmits one-way fear, driving creatures apart.

So the more people consume remote input, the lonelier they are, period. The threat accelerates because isolated, anxious people consume relatively more remote communications and become yet lonelier as a result, and so the vicious circle continues.  That exponential spread makes it an “epidemic.”

But loneliness is unlike any epidemic anyone has seen before. That is because loneliness is a metaphorical epidemic, not a literal one. Literal epidemics involve physical contagions spread by physical contact: germs, viruses, parasites, misfolded proteins (mad cow disease) or tumor cells (Tasmanian Devil facial cancer). Because humans are a social species, and social contact spreads disease, the go-to cure for stopping epidemic spread has been social isolation — quarantine. You catch the disease from other people. You stop the spread by isolating them.

This is not the way to stop the so-called loneliness epidemic. We’ve reached the limits of the epidemic metaphor, which communicates only the urgency but gives the wrong antidote. We need an accurate, actionable metaphor.

Meanwhile, let’s call the exponential spread of loneliness an “anti-epidemic.” Loneliness is a psychological state, not a physical contagion. Among humans, feelings like sadness and joy tend to spread when we’re nearby, not alone. So the “epidemic” spread of loneliness isn’t like catching a physical disease from other people, but precisely the opposite. You become lonely because you aren’t around other people. And if you’re lonely — or alienated, anxious, angry or fearful — you tend to disengage from other people too, which makes everyone, you and them too, yet lonelier. (Snubbing really hurts.)

The core cause of these anti-social feelings is anti-social behavior, which both results from and causes more anti-social behavior. To bring it home: We stop loneliness by bringing us together, as much and as close as possible.

By almost any quantitative measure I can think of — year-on-year growth, number of people affected, economic consequences, net human misery — this anti-epidemic of anti-social behavior beats global warming and COVID-19 tenfold. That makes it worthy of resources at every possible scale, from the minuscule to the grand, from “Should I smile at people?” and “Should I give my employees more time to socialize?” to “Should I spread fear?” and “Should I start a war?”

So no matter who you are, no matter what your power, if you can understand how the anti-epidemic of self-isolation spreads, you know how to help. Connect people. Pull machines out of human interaction and reduce the interruptions they impose. Be sympathetic to people whose only desperate social interaction is talking to a checkout clerk. One can’t climb out of loneliness by oneself, and willpower doesn’t help.

Again: We stop loneliness by bringing us together, as much and as close as possible. Anti-quarantine.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Anti-Quarantine to Stop an Anti-Epidemic appeared first on Fair Observer.

“I am perhaps the least naturally-gifted yoga student ever. 

I was surprised to find through a chiropractor’s X-ray, at age 50, after a lifetime of athletics, that I have a full suite of spinal diseases: arthritis, scoliosis, anterior pelvic tilt, military neck, spongylosis, etc etc. That explained, finally, why never in my life did I feel the “core engagement” other people did. In fact, I’ve been trying quite earnestly to “engage my core” for at least a decade through yoga, Pilates, pole, and various homebrew interventions, only lately succeeding somewhat, and as a result have been the most annoying question-asker in many a class.

On the other hand, I am a biophysicist, neuroscientist, and technologist with a fair claim to understand the basic principles on which yoga and virtually all other alternative embodiment modalities (say acupuncture and chiropractic) are based. That understanding has enabled me, in spite of a spine and a diaphragm wrapped in sensorimotor dark space, to resurrect much of my neuromotor circuitry from a lifetime of core-free, breath-free, outside-in operation. The best restoration project ever, repairing a healthy but completely locked-up middle-aged body. It’s an amazing transformation, and I’d like to share it.

So as a student I might be a nightmare or a blessing.”  

Once I was accepted and began attending classes, 4.5 hours in a row in a basement, the nightmare part became obvious. Every second minute during class, my hand would shoot up (or flutter discretely) to interrupt the speaker with neuromechanical commentary, some of it helpful, all of it weird and contrarian.

A Cure for the Global Isolation Epidemic Is Close at Hand

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But the “blessing” part dominated, at least for me. That program was practically the best experience possible, a perfect mid-life activity for a middle-aged, middle-class, meddlesome technologist. I went to class every Saturday and Sunday afternoon with a bunch of sweet, energetic people. We sat on mats like in kindergarten and got to stick our butts in the air and do headstands when restlessness struck during class. Being allowed, nay invited, to move during meetings makes a bad day of yoga better than a good day of work. What better way to spend weekends?

No Words Needed

We learned straight from the best, master-class style, about all kinds of yoga — the most important field of activity anywhere for making human beings healthy and happy. Rebecca Kovacs led a resonant gathering, complete with sound, to illuminate her idea that “the spine is a spiritual antenna” (I agree). James Fox, founder of the Prison Yoga Project, showed how to relax and destress people living in one of the most stressful places on Earth, an American prison. No wonder he has such an impact, his program now in hundreds of prisons worldwide: James Fox guided our group into amazing cohesion, like a priest or orator.

Our student group’s maternal, collaborative energy — ultimately all women save me — gently deflected even the most tone-deaf lecturers. While the Palo Alto sidewalk upstairs parked million-dollar sportscars and billion-dollar deals, downstairs, in our windowless bunker, our primate kin group sat around on the ground, glowing with something rare and wonderful in this valley: self-awareness and group resonance for their own sakes, uncorrupted by monetization or self-promotion. We did what humans evolved to do, we had fun, and we felt nourished.

Everybody agreed that group yoga is the most potent. Evolution helps: A reasonable definition of paleo primate play is to hang out with age-mates moving in fun or comfortable ways, showing off and cheering each other on, with all triumphs and failures visible at close range, groans and hoots together. Homo sapiens’ original path to social and physical happiness remains a collective exchange of information in which megabytes of subtle sensory signals fly back and forth, no words needed.

My biggest personal enjoyment and accomplishment was stretching, bending, “ironing out” the many kinks in my own old bones and enjoying the afterglow among other people doing the same thing. Now, I feel physically better than I did as a teen.

Yoga Neuromechanics

My second-biggest enjoyment was discovering that the abstract neuromechanical theory I’ve been working on for years in private, which explains how yoga works in secular terms, may be what yoga as a discipline needs most right now.

Spontaneously in class, often without warning, one or another of us students would be asked to lead everybody in an exercise. More times than I can remember, I invented a brand new physical activity on the spot using neuromechanical principles, and people really liked it. In particular, igniting and sculpting what might be called “group resonance” became my specialty: live delicious human connection, inspired by theoretical physics. I also invented a trick to make people feel safer with physical contact.

Backstory: The very most successful yoga traditions and practices involve hands-on touch, often called adjustments or assists, in which the instructor places hands on the student, presumably to improve their physical posture. Unfortunately, too many charismatic teachers have touched too many students the wrong way, in which case a whole therapeutic yoga practice (not just the abuser) falls into disgrace, leaving yoga students even more afraid of being touched than before, and leaving both teachers and studios more afraid to offer assists in their classes.

Here is a trick I used several times to address that critical concern about consent. In front of each student’s mat, I place three colored index cards: red, green, white, with the white card on top. I ask them to put the red card on top if or whenever during class they do not want touch. Or they might instead display the green card as an invitation to ask about my assisting. During instruction, I can now approach any student whose green card is facing up, knowing at least an offer of assistance is expected and welcome. 

The cards work because they give students more choices and more power. First and most obviously, using a card each student can declare a preference without having to talk (and without the teacher needing to remember!) and can change it at any time. Furthermore, no one is forced into a choice. Just leave the white card on top, so the instructor will know they’re not playing that game.

Common-Sense Communication

Common-sense communication inventions like those cards, along with the more subtle principles of neuromechanics, could create a revolution. They will allow us to create techniques especially responsive to modern maladies, unhindered by tradition. I want my new career to be reviving the minds and bodies nature gave to us.

First among the skills we will need to enact this revolution, especially in tech-obsessed Silicon Valley, is collaboration. In a “collaborative yoga” class, students one by one would invent, explain and demonstrate new poses as in a collective laboratory. Once people learn to co-invent collaboratively as easily as individuals invent alone, the whole game changes, putting play and fun as number one.

Next up will be my own specialty, “data science yoga,” because yoga practice provides specially-tuned information streams essential for recalibrating mechanically sensitive bodies. Data-science yoga will unabashedly invoke neuromechanical ideas about learning for certain people, such as data scientists and “spectrum” people like myself, who find the language of technology more actionable than vague terms like “core,” “diaphragm,” “pelvic floor” and “heart chakra.” Especially people unfamiliar with those internal sensations deserve to know how to make them work inside themselves.

As of last week, our teacher training course is over. To keep in touch, we’re hosting parties and sound healings, and trading advice on yoga jobs. My perfect yoga job would be holding workshops, teaching people how to drive their nervous systems using nature’s manual. I know I’m lightyears away from the popular image of a yoga instructor — I’m bald, male, crusty, middle-aged, abstract — but I have wonderful news to share, and a new language to share it. In particular, now I am ever more certain that yoga has answers to life, and that neuromechanics has answers to yoga. 

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Can Neuromechanics Help Jump-Start a Yoga Revolution? appeared first on Fair Observer.

Now consider gazelles. Herding animals, they spend almost all their time feeding, jostling neighbors, locking horns, sleeping and mating. They evolved for reciprocal, autonomous neuromechanical interaction. Their nervous systems need those vibratory reinforcement signals to regulate biorhythms and stay sane.

No wait! A white tail flashed! Gazelles leap, white tail up, white tail up, white tail up! Everyone sprint! Go! Go! Go! No time to wait! Alarm has sounded! Danger! Run!

That’s the gazelle version of broadcast media: fast, one-way, designed to catch attention, distract, motivate. That is, to motivate alarm, fear, urgency and hatred — quick-response reactions. Broadcast doesn’t motivate bonding, affection and love, but the opposite.

That’s because it can’t. Bonding, affection and love need reciprocal, autonomous interaction, the one thing broadcast by definition cannot do. I’m sure that any isolated gazelle, if subjected to white-tail-flash signals on its eyeballs all day long, would be a nervous wreck.

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That’s how broadcast media work and don’t work. Broadcast of any form, even old-school newspapers and radio, suffer from the gazelle-tail problem of communicating emotions which isolate people far more efficiently than emotions which bring us closer. Furthermore, modern digital transmission focuses and concentrates the subtle social toxicity of broadcast thousandfold, by mixing in personal segmentation, instant delivery and monetization. Digital things do grab our attention very efficiently — on purpose.

To that overdose of white tail flash add the physical isolation so many people suffer nowadays, spending whole days seeing no human face in person and touching no human hand, even as they watch alarming news on screens. Consuming information that can only agitate you is bad enough; doing it alone is even worse. No wonder whole countries are filling up with hate and fear.

Human children weren’t born for this. We were born for kinship, companionship, snuggles, grappling, eye-gazing, grooming — and of course hunting, gathering and resting. That is, we need reciprocal autonomous neuromechanical interaction, just like the gazelles. If we get enough proximity and touch, enough live conversation and back rubs and hugs and arm links and scalp massages, then we’re happy again. That’s just how warm-blooded biology works.

The global epidemic of isolation results directly from the automated technologies of attention-harvesting, “social” media and online advertising. Like most outbreaks, isolation festers most severely at the epicenter — my boyhood home of Silicon Valley — where together and separately everyone typically eats meals in silence, hunched over phone; where no one has time to do anything, especially to talk; where people are always suspicious of “pitches”; where healthy, well-educated teenagers throw themselves in front of trains to die.

The tragedy is that homo sapiens, the most deeply and intricately loving and empathic species ever to walk planet Earth, is now among the most lonely, hateful and anxious, thanks entirely to technology that makes us look at and touch it instead of each other. And thanks to white-tail-flash fear and anger, broadcast tech acts like an enchanted window that, by transmitting mostly awfulness, makes everyone seem awful and worth avoiding.

Fortunately, the cure is close, at hand.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post A Cure for the Global Isolation Epidemic Is Close at Hand appeared first on Fair Observer.

In fact, the more people read printed news, the more valuable it is, being both trusted by many and known by many. With rewards like those, of course some news outlets grow to national, even international, scale, almost like natural monopolies, and provide whole societies with standardized, synchronized information. With a subscription, any person or library could have their own complete, permanent record of what matters — and mattered — to society.

Now update printed news to the digital age. The cost of copying and delivering information goes from cheap to free, meaning more profits for the outlet but also more uncaptured revenue — because each reader can now copy and deliver too. Furthermore, each specific reader can be profiled, so that specific items and ads can be tailored for each reader. It’s almost the perfect business.

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“Almost,” because while digital platforms give far more fine-grained control over readers, they lose control over money. It’s actually too easy to copy digital content, and too easy for readers to find free versions, so the old pay-for-paper model, with its chokepoint at the retailer, doesn’t work anymore. One solution is extra advertising, bound so tightly with the news, paragraph by paragraph, that you can’t escape it. Unfortunately, such relentless interruption undermines reading comprehension and drives readers crazy.

An Almost Perfect Business

The alternative is to charge for digital access, with a paywall. A paywall not only captures revenue otherwise lost but, by making the information harder to access, it reaps the rewards of scarcity, because hard-to-get things are more valuable. Furthermore, a paywall can charge different rates to different people and give different things in return, so money and attention can be most effectively squeezed out of readers. In fact, if you ask the simple business question about how to turn an existing news source into money, a paywall seems the best answer. And it is the best answer, but to the wrong question.

The right question asks about the opposite influence: How do paywall revenues influence the information being supplied?

That depends on what you mean by “information.” Economics and computer science both understand information, but in different ways. As a general rule, economics considers information to be part of the essential infrastructure, like air: necessary, neutral and freely available. Or rather, economists use the concept of “free information” to prove theorems about stable economic balances in free markets. But as American laissez-faire economist Milton Friedman once said, “There is no such thing as a free lunch.” He could have also said that “There is no such thing as free information.” Information costs money and is worth money. The rarer it is, the more it’s worth — and the more it’s worth to copy.

That insight is so deep, even computer scientists understand it. In fact, one of them proved it mathematically. Claude Shannon, who invented the concepts of bytes and bandwidth, proved that the more unlikely a message is, the more information (bits or bytes) it carries. But there’s a catch: If you even copy the information once — much less a million times — you change those probabilities, and thus change the actual information carried by the message, even if the apparent information (the content) remains the same. So copying, just by itself, corrupts information. A stock tip on the front page isn’t worth as much.

Now add in moral hazards, the economic term for foxes guarding henhouses. For hundreds of years newspapers tilted news toward advertisers and those in power, but the tools were coarse, and proof lingered on paper. Online advertising has millions of times more data now, so the moneybags now have even more power to ensure the news serves their own interests. And since there is no solid paper to store, there is no way to record whatever chicanery keeps those sponsors happy. Biased news helps defray the bills, leaving little lingering trace, save on balance sheets. In the online world, unbiased news is more expensive to write — and harder to sell.

Moral hazards show up inside newsrooms too. The New York Times is reputed to earn $600 million a year from its paywall, which means half a billion dollars from people reading news on screens. With that much revenue at stake, how likely are they to report on the undisputed technological proof that screen use damages the human nervous system? Economically, their paywall forces them to stay hush about a dangerous technology.

Human Glue

The root problem is a bit of business wisdom I learned as a data scientist at a large aggregator of online sales “leads.” As I wrote the automated fraud-detection system, I was told to devalue so-called incentivized leads — “fill out this form, get a free phone”— as the least reliable ones in our entire ecosystem. The general rule is embarrassingly obvious: If monetary forces have a chance to influence information according to their specific bias, they will. It’s their job. Thus, incentives undermine trust.

To be sure, business pressures and human trust have co-existed for millennia, at least until recently. So obviously, incentives all by themselves don’t cancel human trust. But human trust, over not just millennia but over millions of years, was formed by eye contact, proximity, handshakes and long-term relationships, multiple forms of high-bandwidth sensory information entirely missing online. In the absence of that potent human glue, trust will inevitably erode, but it happens much faster when business pressures work their magic.

In short, business doesn’t understand trust once computers are involved. Fortunately, computer scientists do. They know two things.

First, they know that errors cascade. One becomes two becomes four becomes eight, and so on. That’s why even a single bit-flip can crash a computer. Second, they know that distributed processors must cooperate. If different parts of a computer start competing with each other, especially undermining each other’s communications the way warring nations do, the system must fail. So digital computers trust every bit, because every bit is perfect. It has to be.

To understand distributed human trust, imagine our base hardware in its original analog “paleo” configuration: pre-verbal Homo sapiens. Before words, our biped ancestors foraged and hunted in tight-knit groups, communicating entirely with grunts, hoots, grimaces and back-slaps. That is, their interactive, distributed communications channel was live vibration, like elaborate tuning forks linked over meters and seconds, down to micrometers and microseconds. As vibrating jelly bags, they stayed “in tune” with each other without using words or categories. That’s how we natively collaborate.

The good news is, we know the human kind of distributed computing works, or we wouldn’t be here. The bad news is, our version needs in-your-face reciprocity, which doesn’t work online. Imagine news, back in the day. An incident seen by a human being, and recounted around the campfire in the presence of other human beings, counted as trustworthy “news” to a human. Physical newspapers were still somewhat trustworthy, because a newspaper published over years by a known citizen, in public on enduring newsprint, had real people as publishers and editors, and had a medium — paper — which was transparent and enduring. An article flickering on a screen under a logo is far less trustworthy, being devoid of permanence and human presence. The worst, paywall-enabled news presentation occurs when online messages appear differently to each reader, as tailored by ads and algorithms, and can disappear whenever powerful interests wish, replaced by a sanitized version under the same title.

So the very features of digital news which help paywalls make money — their abilities to track readers, to rewrite and repost at will, to prevent unauthorized access and attribution — also undermine both individual trust and public trust. Paywall outlets do provide whole societies with information, but “personalization” means it is now neither standardized nor synchronized, and thus not useful for solving social problems. Unlike subscription newspapers, paywalls contribute noise and bias more than signal. In the neutral terms of computer science and data science, paywalls and ad tech undermine trust. It’s time for real innovators to find a real solution.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Paywall Paradox: How Good Business Does Bad appeared first on Fair Observer.

How Human Collaboration Can Beat Screen Addiction

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Such digital demonization must be reversed for humans to survive. Whether you think Rushkoff is right or wrong, what other discipline of scientist (besides media theorist) is there to understand our communications problems, and to pose it specifically enough so we might have hope to solve it?

Cryptographers

Enter cryptographers because they are, in essence, media theorists too but of a much more powerful sort. Rushkoff is a traditional media theorist, who studies “the media” directly. His tribe examines various media (books, TV, the internet, Facebook) via historical examples and then publishes the results through similar outlets. It seems straightforward enough. Other media theorists using that approach have been Ray Bradbury,  Michel Foucault,  George Orwell and Marshall McLuhan.

The superpower of a media theorist is direct domain expertise through evidence of how media actually operate in the real world. The super-weakness (or Kryptonite) is the reliance on the data — historical examples — on which their own work proves to be systematically biased and untrustworthy. The super-lesson of media theorists is, in Orwell’s words, “He who controls the past, controls the future; and he who controls the present, controls the past.” Or more pithily, “History is written by the victors.” Hats off to theorists like Rushkoff, who have to fight fire with fire, and muck with muck. Media theory is slippery, the hardest sort of theory there is.

Fortunately, there are other ways that humans communicate and miscommunicate besides “the media.” Studying those ways might address our problems more effectively. For example, you could understand brains as signal-processing instruments and then calculate how nervous systems establish trust in mathematical terms, as Criscillia Benford and I have done. You could be a magician or a medium (pun intended) who understands how to fool humans in real-time, and how easily we can be fooled. Or you could be a cryptographer who understands communication as a general mathematics process of code-making and code-breaking. In that case, your results would be statistical, bulletproof and guaranteed.

Cryptographers are the ones responsible for ATMs, data encryption and Bitcoin. They do the numbers so carefully that their results are guaranteed by the unchanging laws of mathematics and statistics. When they understand a communications channel or encoding/decoding protocol, their understanding is as reliable as anything in science.

Alice and Bob

A typical cryptography dilemma involves communicating between A and B (usually denoted as Alice and Bob). Alice and Bob want to communicate privately. That means they don’t want outsiders to eavesdrop and certainly don’t want outsiders to rewrite their messages surreptitiously. The name that cryptographers have for such maleficent manipulation of messages between Alice and Bob is a “man-in-the-middle attack” (MITM). In their lexicon, MITM is the mathematical term for a particular kind of hostile communications exploit, in this case exactly the kind of thing that digital media do between humans.

It’s already obvious that digital media companies read our messages. That’s how Facebook and Google admit to making money in the first place. It’s less obvious how they write, rewrite and reorder our messages, at least until you consider how much people rely on auto-response, auto-correct and spam filters. And digital media read and rewrite not at random, but in ways specifically calculated to take money and attention from us. That is, they mess with our messages in part against our interests. That means digital media act like a “man in the middle” when we communicate, making those communications — in cryptographic terms — presumably not trustworthy.

Cryptographers calculate code-breaking, so applying their term has a kind of heft that traditional media theory could never have. Banks listen to cryptographers. The Pentagon listens to cryptographers. Bitcoin listens to cryptographers. Even venture capitalists listen to cryptographers, if they listen to anyone.

The only problem is that cryptographers typically solve different problems, using different assumptions. Cryptographers typically want trust to be perfect, then try to change the codes and channel to hit that goal. Compared to that, a human’s digital dilemma is inverted: We already have a faulty channel we can’t fix, a bunch of media corrupted by specific biases toward profit and power, so we need to find a way to use those damaged media in the most trustworthy way possible. This isn’t the kind of problem cryptographers usually solve, but I’m sure they and their mathematical tools are up to the job.

Faking It

So, perhaps, in an ideal world, an official cryptographer or two could restate the “Team Human” problem, the problem of fake media, as something like this: Suppose many Alices want to communicate with many Bobs through media channels in which a man in the middle is guaranteed to selectively amplify and filters messages, in secret, as advertising and profit-driven media must do for business reasons. Given this breached channel, what is the best strategy by which Alice and Bob can still communicate with and trust each other?

Worldwide, ever-more important decisions — those about politics, business, personal finance, medical care and so on — are being made through digital rather than real-life media channels. Because so many digital interactions are already faked or fake-able, the channel is clearly not trustworthy and seems to be getting worse. Humans need a fail-safe, fail-over plan to maintain trust. Who better than the caretakers of mathematical trust to set it right?

So, if you know an actual cryptographer, please forward this article. If you yourself are an actual cryptographer, please consider this request: Uniquely among professions, you have both the tools for calculating what has gone wrong with human digital communication and the respect for suggesting a fix or two. We humans have been hacked. Please help us un-hack ourselves.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The “Man in the Middle” Is Media Messing With Your Messages appeared first on Fair Observer.

It turns out that data science and neuroscience are like that. Those barely-overlapping disciplines each understand complementary things about human brains. Unfortunately, when these insights combine, the consequences can be catastrophic for mental health. What data science understands could be called “optimized persuasion.” What neuroscience understands is called “natural statistics.” Not many people are familiar with both ideas because expertise in either data science or neuroscience is rare, and finding both together in one brain is even rarer.

So lucky me — my PhD combined data science and neuroscience, and I’ve worked for over a decade in each field simplifying, inventing, explaining, analyzing and even helping save Microsoft’s NT5. My lucky accident of double training lets me see how brains work and also how technology affects them. As a bonus, I’m married to a fiercely independent thinker who understands mediated communication and story structure (“narratology”). Our combined expertise covers a wide swath of science and the humanities, and the peer-reviewed research report from our three-year sabbatical was published in 2017.

An Epic Battle

Here’s the gist I want you to know, as a fellow warm-blooded human who cares about those close to you: We’re in the midst of an epic battle between two historic forces, neither of which seems likely to retreat. In one corner, the triumph of data science and algorithms over our sensory and attentional systems — i.e., effective automated persuasion on a global scale. We humans have been hacked. In the other corner, the response of those sensory and attentional systems to a novel, 24/7 data flow containing weird regularities and interruptions, a statistical ensemble that looks nothing like the natural environment in which that hyper-sensitive system is able to self-calibrate. The irresistible force vs. our brittle brains.

The key neuroscience concept behind the brittleness of brains is “natural statistics.” It turns out that animal brains evolved to operate in natural environments, and they also learn best in those same environments. For example, a few decades ago, my long-time colleagues Bruno Olshausen and Dan Ruderman showed that the information-processing properties of the mammalian visual system ought to have evolved to work best in the forest-and-bush-heavy environment of nature, and in fact neurons do work that way.

In other words, our eyes expect natural-looking fine detail everywhere. The natural world is filigree. That’s what the visual system processes and learns from. Saying that nature looks like nature is now quantifiable and has become a crucial concept for understanding how brains work. For example, lab animals that grow up in cages, which are flat, boring and lit by flickering lights, have bad vision compared to ones that live outdoors.

Neuroscientists already know that hours a day of fake, distracting, unnatural input is bad for animal brains in general; why would it not be true for human brains?

On the other hand, as we know, electronic technology is ever-more addictive, intrusive and profitable, now consuming half of our waking hours and social lives, more or less. The problem isn’t that technology is necessarily bad — it isn’t — but that the specific kinds of technologies we find most captivating are bad, precisely because we find them captivating.

Our informational appetites evolved in the bush, where interesting things and dopamine are hard to find. Now, we have quick hits everywhere. Any kind of animal tends to get addicted when appetizing things once rare in nature — cocaine-levers for rats, laser dots for cats, treadmills for mice — become suddenly common. For really unusual stimuli, even existing at all violates nature’s statistical contract.

You don’t need to know the technical details of our scientific article (I’ll explain it if you want). The gist is threefold: 1) any technology that influences our sensory interactions affects our brains in numerous ways; 2) most of the damage is unconscious; and 3) our response to damage usually seeks even more of the damage-causing media.

From Cave Art to the TV

Of course, this has always been true of representational technologies, from cave art to novels to TV. As we fogies keep saying, don’t look too long at the flat thing because it is nothing like the real thing. But smooth sidewalks and flat walls are also unnatural and also deprive us of the natural variability we need. So, in a deep sense, the problem we face is as old as material culture itself — we build things we find fascinating, then we become fascinated by them.

But now the things we build are a million times faster and smarter than us. Technology has outstripped the human sensory system. We are simple beings, whose nervous systems evolved to work in the simple medium of air. Air is multi-sensory, high-fidelity, dropout-free, symmetrical and honest. It is in every way the opposite of the digital world. Persuasive representational technologies, on the other hand, have never before been so well-informed, so integrated into daily life, so interactive, so instantaneous, so “smart,” and so focused. As a species, machines have won the evolutionary bandwidth war hands-down. And they’re getting better all the time.

The good news: Just get back in 3D space and you’ll be fine. “Natural statistics” is why hikes outdoors make us feel better and why laughter in a crowded pub beats watching videos by yourself. From technology’s point of view, the onslaught of tech taking over human minds seems unstoppable. But from a human point of view, just turn it off and look around. You’re still here, after all.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post When Data Science and Neuroscience Collide appeared first on Fair Observer.

Some of us in Silicon Valley are trying to recreate those experiences. Here, the move-fast attitude that spawned digital hacking now also supports “biohacking,” the modification of bodily function through unusual chemical or thermal interventions. Applying scientific principles to improve one’s own life is now the rage of the CEO class.  The techniques usually work, improving not just overall health but mental clarity.

Biohacking

Twitter CEO Jack Dorsey has popularized biohacking, even without claiming superpowers for himself. And history provides dramatic superhuman examples like Harry Houdini, whose famous underwater escapes involved simultaneous feats of cold tolerance, physical endurance, breath control, contortion and fearlessness. Today, the “iceman” Wim Hof can swim at the North Pole. Others can hold their breath for more than 10 minutes. It only takes a few examples like these to show that human superpowers are possible.

Contemporary biohacking falls neatly in two classes: deprivation and intervention. On the deprivation side are paleo diets, calorie restriction, intermittent fasting, “dopamine fasting” and cold tolerance. Intervention in those same metabolic systems might include dietary supplements, “micro-dosing” of hallucinogens or cryotherapy. As with diets, success requires weeks of consistent practice, so that feedback about what works comes slowly.

Buried in biohacking’s consistent success is a spectrum from safe to risky. On the safe side, each of the “deprivation” practices recreates part of the paleo environment, before tools or clothes, which biped bodies originally evolved for. If you think about the lifestyle of paleo people, their core competency was dealing daily with deprivation.

The innate discomfort of deprivation makes it unlikely to be addictive or to make much money. Because it works by sensorimotor recalibration, deprivation is safe from perverse economic incentives. On the other hand, the “intervention” practices, from supplements to drugs, have a different goal: to produce specific biochemical results or experiences, usually through commercially-supplied products. The appeal of this second path to both users and suppliers is obvious, as is its potential for abuse.

Biohacking vs. Neurohacking

Biohacking is what’s getting the buzz. But neuroscientific principles point to a more powerful way to hack the human nervous system: neurohacking.

By neurohacking, I mean hacking using the physical principles of neuromechanics in place of neurochemistry. That is, using the mathematical signal-processing laws connecting muscular vibrations to brain impulses during action and learning. It turns out you can use data-flow and physics ideas on their own to understand what might be called optimum biomechanics and hence optimum human function.

Those insights allow you to predict patterns of motor-neuron pulses that will improve balance and facilitate graceful and efficient running, internal heat generation, sensory sensitivity, interpersonal connection and so on. For example, optimal biomechanics enables hyper-athletes to perform simultaneous feats of strength, flexibility, coordination, grace, fluidity and expressiveness. For a shining example, look at Caltech physics graduate Renee Wu.

The pulse-timing principles of neuromechanics do not care what generated the pulses, so that — ironically — you can understand “neurohacking” without understanding neurons at all. That neuron-free approach is so untraditionally simple that many scientists have trouble with it, and research institutions do not yet fund it.

If biohacking is metabolic, then neurohacking is mechanical. Biohacking changes a body’s chemical or thermal environment over hours or days. By modifying muscle firings, neurohacking operates a billion times faster on microsecond neuromuscular phase. But be careful: High-speed interventions give high-speed feedback and improvement, but like other fast things, they can also spin out or explode.

The key principle from information science is this: The smaller the signals in space and time, the higher the bandwidth and information density they carry.

Physics tells us that brains operate with microseconds. However, we only consciously think and react in tenths of a second. This means that consciousness is 10,000 times lower and coarser than the deepest neuromechanical unconscious, where sensation is made. The fact that humans can operate in that ultrafast regime is both good and bad news. Biologically, high-bandwidth flow states are fun and healthy (albeit subtle), but their very speed and power, buried deeper than breathing or blinking, also puts them beneath the reach of conscious rules and memory.

Here’s my hypothesis: If the most effective digital “hack” of a computer would (by addressing the fastest and smallest bit-transitions and transistor-gates) enable execution of virtually any digital computation, then the most effective analog neurohack of a brain would (by addressing the most precisely-timed neural firings in the body) enable executing of virtually any muscular output from internal heat to eternal force, and thus enable experiencing virtually any sensation from calmness to ecstasy. The experience of maximum sensorimotor bandwidth is profound: time slows down, senses feel hyperacute and empathy upwells for others and even oneself.

White Hat vs. Black Hat

Once you start pushing any hardware to and past its design limits, you’re hacking. In the world of hacking, “black-hat” actors seek individual short-term profit and power, while “white hats” seek pro-social fairness and the long-term stability of the ecosystem. The distinction between white hat and black hat applies to biohacking too.

Whether biohacking or neurohacking, the science of testing white hat vs. black hat techniques could not be more different. Black-hat hacking, as it explores the most easily-scaled ways to gather money and power, inevitably leans toward the greatest impact on the greatest number, so it looks at populations and averages.

On the other hand, science seeking the uppermost human capacities has no use for averages, especially averages over sedentary, coddled populations. The scientific pursuit of extremes needs only sensitive, coordinated, powerful individuals, the near-superhuman outliers like Hof, Wu and Houdini. Outliers prove what’s possible as opposed to what’s normal.

Neurohacking faces the same white hat vs. black hat challenge, but even more so. First, because neurohacking operates below conscious awareness, you don’t know how it affects you until after the fact. More crucially, some neurohacking operates below conscious reaction times, so you respond instinctively before choice is even possible. While one might summon a few seconds of willpower between wanting a cigarette and lighting it, your eyes and attention move far faster, alighting on a sudden surprise the moment it enters your brain, before willpower is even possible.

Because neurohacking can be yet more scalable, monetizable and habit-forming than biohacking and less easily resisted, its black hat version is even more dangerous, especially in the hands of organizations. Think of the damage done by the Opium Wars, big tobacco and the sugar industry. The evidence is everywhere that two common sensorimotor manipulations — persuasive technology and “screen addiction” — already damage human health worldwide. To keep us safe from even deeper threats, neurohacking must stay in purely human hands, unmonetized, unsupervised and unregulated. (More on that at the end.)

But even white-hat biohacking still carries dangers. In recent decades, people have died from nutritional failures, supplement overdoses and cryotherapy. Over the centuries, people have suffered psychic breaks from yoga and meditation.

Principles of Neurohacking

So, consider yourself warned. I am not a medical doctor, I am a theoretical physicist. And I am not providing medical advice. What I am saying is you can hack a brain when you know how it works.

At the core, all brains control body vibrations, ranging from sub-bass body tremor to ultrasonic micro-tremor, that is from seconds down to microseconds. A brain controls vibrations the way a supercollider controls particles: by cleaning, coordinating and collimating wavefronts passing through myofascial conduits until the ultrasonic micro-tremors ring like coherent laser light. That ultra-pure mechanical resonance serves as a carrier wav of sorts for physical sensation and control. It emanates from the midline spine and from there entrains vibrations in the limbs and periphery. It runs the body from the spinal cord outward.

The brain’s self-tuning and self-calibration abilities, like all tuning and calibration, are amplified by clean, focused data from novel configurations. Data sources well-known as therapeutic include pleasant activities like stretching, exerting, massage, tugging, pushing and caressing. More powerful but less well-known data sources include weird and uncomfortable practices, such as touching a heavy, sharp axe-head against already-painful trigger-points on the skull or bone, thereby inducing a kind of reversible migraine sensation. (In this practice of ultra-grounding, the object’s heaviness provides the brain with a solid, steady “grounding” reference signal across frequencies into the ultrasonic, data that help realign the brain’s body map to produce joint-opening sensations of “release.”)

The neurohacking explanation for tolerable discomfort and its beneficial results is simple: Discomfort is data you need but don’t want.  Or as some biohackers say, “no pain, no gain.” The neurohacking explanation for intense pleasure is similar: Pleasure rewards progress toward an unlikely state, such as a fully-straight spine or fully-inflated lungs.

In addition to deliberate discomfort, neurohacking relies on positive attitude. Reconfiguring one’s nervous system requires “letting go” of the old configuration. It relies on faith, trust, intimate connection, uncertainty tolerance and the acceptance of discomfort. Having an accepting, even willfully optimistic approach is essential to make neurohacking work. (Imagine the opposite: If your conscious mind believed superpowers were impossible, your unconscious mind would follow suit, making failure a self-fulfilling prophecy. So if you believe neurohacking won’t work, then it won’t… for you.)

Individual Neurohacking

There are countless neurohacking techniques for individuals. An off-the-cuff list based on my biophysics research (on ArXiv.org) includes these potential superpowers: cave echo-orientation, microsecond sound localization, sound healing, spinal ecstasy, thought-reading, contortion, endurance, hyperbalance, microtremor control, breath control, neuromechanical states of grace, auto-hallucination, reversing arthritis, reducing synthetic autism and Moebius motivation. (While there is no space to discuss those here, I would be happy to fill in details, or host a discussion, if Fair Observer readers show sufficient enthusiasm.)

I have used these techniques myself for years and have seen firsthand how well they work on others. But so have many professions and groups; for example, chiropractors and pole dancers.

Chiropractic healing is safer than drugs or surgery. The neuromechanical benefits can be truly life-changing (for me at least), only hobbled by mumbo-jumbo explanations regarding “pinched nerves.” In fact, the chiropractor practice of mechanically adjusting and realigning the spine de-wrinkles and de-kinks the brain’s data map, its virtual look-up table connecting neurons to muscles. That means that the pops and clicks you feel in joints are not just “bubbles in synovial fluid,” but specifically result from instantaneous transitions in the data map. Good chiropractors understand not only how to realign spines — compression, tension, torsion, myofascial pressure, thermal cycling — but understand the neuromuscular releases and the metabolic/hormonal/emotional relief that realignment brings.

My favorite hyper-athletes — pole dancers — are the nicest people ever. Their studios and stages are among the only happy places in the otherwise miserable Silicon Valley. Because humans evolved as a social, tree-climbing species, and a pole acts like an ideal hand-sized branch, a pole studio is a perfect paleo playground. Pole dancers gather in skimpy clothes to twist, pry and dangle their bodies from every joint in every position, incorporating every combination of angle, exertion, strength and pain imaginable. They yelp, gasp, show off and cheer each other on. All that social tugging and twisting improves their spines and lives. If you don’t believe it, ask someone whose life was changed by a pole.

After chiropractic touch and pole practice, the simplest neurohacking technique is whole-body ultra-grounding. This resets the brain’s motor map by pressing heavy fixed points against multiple bony prominences at once, and perhaps even connecting the points by lightweight (e.g., carbon fiber) conduits. One possible result is symmetric spinal health syndrome, reversing aches and stiffness even in the arthritic spine of a middle-aged man like myself.

Pro-Social Neurohacking

Paleo humans lived in hyper-functional teams, not as rugged individualists. Homo sapiens are the most intricately social animals on the planet. Our nervous systems evolved to cooperate and collaborate full-time and to reassure and heal each other through touch. Intimate, continuous, subconscious sociability is our greatest native superpower.

As self-vibrating objects, human bodies resonate like wine glasses if you let them. So as a general principle, the most universal neuromechanical “cure” for many mind/body problems is close proximity to caring people. If encouraging humans hear and touch you, then you’ll feel better.  

Neurohacking Teasers

Here is a teasing introduction to some more specific pro-social neurohacking practices.

1: Pre-conscious resonance: Spiritual people sometimes sense a delicious silence in prayer, or in sacred spaces such as temples, mosques, churches or especially Auroville’s Matrimandir. That connection is built from accumulated micro-motions and micro-sounds.

Here’s how small groups can feel that effect: Arrange yourselves symmetrically and comfortably in a peaceful, quiet, distraction-free space, touching skulls as two partners might when lying side-by-side in bed. (Skull-to-skull is the highest-bandwidth neuromechanical connection.) Once so arranged, then rest, doing and saying nothing, just breathing, for at least 15 minutes. If both (all) of you intend to create and appreciate the silent resonant connection, then you will. 

2: Physic healing: If “psychic healing” is hands-off, then “physic healing” is hands-on. For millions of years, our species and their ancestors used hands-on touch to make companions feel better. The trick is for two people to collaborate on focused discomfort, as with trigger-point therapy, in the service of realigning the receiver’s motor map. With a common intention to heal, both parties focus on the sore spot — with the healer pressing in deliberately and attentively with a fingertip or even a semi-sharp object like a stone, a spoon-handle or a healing crystal, and the receiver mentally pressing out at the same spot. After five or 10 minutes, upon release the receiver is likely to feel calmer, with more relaxed muscles.

3: Self-scaling meta-collaboration: If people enjoy something enough, they will share it. Then the recipients will share it and it will self-scale, spreading exponentially all by itself. (Marketers know this trick, unfortunately.) In a neutral environment, coherence among humans self-replicates as inevitably as crystallization, auto-catalysis or resonant convergence, so that human biorhythms synchronize as naturally as pendulum clocks on a table. If the people also enjoy fostering collaboration, their enthusiasm will catalyze yet more collaboration (i.e., collaboration about collaboration, or meta-collaboration). In the right hands, that could change the world.

For example, the acting-inspired method called “improv,” which practices uncertainty-tolerance and collaboration by default, has already jumped from the stage into offices and boardrooms. When operating in close proximity, especially with reciprocal touch, such real-time collaboration techniques hone interpersonal sensitivity and trust. Pairs and groups become hyper-collaborators, interacting as smoothly as the best military, athletic or dance teams, while also knowing exactly how and why it works so well.  

Neuromechanical coupling techniques can underlie theoretically-optimal discussion and negotiation formats. Furthermore, they often induce experiences that answer questions such as: How can I resonate? How does my mind work? Can human skin feel delicious? Can group vibrations unite us?

4: Self-scaling chronic pleasure: If people can have chronic pain, they can have chronic pleasure. Back in paleo times, chronic pleasure was likely as normal as purring in cats. Even today, spiritual and yogic types experience it. The trick is to resonantly co-activate the same pleasure centers in two or more people. For example, if two people both enjoy relaxing and stretching the muscles of the head, then the skull-touching technique above could provide a simultaneous spinal ecstasy which regular practice might make as effortless as singing. Ask a yoga expert how it works, and why they want to share it with you. If you taste it, you may want to share it too.

Superpowers and Super-Responsibilities

Because these techniques are built in our biology, they have been discovered and rediscovered over millennia throughout the world. But as a general rule, the most potent of them (which are also the cheapest and easiest) undermine established power structures, so that over time the public-facing versions become de-fanged, misinterpreted and diluted. Meanwhile, the purest versions stay secret.

Biophysics and information theory point to easy-to-use versions and render them in the easy-to-discuss language of technology. That language, though, brings a clear warning: you can’t cheat mother nature. Just like there is no free energy, there is also no free resonance. Elementary principles of data topology impose an ironclad law of symmetry:  Techniques that rely on the symmetric resonance of human beings will underperform at best, and cause long-term damage at worst if invoked or incentivized to break that symmetry.

Neuromechanically, all humans are created equal, even invisible users and enemies. Introducing inequality or exploitation into resonance will damage the participants and come to haunt whoever started it.

So stay safe, and enjoy your fellow creatures and yourself.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post White Hat Neurohacking for Paleo Superpowers appeared first on Fair Observer.

If we described this same situation for a computer, we would say the computer is infected with something and it doesn’t matter what. Once you know a computer isn’t computing right — whether the problem is a bad disk, viruses, malware, spyware, corrupt memory or poor wiring — you need to get it back to a known safe state. At the very least a reboot, at worst a clean reinstall of its most basic operating system. The problem is that once you can’t trust your own operating system, you can’t trust anything it does. Period. The only recourse is a return to known safe ground.

People have had this problem since The Fall and have solved it with the same solution. It turns out rebooting the nervous system is what yoga, Pilates, Feldenkrais, climbing, pole dance, tantric meditation, chiropractic healing and a zillion other body-awareness practices have been providing such organic reboots for years, if not millennia. And there is an excellent chance their tribal forebears spent even more time moving in even more fun and effective ways, all the way back to the Paleo Garden of Eden.

So, these modern practices are reviving sensorimotor self-awareness, aka body-wisdom, which is the natural birthright of any vertebrate, especially a social biped. By one means or another, those practices focus both sensory attention and muscular intention on the very midline of the spine, and as a general rule, the more minutely and symmetrically you can control your spinal and breathing muscles, the better your body’s motor-architecture works.

The spine is the center of absolutely everything important about what brains do, so if you can optimize that particular string of bones and that particular squeezing cylinder independently of everything else, including the limbs and jaw, you’ve pretty much reset your motor architecture, and thus your cognitive and perceptual architecture along with it.

Reboot Your Spine

In this delightfully reductionist view, improving your life all comes down to how you feel and move your spine. Without burdening you too much about my own past (yet), I’ve spent the last several years trying to undo lifelong arthritis and virtual scoliosis, in order to feel my spine the way dancers and yogis do. It’s working, which has been wonderful for me in tons of ways. (Save that I’ve become more forgetful, which is most easily explained by the fact that a continuous-control spinal architecture isn’t supposed to store anything anyway. Archiving is for slower architectural layers.)

I expect to spin out more detail later, but for now, let’s end with a weird trick to reinvigorate whatever practice you currently have. See how your body reacts the way I expect (I swear by this technique myself, and find it quite addicting).

Try this: press your incisors against an outward (convex) wall corner or dance pole. Yes, really, push the notch between your two top front teeth gently against the most solid object you can find. Your face will look zombie-ish. It will feel ridiculous, maybe even uncomfortable.

This may be the first time in your life the bone of your skull has been truly connected and grounded, in both the DC and AC senses, through direct hard contact with another solid object. That lock-in gives the muscles of your neck something to work with, and to work against. So, stand as still as you can that way for a couple minutes.

I predict you will experience at least one of the following symptoms of motor-map change: 1) sudden new sensations in unfamiliar zones of muscle or tendon inside of your neck, cheekbones or “brain”; 2) a sudden sound inside you like a click, pop, clunk, squish, rip, etc.; 3) ringing in your ears or skull; 4) a sudden sense of calmness; 5) your neck or back moves more fluidly; 6) your balance shifts.

If this exercise doesn’t teach you something about your spine, you now have a great reason not to read any further.

Enjoy rebooting your spine.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post How to Reboot an Infected Nervous System appeared first on Fair Observer.

I came to data science after a job at Bell Labs, a Caltech Physics Ph.D. and a postdoc at the National Institutes of Health math research branch. I worked at one tech startup after another as a coder and software architect, first calling myself a “specialist in statistical algorithms,” and later chief algorithm officer, while still writing my own queries and code in real languages like Java, SQL and Python — not Matlab or Mathematica. I made a couple big splashes, and the last two startups were acquired. Those “exits” bought me time to work on cooler stuff.

In retrospect, I was probably destined for data science. I grew up in Silicon Valley, in Menlo Park. Learning to program BASIC at age 9 on an old-school teletype with an acoustic modem, tracing down nano-amp current-leaks in homemade circuit boards, measuring atomic nuclei as a laser-jock at Bell Labs, finding statistical gold in neural spike-trains at Caltech — I was always gathering data and making sense of it myself.

From this physics/brain/data perspective I see the sword of technology cuts both ways. Information theory tells us how fragile brains are, and Big Data tells us effective ways to exploit that sensitivity in grabbing human attention. The problem is, attentional economies are zero-sum: Every time my app captures attention or influences behavior, some live human at the other end loses focus or autonomy. Yes, algorithms can influence nervous systems, but it’s not fair, and bad for them. That’s the dilemma I want us data scientists to solve.

We Ruled Tech

I was the child of two brilliant nerds, and the older brother of one. Dad was a nuclear physicist, mom too for a while, before becoming a reporter and environmentalist. My kid brother Ed filed a corporate patent in high school, inventing a way to measure hundreds of sensors with three wires. With me he was a brilliant co-conspirator, collaborator and technical colleague. Our parents gave Ed and me a lot of help and a lot of freedom, so we rode bikes everywhere, bought old radios to fix at garage sales, and climbed trees.

Silicon Valley wasn’t called Silicon Valley then. Santa Clara and Fremont were mostly orchards. Start-ups and stock options and venture capital weren’t a thing yet. Life was more three-dimensional: We built things with our hands, bought from surplus stores (not screens), rode actual bikes on real asphalt, and were unreachable unless our parents knew whose house to call. Tech was rare: long-distance calls were expensive, no answering machines, only a couple TV channels (none on Sunday morning except “Agriculture USA” out of Nebraska), no cable, no internet, no Google, nothing wireless except walkie-talkies. It was easier to work on major projects without distraction. What was fun about making TV jammers, “librarian tormentors,” blinking tie clips and such was actually making them. We had to select the transistors, read resistor color-codes, make our own circuit boards and measure voltages and currents all day long, with analog voltmeters and a 50-pound 1949 Tektronix 512 vacuum-tube oscilloscope with a small round green screen (bandwidth limit 1 MHz). We took and analyzed our own data on the fly, and when our circuits finally worked, it felt like we had beaten Mother Nature.

Back then we ruled tech, it didn’t rule us. You would build a gadget to do something cool and simple, and it did. No software, no dependencies — just wires and voltages. For example, Ed’s and my piece de resistance was hacking the public-address system at Menlo-Atherton High School. This was a perfect “MacGyver” project made from a cassette-tape player hidden under the eaves, two wires from it covertly spliced into the amplifier’s co-ax cable, and a remote on-switch dropped down a drain pipe for access from the hall below.

We had one shot, and it worked: Our bootleg announcement canceling final exams aired during the second period on the last day of classes my sophomore year. That technology was analog, simple and do-it-yourself. But with digital tech today, the knowledge-to-complexity ratio of man vs. machine has been inverted, and you buy it instead of building it yourself. Now tech can understand you, it can advise you, it can anticipate you and it can trick you. For these abilities, data scientists can take credit.

Back then, data science wasn’t called “data science” either. I called myself a “specialist in statistical algorithms” when I first returned to the valley. There weren’t billboards up and down Bayshore Freeway recruiting machine learning and data science specialists, like now. Then, the job made you one of the few people in the building who actually knew what’s going on. You run the queries, you vet the data, you find the trends and correlations, you build the predictive models, you live and die by the math, and you have the CEO’s ear in ways marketing guys never can. If data is the lifeblood of a company, then a data scientist is an oracle.

Data Oracles

Of course, people don’t always listen to oracles, even if they should. Execs see patterns in random noise, or fail to believe statistics. One CEO told me to lie to his investors (I didn’t). Several ignored proof of crippling product problems; more than once I was the messenger who got shot. Of course, the customer needs take priority. Of course, deep architectures take too long to build. Of course, the laws of information processing can’t answer everything, but the answers they do give are always right. (“Ye canna change the laws of mathematics, Captain!”)

This is where our collective faith in mathematics can help us solve our dilemma. The most important principle I internalized in 20 years of data science, from my first successful commercial algorithm (video car detection) through my most impactful (the PreFix debugger that saved Microsoft) and most elaborate (an auto-bidder against Google’s AdWords “auction”), is dimensionality reduction. In information-limited scenarios — which means almost always — raw data should be fit as gracefully as possible to low-dimensional continuous models.

For example, the algorithmic trick called singular value decomposition (SVD) transforms one high-dimensional vector into another by going through a narrow, low-dimensional chokepoint. The narrower the choke-point, the better the signal-to-noise ratio and the better the answers. It’s kind of like Occam’s razor: The best models are the most compact. Dimensionality-reduction gets much more complicated when the low-dimensional data-manifold is curved or variable, but the basic idea to wring out noise by judicious compression is essential.

Ideally you know the structure you’re looking for in advance, like “assuming” a day has 24 hours or a week has seven days. Never, ever use data to relearn things you know in other ways — that’s a waste of data. For example, MRI machines know in advance you exist in three dimensions, as a prior assumption hardwired in place before scanning data even arrives. Such prior assumptions aren’t cheating or laziness, they’re mathematically essential to get anywhere with limited data. It’s called Bayes Theorem. I first heard it evangelized 25 years ago at Caltech, and now it’s common currency.

If you’re with me so far, you already have the keys to understanding the brain and how to live. That’s the cool project I’ve been working on the last couple years, with my partner Criscillia. Here are the results in three very compressed paragraphs. They are justified at length in this peer-reviewed article, “Sensory Metrics of Neuromechanical Trust.”

Brains Are 3D

All brains evolved to map 3D space, assembling spatial maps from discontinuous pulses sent by distributed sensors. Doesn’t matter if it’s a visual map from retinal pulses, or a proprioceptive map from mechanoreceptor pulses, in both cases the data is high-dimensional and discontinuous, yet must represent continuous 3D space. That’s a functional definition of the technology called real-time tomography (like MRI), a very data-hungry and processing-hungry operation. 

The conclusion that brains are 3D simulation engines seems obvious in hindsight, but in one stroke it promotes raw, real-time sensorimotor experience as the highest, purest function of a brain, and demotes anything quantized. Memory, language, categories, decisions and cognition are all coarse, low-bandwidth hacks, ill-suited to the exquisitely speedy circuitry they run on.

We did not evolve to “think” — we evolved to move, sense and feel, which is still our primary activity even if we’re oblivious. Our minds are actually continuous, unified and far more powerful than we’ve been taught. I’m sharing these insights with you because I want you to understand how our minds work and use that knowledge to begin healing the world.

Natural Inputs Are Good, Artificial Ones Bad

Look around you: at your fingernails, the room, beyond the window. Do the numbers: using an HDMI pixel-pitch of 0.2mm as a benchmark, your visual field exhibits teravoxel resolution with predictive latency at zero and sub-millisecond phase precision, fed by only a million pulses per second, i.e. about a megabyte of input decompressed millions-fold into a vision far surpassing anything Virtual Reality can even dream about.

Whatever magnificent engine is synthesizing that real time, hyper-resolution, hyper-consistent image from a few photons through two tiny pupil-holes, the self-tuning strategies of that engine evolved for fractal, continuous, multi-sensory, interactive inputs. Think trees and turbulence, not discontinuous images, events or words. Evolution hyper-optimized brains not just for 3D space in general, but for specific continuous patterns found in nature.

That is the statistical contract and informational nutrition each brain needs. As one might expect, such a high-performance system doesn’t do well when most of its data arrives in the wrong format. Digital inputs deviate from the natural contract in every possible way: They alternate smoothness with discontinuity, they fracture sensory input, they arrive on flat screens, they teleport through space and time and they are specially sculpted to catch our eyes and hold our interest. Technology is neither natural nor random — it is so sophisticated that it can captivate and even hack our brains.

Go Back to Basics

Brains work fine with the right input. You’re a vertebrate, so your most important systems lie along your midline — swallowing, breathing, reproduction. Learn to feel and flex your spine with yoga, Pilates, dance or Feldenkrais. Go for high-entropy grace and flexibility, not low-entropy reps and cardio. Go “forest bathing” in quiet and natural places with trees, vistas, wind or water. When you can, be close to people in proximity, ideally without remote distractions, and soak up the micro-expressions and nano-gestures of human resonance.

Use those nonverbal channels at work as much as possible. When you must, use digital channels, respect their glitches, biases and limited sensory bandwidth. Don’t expect low-latency replies, assume misunderstandings are innocent, don’t do emotions via text. Mobile is better than text, landline better than mobile, video better than only audio, but proximity still beats all, million-fold.

The tragedy of technological damage is best explained not in the language of capitalism, materialism, civilization, human biology or even carbon-based life. The most efficient language is mathematics, and it describes the inevitable collision between creatures’ information-foraging habits and the natural results of their material productivity. We make things we find attractive, and now that’s all we see. This could happen anywhere in the universe.

The triumph of the data scientist is that we can understand our minds as ultra-high-performance representational engines. The tragedy of the data scientist is twofold. First, doing computer work damages our own sensory needs. We must sit down indoors for hours, stare at screens, communicate with text and think through code and numbers.

Second, our profession damages the outside world when it manipulates people by aggregating revenue from micro-thefts of human attention and autonomy. Worse, the results turn children into addicts and tip elections. We, as data scientists, are both blessed and cursed: We will be the first to know what humankind is made of and the first to offer help, but also the first to understand our crimes. Let us apply our brains to solve them.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Triumph and Tragedy of the Data Scientist appeared first on Fair Observer.

Put another way, if a sensitive, world-acclaimed innovator denounces his industry and its technology for undermining human dignity and brain function, something big is up. Who could be more qualified than a world expert — with loads of experience and no incentive to fib — to call the alarm about widespread technological damage?

Young isn’t the first to denounce digital and acclaim analog. Legions of self-proclaimed audiophiles have lamented the loss of vinyl LPs since digital CDs first appeared in the 1970s. Likewise, legions of people who grew up talking for hours on old-fashioned analog telephones hate talking on digital cellphones now. For decades, there has been a deep-set conflict between those who claim analog has some ineffable “presence” missing in digital versus those with technical know-how who can explain how analog and digital actually work. In essence, the producers of digital tech claim it is flawless, while the most sensitive consumers claim it is awful. They can’t both be right.

There is a truism that technology often fails to live up to its promise. But utterly failing at its central task is something else. Car buyers don’t claim cars fail to move and shoe wearers don’t claim shoes cut their feet. Yet consumers and especially producers of the most spiritual and emotional human communication — music — routinely say digitization destroys emotion. For those to whom emotion matters, this problem is bigger than cars or shoes. Science needs to get emotion right, and sound is in the way.

What Ordinary People Say

Since we’re talking about everybody’s emotions, not just Neil Young’s, let’s look at the spectrum of reaction to his interview. About half of commenters agreed with him, often saying lyrical things like, “In analog music, you can hear ‘subtle differences,’ so voices and instruments ‘sound more natural,’ even ‘glorious,’ with more ‘color,  ‘depth,’ and ‘beauty.’” Other readers wrote, “Just because one cannot hear or discern the missing info doesn’t mean it does not exist” and that poor “audio quality leads to ‘listener fatigue.’”

The anti-Neil Young comments don’t sound as much like music appreciation. Rather, they have the snide sound of an annoying know-it-all engineer. To wit: “Digital recordings are better and hold more information,” “Fidelity on a basic CD is ‘altogether superior’ to any vinyl LP,” and the “Nyquist theorem proves that analog information is perfectly preserved in digital form, and naysayers ‘disagree with math and science.’”

While such comments can be annoying, they do invoke a kind of truth sacred to technologists: Certain kinds of math and science are objectively true. You can’t ignore physics and stay intellectually legitimate. 

Of course, if you invoke the wrong law of physics, your ideas might be useless, or worse. In the case of sound and sound reproduction, there are two laws of nature at work, the first of which is the Nyquist Theorem mentioned above. 

Overall, the comments cluster into complementary philosophies, which might be called theory vs. experiment.” They raise the deepest issues possible pertaining to interpreting reality: How much should we trust the laws of nature versus how much should we trust our own sensory experience? Of course, people who notice differences in sonic texture will say so, as the reader comments above refer to the experiential data of  “color,” “depth” and such. But other people, those who know certain laws of physics always apply, will assert the primacy of natural law bluntly, as one might assert the self-evidence of 2+2=4.

The unfortunate asymmetry of such discussions is that while one individual sensory experience doesn’t speak to anyone else’s, and thus doesn’t insult them, the reverse isn’t true. Invoking a law of nature that says certain experiences can’t possibly exist does, in fact, insult anyone having that experience. In such discussions, the “scientists,” in effect, call the “musicians” stupid, insensitive and/or hallucinating.

It’s not just musicians who don’t want to be told by scientists that their experiences are hallucinations; it’s even other scientists. For instance, neuroscientists know their results must accord with the laws of physics, but the reverse isn’t true. Physics doesn’t have to “obey” neuroscience laws, because there are no neuroscience laws. 

Neuroscience is an experimental discipline, 150 years of accumulated interesting results, with very little agreement beyond the usual mantra that “more research is necessary.”  In the hierarchy by which abstract theory intersects with specific experiments, math trumps physics, physics trumps chemistry, chemistry trumps biology and biology trumps psychology. So even inside science, as a general rule, established laws of math and nature trump experimental results. 

In that sense, the discussion between Young and his detractors is truly scientific. And, in that sense, science can resolve it. But first, a little history.

The Laws of Sound and Math

While Thomas Edison is credited with inventing both movies and phonographs, the two techniques couldn’t be more different. Movie technology freeze-frames analog continuous-time into discrete, discontinuous snapshots. In film, analog 3D life is compressed into separate analog 2D pictures. Time, on the other hand, is chopped up ( i.e., digitized). Film captures individual photographs (i.e., two-dimensional gray-scale (analog) images spaced a few dozen milliseconds apart).

Contrast those intermittent photographs with phonographs, in which time is continuous. Phonographs, the ancestors of vinyl LPs, originally scratched tiny but continuous sound vibrations directly, mechanically, onto a cylinder of tin foil, then replayed them in reverse, with a horn-shaped “loudspeaker” — like the old Victrola players listened to by dogs in the ads (above the slogan, “His Master’s Voice,” because dogs actually could recognize people in those recordings). The cylinders had only one groove, hence they had no stereo and no possible representation of space. But they recorded enough pure, continuous analog time to evoke instant recognition, which is the sweet elixir of the nervous system for humans and animals alike.

During the 20th century, analog sound recording vaulted from foil cylinders to plastic platters, ever larger and spinning ever slower as technology improved, at 78, 45 or ultimately 33 1/3 revolutions per minute (33 1/3, the slowest speed, was called “long-playing,” or LP). At roughly the same time, analog sound transmission wrapped the world in two other ways.

The continuous-wave analog radio (first AM and then FM), invented first by Nikola Tesla and popularized by Guglielmo Marconi, mimicked the abilities and peculiarities of analog recording with its tubes, crystals and resonators. While audio recording moved sound across time, radio moved it across space and could have an enormous impact when blanketing a country. Orson Welles’ voice and genius — on the radio — took less than an hour to convince America we were under Martian attack. Franklin D. Roosevelt and Winston Churchill’s voices, also on radio, inspired citizens in time of war. So did Adolf Hitler’s and Benito Mussolini’s. Broadcast voices move whole peoples.

Analog emotional resonance also worked through phones. The old-school “landline” phones (aka, the plain old telephone service, or POTS), connected two people in real-time through a pair of dedicated, analog copper wires. Those of us who grew up with POTS phones happily spent hours on them because the connection was so good: no dropping, no gargling, no lost words, no weird sounds or silences. Ask anyone who lived that to confirm it. Talking on POTS phones was like having your conversational partner whisper in your ear. 

Here’s one bit of historical trivia: Even the earliest connections in the 1920s were so continuously lifelike that musicians who had access to shared “party” lines would often practice music over the phone, rather than travel to each other’s houses. But that practice disrupted paid phone traffic. Jam-sessions and day-long conversations over party lines eventually became so widespread that the telephone company, Ma Bell, had to run a campaign to discourage them, like this amusing promotional message from the 1940s: “Bobby Gets Hep.”

Even before the invention of stereo, the decades-long experience optimizing monaural sound in all its forms taught technologists a lot about human hearing. They discovered that our ears can’t hear at all above 20,000 Hz (back-and-forth cycles per second), so they knew not to waste any effort at all above that threshold. They also discovered that we only really need frequencies below about 3000 Hz to understand spoken speech, that the consonants have much higher frequencies than the vowels, and that consonants can never be dispensed with (while vowels can, as in whispering).

Then stereo arrived, enabled by the singular invention of having the same needle move in two directions at once, 90 degrees apart, to carry two independent channels. Because individual vibrations from the same needle in the same groove stayed in stereo synchrony at the micro-second level, someone listening to a high-fidelity player could actually hear where in space the sound came from, not just what object made the sound.

After stereo, the next innovations were digital ones: how to digitize sound (analog-to-digital conversion, or ADC), how to reconstitute it for recognition (digital-to-analog, or DAC), and later how to most cost-effectively “compress” the sound in between for storage and transmission. Engineers finally learned how to throw large parts of the signal away without anyone noticing. There were thus new choices about new informational concepts like bandwidth, frequency limits, bit-rates, sampling rates, encoding depth and, most crucially, deciding what is “signal” vs. what is “noise.” Making new choices required new principles.

Based on the existing, already-deep understanding of single-channel “mono” sound, the founding principle of compression became fidelity: to preserve the best possible rendition of sound consistent with our ears’ limits, in the service of better recognition, identification and description of the source. Who is making the sound? What are they saying or singing? What do they mean? 

Of course, balancing bandwidth vs. fidelity required engineering tradeoffs, based on needs and costs. They did so by respecting the old laws of math and physics, plus the new “laws” of information. These laws, discovered about this time by mathematician Claude Shannon, turned the wooly concept of “information” into a quantified technological term by defining bits, bandwidth, signal and noise in terms of analog statistical probabilities. Weirdly, while Shannon’s equations are central to the discrete bits and messages of digital communication, the equations themselves are analog, crossing the divide between continuous nature and manmade messages plucked out of nature.  

Another law, the Nyquist Theorem, was more human-centered. People already knew from experience and experiment that high-frequency signals carry more information than low-frequency ones. This is why speech needs consonants more than vowels, and why hi-fi recordings sound more realistic than low-fi ones. Shannon knew there were deep mathematical reasons for that experience and, ultimately, proved a theorem showing that if you sample signals at a regular frequency f, the maximum possible information transmission I (in bits) is given by the equation: I <= f/2.

This is the Nyquist Theorem, and it implies that digital sampling can be perfect in certain ways. Shannon’s proof of was named after Harry Nyquist, who had decades earlier proved part of it. In particular, the Nyquist Theorem revealed that a human ear, whose upper frequency seems to be capped at 20,000 Hz, could not possibly use signals sampled above 40,000 Hz. (This is why CDs and WAV files sample at 44 kHz, slightly beyond that limit). The fact that individual human ears can’t hear above that range — while bats can — is the warrant behind the claim that a sample rate up to 88kHz is useless unless you’re a bat.

A Triumph of Technology

Back in the 1970s, as a teenager, I fancied myself a nerdy audiophile. Half my spending money went to flat-frequency-response headphones and fancy amplifiers with high linearity, low noise and wide dynamic range. Even the earliest CDs brought amazing improvements in all those measures. So I tossed my record collection. I knew, based on our human 20,000 Hz maximum, that digital recording was objectively better, if not truly perfect.

Actually, it’s not quite that simple. Headphones and earbuds, being smaller and quieter, do indeed give better sound per dollar, but they move with your head and remove the bass notes from your skin. Digital CDs — being digitized but not otherwise compressed — still sounded nearly perfect to me, but not so MP3s, AACs and, later, streaming, all of which made audio more portable and convenient but at some cost. It is very clear to both my senses and my intellect that too much compression really does damage sound quality — no one disagrees with that part.

So, I grew up experiencing two technology transitions: from analog LPs and phones to digital CDs and voice-over-internet (VoIP), which sounded fine, then from those to highly-compressed MP3s and cellphones, which definitely sounded worse.

Yet even the bad-sounding conveniences won in the marketplace, so much so that now most of the music and sound we consume is both digitized and compressed. Clearly, having 5,000 songs in your pocket, as the first iPod advertised, is collectively more attractive than having a few really good songs at home on a turntable. The triumph of science was to invent and deploy all those technologies, so people could choose between fast/convenient/coarse (like iPods) vs. slow/inconvenient/refined (like CDs).

The Paradox of Musicians vs. Engineers

The vast majority of low-quality sound, whether on iPods or cellphones, comes from over-compression. But the age-old debate revived by Neil Young isn’t about over-compressed music like streaming, but about uncompressed digital music like CDs.  That’s the mystery: Why do engineers think it is perfect while musicians think it is awful?

That’s a truly scientific paradox, involving scientists themselves. Why do Young and many, many musicians and sound artists insist, in their full professional capacity, that even the best digital recordings damage presence and emotional content? This standoff pits sensitive listeners who can’t explain their perceptions scientifically against actual scientists, who, in spite of insensitive ears, claim those perceptions are physically and mathematically impossible. What if the scientists missed something?

The Mystery of Missing Microtime

My own scientific career might shed some light on this. As a kid, I actually enjoyed solving the infamous physics “word problems” that intimidated most of my peers. I cranked tirelessly not just on my high school’s “problem of the month,” but on constructing (analog) electronic circuits like TV jammers, blinking tie-clips, librarian tormentors and wireless bugs. (My only digital project was a clock radio: I etched the copper circuit board, soldered in the transistors and integrated circuit, and mounted it all in a wood cigar box.)

My do-it-myself attitude lasted through graduate school, where I stumbled onto a deep mystery about neurons in the brain. It turns out that neurons care about time-differences a thousand times tinier and faster than neuroscientists thought.

The reason is simple: Information content goes up with timing precision. If brains are to process information efficiently, they must be sensitive at least to milliseconds, if not to microseconds. To discover on my own that neuroscience had missed the mystery, microtime reminded me both of nature’s delicate machinery and of the narrowmindedness hobbling publish-or-perish research. I saw my own field of science miss something huge.

After graduate school and a post-doctoral fellowship, I returned from academia to my boyhood stomping ground in Silicon Valley. There, I spent 15 years working as a “tech turnaround artist,” meaning I either saved hopeless technology projects or at least understood why they couldn’t be saved. In facing challenges that other strong professionals had not resolved, I re-learned the principles of solving very, very hard problems — principles I first learned from those physics word-problems in high school. The most basic principle is common to puzzles of all types: What clues haven’t we used yet? In particular, is there another law of nature we forgot that might apply? 

“Where” Beats “What” in Hearing

At the beginning of this article, I mentioned that sound recording involved two laws of nature, with the Nyquist Theorem being one of them. The other is the speed of sound in air: speed of sound = 330 meters/second = 1 mm in 3 microseconds.

Why might this matter? The science of sound recording got in its present mess by sticking with what it was good at, rather than what it needed to know. Science was good at dealing with one variable at a time, a single monaural sound channel, via needles, wires, speakers and, ultimately, Shannon and Nyquist. At that time, science didn’t know what brains do, so it skipped that part.

A more brain-centered, human-centered approach to sound recognizes that the main task of a brain is to manage the vibrations of a physical, three-dimensional body. Part of that task involves making sense of vibrations outside the body, both in recognizing what thing made a sound and, more especially, inferring where the sound came from. 

Here’s why: Imagine you’re alone and frightened in the woods, in the dark, with threats nearby. Suddenly, crack! A twig snaps close by. At that moment, which would matter more to you: where the sound came from or what type of wood the twig was made of?

The best way to locate sounds is to use the whole body — ears, skull, skin, even guts — since the entire body contains vibration sensors. The brain’s main job is making sense of vibrations throughout the body, eyeballs to toes to eardrums, all consistent, all at once. One single vibratory image unified from skin and ears.

Headphones and earbuds fracture that unified sensory experience. Normally, your skin still absorbs vibrations from the outside, consistent with what you see. But with headphones covering them, your ears process entirely different signals injected directly into the perceptual space inside the head. That new sound image bypasses skin and eyes, while still being superimposed in front of you in space, on top of real sound sources. That physical impossibility sounds interesting, but it is the deepest kind of hack a brain can suffer, short of drugs. Consuming separate, inconsistent sensory streams that create competing maps of space violates a brain’s design.

For localizing sound, though, the skin is merely helpful, because the ears do pretty well on their own. Your ears (and brain) deduce the location of a sound by using the microsecond difference in arrival times of soundwaves at two ears. (Acoustic scientists call this discrepancy the inter-aural timing difference. Using the sound-speed equation above, they might enjoy the “word-problem” of calculating how a centimeter-level separation you can hear translates into the microtime difference your ears make use of).

I wrote my PhD thesis on neural pulses, so I know they last about a millisecond each. That’s a thousand microseconds, hundreds of times longer than the few microseconds we need for sound location. On the face of it, neural pulses seem too clunky and bulky to carry such tiny, delicate messages.

Fortunately for us, neurons do not encode sound like CDs do. Digital recording samples the sonic world every 23 microseconds, whether or not a sound is there. On the other hand, each neuron waits for a soundwave to arrive and then fires a single pulse. And all the neurons do that. So a soundwave striking lots of neurons at once will fire lots of pulses at exactly the same time. That synchronous volley arrives at the brain, which infers from the volley the time the original soundwave arrived, if necessary down to the microsecond level.

How does all this translate into the language of technology? The guiding principle of a nervous system is to record only a single bit of amplitude at the exact time of arrival.  Since amplitudes are fixed, all the information is in the timing. 

On the other hand, the guiding principle of digitization is to record variable amplitudes at fixed times. For example, sampling with 24-bit amplitude resolution, every 23 microseconds (44 kHz). Since sample times are fixed, all the information is in the amplitude.

So unlike digital recorders, nervous systems care a lot about microtime, both in how they detect signals and how they interpret them. And the numbers really matter: Even the best CDs can only resolve time down to 23 microseconds, while our nervous systems need at least 10 times better resolution, in the neighborhood of two to three microseconds. In crass amplitude terms, that missing microtime resolution seems like “only” tiny percentage points. However, it carries a whopping 90% of the resolution information the nervous system cares about. We need that microtime to hear the presence and depth of sounds outside us and to sense others’ emotions inside us. 

The old analog technologies, LPs and POTs phones, preserve that necessary 90%. Digitization destroys it. Neil Young was right.

Easy Tests

This being science, all of it is testable. The most dramatic measurements of microtime precision will be found when testing people accustomed to using sound to locate things — that is, in the congenitally blind, especially those who live in quiet, natural places, where tiny distinctions are easier to hear. In general, the hearing of those people will likely represent the most accurate human auditory perception possible.

So, we should test how well they hear locations in space, in ideal circumstances — say, tracking airplanes flying overhead from a quiet, open field (with skin exposed), or distinguishing clicks a few centimeters apart at various distances. Let them compare LPs against CDs and streaming media. Let them compare POTS phones against VoIP and cellphone calls. Ask them yourself. (And don’t trust Apple or Google to help).

The Future of Microtime Communication

In calling out digital music, Neil Young unknowingly highlighted a global public-health catastrophe caused by artificial sound in general. (And by screens too.)

Of course, people like artificial or artificially-transported sounds. But as with drugs, our nervous systems sometimes like things that are bad for them. Enhanced, interesting, distracting sounds are no exception. And as with sugar, the market makes money giving people what they want right now.

Likewise, people as a species want to talk, or at least used to want to talk, back when real-life proximity and POTS phones let us do it properly. Unfortunately now, due to straightforward but perverse incentives, networks make money by throttling bandwidth through compression, so calls via cellphones are typically low-quality and shorn of emotional resonance. Humans connect poorly through cellphones unless they know each other really well.

The Coming Microtime Technologies

I predict the emergence of three new technologies that could change the world by reconnecting people.

1) Devices that quantify sound the right way. It shouldn’t be hard to create a multi-function “tricorder.” It could measure someone’s sonic environment in all kinds of ways: decibels (min, max, median, average), frequency distribution, suddenness, repetition and any other signal parameters that matter to ears and brains. Better yet, when paired via a data channel with a matching tricorder on the other end of a phone line, it could track sensory metrics of the call itself, such as latency, latency jitter, hotspots and dead spots in pattern-space and (with stereo) 3D reconstruction resolution. This device would provide sensory-nutrition information, akin to the nutrition labels on foods, enabling healthy decisions.

2) Microtime recording and stereo. A video technology called an “event camera” already exists, which uses pulses much like the nervous system does. Audio pulse-tracking could underlie a whole new form of analog recording, tossing amplitude and keeping microtime instead. When that recording scheme is used for stereo, played back through well-placed speakers, listeners will experience the sharpest, fullest 3D sonic field possible short of real live sound.

3) Micropresence = microtime telepresence. Imagine marrying microtime stereo with remote-video “telepresence” for the best interpersonal connection possible over distances. One very good arrangement would be an augmented-reality system (connecting matched rooms) that superimposes your conversation partner’s face consistently and coherently atop your own visual space. Microtime visual cues like micro-expressions will be partly visible even on a 3D face scanned by normal video. When combined with microtime sound properly aligned with the speaker’s mouth and throat, you will experience the most coherent sensori-motor experience possible remotely.

The sooner technology restores the microtime connections that humans need to thrive, the sooner we will thrive again, leaving loneliness behind for good.

The best connection will always be a physical presence and proximity. I expect more “acoustic” music concerts, all-live musicians, no microphones or even hyper-flickering LED illumination. Acoustic dances. Acoustic conferences. It turns out the so-called “emotional resonance” people enjoy together really is a kind of neuromechanical resonance, aided by acoustics and reduced by reproduction. (It’s best experienced in sacred spaces like churches, temples and Auroville’s Matrimandir. Live silence, like live music, will always connect people the way Neil Young hopes.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post How Science Got Sound Wrong appeared first on Fair Observer.

But not all submarines work that way. Some of them listen to their environment silently, emitting no energy and offering no clue of their existence (“silent running”). It’s slow work, and requires constant attention, but you’re much less likely to be attacked, since others may not notice you’re there. As strategic choices, listeners listen, and pingers ping, but only for the most part, because those two strategies are just opposite poles of the general strategy of pinging. Pinging means interfering with the world in order to learn about it. Pinging interferes a lot, listening only a little.

Pinging is best for reorientation, because it’s intermittent —like turning on a room light briefly, to remind yourself how far away the door is, or rocking a dial or a physical object back and forth, to locate the “edges” of its balance to infer where the middle is. Pinging is algorithmically efficient; one burst can illuminate a lot, and dividing the task of sensing into separate output and input phases simplifies computation. Unfortunately, the pinging approach is so efficient that it becomes addictive.

Once you become a pinger, in practical terms it’s hard to go back. For an inveterate pinger (like me), the longer I go without a ping to orient myself, the more uncertain and at sea I feel. It’s hard to wait long enough to gather the long-term data which might ultimately improve my listening skills. So even now, I’m still a pinger.

Listening is mostly used when pings are expensive, as in crowded classrooms and interaction with higher-status people. Listening specializes in highly sensitive, long-duration data acquisition, both during calibration and during actual use — which are often the same thing. Listening best applies to social situations, felt in 3D space, because the body’s physical and emotional resonances can coherently accumulate extended signals from other people. Listeners go more by “feel” than rules.

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My wife is a classic listener, from a family of storytellers who value listening. Her nervous system has always been finely tuned and sensitive, so she could listen well and could anticipate people’s moods. Furthermore, when she was growing up, people who looked like her were supposed to keep their mouths shut; in her grade-school classrooms, even her excellent questions were punished. So she learned to pay close attention to other people, and not to interfere. Now, as an adult, she follows well, goes with the flow and avoids sudden changes. And she became an expert on stories.

I grew up the opposite of her. My internal senses were dull, so I constantly reaffirmed my body’s position in space by wiggling it a little bit (still do). Because I couldn’t feel my own moods much, I couldn’t cue in to others’ either, so I relied on words and rules-of-thumb (as opposed to instincts) to know what I should do and what comes next in social settings. With those sensory deficits, of course I specialized not in understanding people but in physical things outside me. And, like both my parents, I became a physicist. My instinct is not to feel, but to think things through in physical terms.

Perhaps because of that, I became an inveterate pinger. I have sometimes bragged that I asked half the questions in any classroom. (Basically, I was proud of interrupting gracefully, and my teachers thanked me for it). I frequently guess story spoilers, I kick the toilet when it sticks, I fiddle with stuff to make it work. I also crack my knuckles (a kind of inside-ping) and wiggle in my chair instead of sitting still. Because our culture doesn’t mind if well-spoken white men like me ask lots of questions and interfere, my pinging didn’t cause me problems that I knew about.

Now, imagine a typical argument between me and my wife. She wants to vent about her stressful day. I do want to hear, so I keep interrupting to make sure I get details right, which interrupts her flow. Or if, at a critical point in her emotional narrative, I ask a point-of-fact question, she might take it personally. And so on. My pinging disrupts her continuous flow of listening and narrativizing, while her socially-oriented reactions confound the answers I need. She needs to know how things will unfold over time. I need to know how they are now.

Each one of us is using a battle-tested, lifelong cognitive strategy, and both strategies are equally legitimate, but the two strategies are incompatible in certain situations. She needs continuity, while I need to know I haven’t lost the thread. We’re both right.

Pinging vs. listening is an example of breaking down personal styles into informative but value-neutral terms informed by the mathematical theory of information flow. Another example might be physical thinkers vs. social thinkers, which overlaps with pinging vs. listening quite a bit. The key is that it’s much easier to get along with people if you respect their differing styles of gathering information.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Our Personal Styles of Information Gathering appeared first on Fair Observer.

While Cooper made the word “neutral” seem like a loaded challenge, the truth is that “neutral” is as neutral a word as can be. “Neutral” is mathematical and boring because neutrality is a statistical concept, most famously embraced by scientists as a freedom from bias, as in “unbiased data.” Scientists know only unbiased data can be trusted for anything.

Most people assume technology is in fact neutral. Technology is a tool, the thinking goes, and we use tools; they don’t use us. The tool is fixed, and we’re in control. But a tool just lying there doesn’t make it neutral. In fact, if the supposedly neutral tools we use every day, and especially the tools we use to gather and understand data, if those tools weren’t neutral, we might have a problem.  

Fortunately, this is easy to decide, since neutrality simply describes the comparison baseline for detecting bias one way or another. To be neutral to a human evolved for nature, objects must be natural: sticks, stones, animals and such. And that means all stones, not just the very sharpest or prettiest, and especially not stones we’ve specially sharpened or painted by hand. Those might have started in nature, but by selecting them based on certain characteristics, and then changing those characteristics still further, we made the statistical profile completely different. That was the whole point. We don’t want just nature-made stuff. We want tools.

Natural shapes are pretty simple, like rocks, trees, moss or clouds. But there are lots of different ways to be un-natural: extra sharp, extra durable, extra interesting, or extra big or small or strong or hot or bright. And now silicon crystals make things extra fast, and phosphor or germanium screens make tiny colored flickers extra coordinated, like a moving picture. That gives millions of ways to be unnatural, every second.

We like these things, and make lots of them, because they’re unnatural in especially useful or interesting ways. We have lots of them for good reasons. Sometimes what seems good at first becomes bad later on, as with lead waterpipes or smoking tobacco.

Some things please us consciously and damage us slowly and unconsciously, while some things are the other way around. The only guarantee is that all of them exist outside the natural realm of sticks and stones on purpose in ways that matter to us. By construction and by default, technology is absolutely not neutral. Neutrality is actually hard to achieve.

So in this neutral statistical sense, even stone tools aren’t neutral, and they took a million years to evolve. Writing evolved over thousands of years, books over hundreds. Smartphones change every year, their operating systems change every few months, and the numerical algorithms running inside the apps change in milliseconds, with senses more uncanny and reflexes far faster than your own. That amazing “functionality” was optimized by thousands of years of human craft, by hundreds of years of economic organization, and by decades and terabytes of user data processed exactly for the purpose of making your eyes move and your fingers click. That’s as far from neutral as one could imagine.

In fact, that principle is true for any form of technology anywhere, from stone tools and cave paintings to atomic power and virtual reality: it makes you want more. To succeed, a technology has to prove useful somehow, which means it influences human behavior to manufacture more of it.

That’s the acid test of whether any technology shrinks or grows. And that test applies not just to solid manufactured objects that influence people, but to abstractions which do so even more strongly: the laws of mathematics,  physics, legal systems and contracts, economic cooperation and money, medicine, politics and culture. Whether such systems and beliefs are “true” or not, they are certainly capable of influencing human attitudes and behavior. And the more persuasive they are, the less neutral and the more capable of hiding long-term damage.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Is Technology Neutral? appeared first on Fair Observer.

Here’s the gist of both: The human nervous systems evolved to pay attention to and consume natural inputs, not artificial ones. So to feel better, increase your exposure to natural inputs. Because the previous article listed 10 lenses for assessing digital damage — worst last — this article will use the same lenses in the same order to assess natural cures. But at core, they’re still all “nature,” indivisible.

1. Natural Light Counters Blue Screen Glow

As a general principle, animal eyes evolved to use light from the sun, at the times the sun provided it. So, as a general principle, for as much of the day as possible, the light entering your eyes should actually come from the sun, perhaps filtered through clouds, windows or skylights. Direct sunlight reminds your eyes how bright bright can be. Get a little natural light every day to keep your eyes in calibration.

Likewise, rediscover how dark dark can be. Outdoors under a deep, dark, starry sky is best, because you can sense expansiveness along with darkness. But even experiencing the dark inside a tiny room can reset your night vision. In that experiment, no nightlights, power indicators or illuminated clocks.

Remember this: The brightest nighttime white or blue that any animal could ever see in nature was moonlight, tens of thousands of times dimmer than the sun. Because of that, nature decided that our eyes should use blue and white to reset our sense of time (that’s why seeing blue at night damages sleep cycles by resetting circadian rhythms). So every now and then, skip watching screens and use only yellow-orange light from dusk to dawn for cooking and reading. Avoid blue light at night, and see if you sleep and feel better.

2. Making Faces Counters Fixed Focus

Your eyes ought to rove all over, not just focus on the same spot all day long. Prolonged immobility is bad for any muscle-control circuits, especially those controlling the sensitive and intertwined muscles of the eyes, eyebrows, neck, jaw and scalp. To wake them up, look up, look down, roll your eyes, cross your eyes, make faces, wobble your jaw, pop your ears. While you’re at it, yawn, gargle, cough, snort and, in general, produce as many sensations and vibrations in your head and throat as you can. Re-complexify your motor system.

The best place to re-complexify is outdoors, in nature, which helps your sensory system at the same time. Bushes and ferns look like fractal filigree, flying birds and bugs make moving targets, and the wind heaves trees, shakes leaves and tickles follicles all at once for a full-spectrum, multi-sensory experience, better than any TV or VR. Enjoy natural, organic bandwidth.

3. Moving in the Dark Counters Ocularcentrism

Brains evolved to operate the back and front of a body equally well, and to be aware of what’s behind us as well as in front of us. Unfortunately, society has taken such extraordinary advantage of the human visual and hand-manipulations systems that many of us have clenched hands and chests, forward-tipping balance and forward-focused eyes. “Behind” is left behind.

To get back in your body, turn off the lights. Pitch black, so you have to balance by feel instead of sight. Shift the weight on your feet, rock back on your heels so you almost topple over. Stand on your tippy-toes. Twist, walk a bit, bend forward, bend backward. Upright balance, even more than acute vision, is a biped superpower, so when you do it in the dark, as cavemen did, you reboot your primal infrastructure. Of course, be careful not to hurt yourself!

4. Books and Newspapers Counter Smooth/Flat/Shiny

If you have to read, at least read something real, like paper. Paper is better than pixels in many ways. You can touch it, crinkle it, bend it, change the angle of the light. It works great in sunlight. The contrast ratio is amazing, with no glare, no flickering, no pixelation. You can write on it. You can bend the corner and always find that page. The software never fails. Best of all, reading comprehension goes way up when you read on paper. Anyway, people trust what they touch way more than what they see.

5. A Concert Counters Fractured Space-Time

Brains should not multitask. Their key job and core competency is making a single, self-consistent map of their bodies and surroundings. That means one big map of the here and now, without competing little maps of other places, times, events and sounds. Multi-tasking and flitting between digital realms fracture an otherwise continuous sensory experience.

To reintegrate fractured senses, go to a concert. A live concert, real singers on stage, a real audience dancing in front of them. The ideal concert would have no electronic devices, and the music would be pure acoustic: piano, winds, brass, strings, doesn’t matter which. What does matter is that every micro-vibration of sound was produced by a human body and directly transmitted from the surface of the performer’s instrument to the audience’s skin and ears (yes, skin helps hearing). Nothing in between. No interference, artificial delays or distortion from microphones, wires, amplifiers or mixers. Just a few people on stage making sounds, and a lot of people nearby making motions, together creating a physical and Platonic ideal of continuous, reciprocal, high-bandwidth human interaction. Just the social experience nature ordered.

6. VVR-IRL Counters Edge Enhancement and Over Sharpening

Here is a funny mind-game to help you reappreciate the amazing nervous systems we were born with. First, the funny name: VVR-IRL, based on the abbreviation VR, for virtual reality. Virtual reality is an actual, real technology made of metal, plastic and silicon. So if you merely imagine experiencing VR, that would be virtual VR, or VVR. If you do that while looking at the real world (IRL), you’re practicing a kind of meditation you might call VVR-IRL.

Here’s how: Find a natural outdoor place, like a garden or park. Bonus points if it’s visually spectacular in detail, scale or both. As you look at it, imagine you are inspecting the world’s most awesome VR rig. Look closely at a blade of grass: Can you spot any pixelation? Compression artifacts? Uncanny edge-enhanced crispness? Quickly swing your eyes and head from side to side — does the world keep up or lag even a little bit? Does reality feel sideways when you tilt your head? How good is reality, really, by the standards of commercial VR?

All my life I’ve been a resolution junkie, buying the very best headphones, speakers and ultra-sharp displays. But in the spirit of VVR-IRL, I finally realized that no artificial inputs of any kind, from any kind of display or transducer, will ever match the brilliant clear immediacy of my own built-in senses as they are, right now. The ultimate VR is me.

7. Hikes in Nature Counter Over-Attractive and Selected

Suppose the nervous system is meant to see God’s handiwork, not man’s, and meant to move through it. To revive that state of sensory innocence, find someplace uncultivated. Ideally, that would be remote, pure wilderness, like the Alaskan tundra or the Amazon basin, without a single manmade thing even visible, much less anything carefully selected for your viewing pleasure. But even an untended urban vacant lot can remind you how weeds, bugs and birds look and act like on their own, un-cartoonified. Actual nature is always more subtle and interesting than the cute subset you imagined.

8. Duration, Silence and “Siren” Ringtones Fight Sudden Interruptions

People aren’t bothered by ordinary jet planes, but supersonic planes drive us crazy. The reason we don’t use supersonic airliners is that the sudden “sonic boom” triggers people’s natural startle reflex. The slow-rising roar of a jet doesn’t do this. Unexpected surprises can’t help shocking people, especially when one not only hears the boom but feels the impact on the skin. The closer the source of surprise, the more startling.

Society learned this lesson well when warning of public danger. In cases of impending threat — tornados, tsunamis or air raids — most countries now choose not to warn the public the old low-tech way, with bells, drums or cannon fire. While those sounds are plenty loud enough, their suddenness creates surprise and shock and makes it harder to keep the nervous system calm. Instead endangered places, use the slow wail of sirens, whose meaning is ominous but whose sound rises gently.

The same principle applies to sudden rings and beeps in our pockets, which disturb us equally deeply, even though we paid for them. A “ringtone” whose volume rises slowly, like an air-raid siren, would be far gentler on the nervous system. The less threatening the better, like sounds of birds or waves, but any sound that starts off quiet will do.

Better ringtones reduce interruption fatigue but don’t treat it. To make you feel better from the modernity’s ceaseless rain of interruptions, find a way to get away from them. Try silence and digital disconnection for at least an hour. People who manage to go days or weeks report feeling even better. Turn off, unplug, go camping. Get away from it all. Call it prayer, meditation, relaxation, whatever — just give your nervous system a chance to hear itself and its fellows undistracted.

9. Autonomous Motion Fights Persuasive Design

Almost everything we see was created to be seen, which means created to make us think or feel a certain way when we see it. Such persuasive intent is subtle for buildings, clothes and gardens, and grossly potent for slot machines and cellphones. So, of course, we feel lied to all the time because we are lied to. The market’s pinnacle of optimized revenue generation, persuasive technology, now works so well that we’re drenched with addictions, distractions, lies, fakes and scams. The decline in our autonomy is real, and our nervous systems know they’re being gamed.

The cure is autonomous motion. By controlling your own neuro-motor system, you overwrite the helplessness induced by digital life. Try standing up, yawning, taking a walk, stretching — just do something, anything, that feels good. For a heavier dose, try an autonomous-motion practice like “ecstatic dance,” which is a DJ-led communal journey lasting two hours and following three simple rules: no shoes, no talking, no judgment. Move as you want to the music, and watch other people do so too, everyone doing exactly what they want right now. Enjoy walking, jumping or spinning through a kelp-front forest of swaying human stalks. Wordless dance has been a human heritage for a million years, the ideal expression of collective autonomy.

10. Mindful Resonance Counters Socio-Sensory Deprivation

The tragedy of screens is that they make people lonely. They do this by using social “messages” that provide meaning without a nourishing proximity connection. The antidote is the opposite: connection without meaning.

For example, take “mindful resonance” (formerly “resonating mindfulness”), a simple biorhythm synchronization technique invented by a meditation teacher, a literature professor and myself. Two to five people stand close together. They might hold hands, touch backs, press down on shoulders or switch between. These are all techniques for increasing the neuromechanical coupling between people (and hence between their nervous systems). If they’re brave, or familiar, they might even touch heads together, skull to skull, for the highest bandwidth connection. They breathe audibly, maybe with humming, so everyone can hear and synch to the collective biorhythms embedded in audible abdominal body tremor. But except for a few instructions, they don’t talk in mindful resonance, so there is no “meaning,” no relationship, no obligation. Just raw-felt silent connection, living proof that biophysics works.

Nervous systems in general, and the human nervous system in particular, evolved for outdoor life and spontaneous nonverbal interaction millions of years before the words, art and technology that humans are now so proud of. But while tech has taken over, our senses still need nature. The more we can reexperience the garden paradise we evolved for, the better we’ll feel.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post 10 Physics Tricks to Recover From Digital Decalibration appeared first on Fair Observer.

Those special-purpose sonic environments are technically called “sound baths,” but both aspiration and experience prefer the colloquial term “sound healing.” Sound baths do, in fact, make one feel “healed” just like a good massage does.

I’m fascinated by sound baths not just for the quiet, subtle thrills that pure tones give to any breathing human. As a neuroscientist and biophysicist, I spent my career understanding the mathematical theory of how fluid brains interact with vibrating bodies, with the most relevant discoveries published in three research papers (see here, here and here). It turns out that coherent sound patterns can help nervous systems “tune” themselves, in the same general way tuning-forks help experts tune pianos or harps. A few months ago, I validated that explanation in person with Aurelio, the man who founded the world’s most prestigious sound-bath workshop called Svaram in Auroville, India. Aurelio and I agree on how sonic waves heal human bodies.

That insight matters, because sound baths — like many “alternative” therapies that use live humans — have amazing cost/benefit ratios, delivering happiness fast and cheap. Yet such therapies get short shrift in monetized media, precisely because they have so little profit and centralized messaging. The NYT article, for example, gave lots of examples and quotes, but didn’t distinguish between practices or explain why they work.

Fortunately, that article’s one scientific quote says all we need. David Baguley, a professor of hearing sciences at the University of Nottingham, said: “We know that sound has a massive influence on how the brain is organized.” Of course! The whole body from ears to toes is just a collection of vibrations, so it’s practically made of sound. Understand sound, you understand us.

The Science

Think of all the motions a human body can have, from big and slow to small and fast. The biggest, slowest motions are the strides and arm swings of locomotion, followed by faster and more delicate motions of fingers, toes and face. Keep going into the muscular tremors of the body (lasting around 0.03 seconds) and of the eyeball (0.01 seconds), through audible sound waves (down to 0.0001 seconds), into the ultrasonic realms of sound localization and proprioception (under 0.00001 seconds).

Those vibrations span factors of millions in time, with the highest-bandwidth, most information-dense signals at the microtime end. Those ultrasound echoes enable the brain to convert time into space, microseconds into millimeters, both inside and outside the body. Those neuromechanical vibrations make your image of yourself and your world.

Every last one of those body motions, from seconds to microseconds, is a kind of vibration and thus a kind of sound. You could say that a brain’s primary task, even the “visual” task of vibrating the eyeball, is that of anticipating and re-creating vibrations in space. Our brilliant brains are jelly managers.

That means the whole brain/body system reduces, in a physicist’s sense of “first approximation,” to a kind of self-playing instrument. Say a “smart” harp with a million strings, one string for each muscle fiber.

In this metaphor, the harpist brain sends pulses (action potentials) to “pluck” muscle fibers at precise, predetermined times. Right after, the plucks’ micro-reverberations trigger a coherent wave of sensory-neuron pulses back up to the brain. By learning to arrange the outputs and inputs to overlap, the brain minutely sculpts muscle and myofascial vibrations in the body, making them as predictable and lingering as possible. But you couldn’t possibly be aware of those tiny vibrations because they are far too numerous, fast and subtle to be tracked by clunky “consciousness.” They are as unconscious as can be.

Back in paleo times, our nervous systems calibrated themselves just fine for a few million years, because the outdoor sonic environment we evolved for was simple, natural and three-dimensional: wind sounds, rain sounds, twig-snaps, people.  Every sound a real one, every microsecond perfectly in place.

Unfortunately, the modern world messes with microseconds: screens and lights flicker at rates that drive the unconscious crazy, digital phones scramble subtle vocal nuance, loudspeakers make unphysical sound patterns, earphones create competing soundscapes, wireless interruptions make unpredictable shocks. Our delicate vibration-managing nervous systems become de-calibrated not just by the sounds we call “noise pollution,” but also by the artificial sounds we call “entertainment” and “connection.”

The solution to mental misery created by a de-calibrating sonic environment is to return to a calibrating one, such as a sound bath. The most natural sonic environment is obviously nature itself and, in fact, the practice of loitering quietly among trees, called “forest bathing,” provides well-documented benefits.

In the neuromechanical view, trees provide naturally complex sound-reflection surfaces, and their rustling leaves provide coherent sonic point-sources, distributed through space. Full-spectrum authentic 3D sound. Sitting under a Bodhi tree in Auroville, I could hear the shape of the moving wind in the rustling leaves. Perhaps that same sound pattern enlightened the Buddha.

Human-made sound baths, on the other hand, use two opposite types of sound to recalibrate the supine recipients in two opposite ways. To recalibrate one’s spatial-localization sense — hearing exactly where a sound comes from — there are rattles, rainsticks, chimes and other objects that make sharp, sudden clicks or dings from specific points in space. These constitute what physicists call “point sources,” a kind of test pattern originating from exact points in space and time. (The Amazonian ayahuasca ceremony, a kind of drug-enhanced sound healing, ends with rattles shaken over the participants).

To recalibrate whole-body vibrations, sound baths also include things that ring continuously from being rubbed on the rim, the way one rings a wineglass. Brass Tibetan “singing” bowls and huge cylindrical quartz bowls both create enduring single-frequency notes, which typically form standing waves in the room. Standing waves have the simplest possible pattern in space and time, and so they provide the entire body with simultaneous, consistent, coherent stimulation. Sensory neurons on and under the skin thus all fire in microsecond synchrony.

Furthermore, the nature of standing waves, like those in microwave ovens, is to have “hot” and “cold” spots. That means you can feel the center of sound coming from within your head and feel it move around inside.

Different Sounds

Other sound experiences, such as traditional religious ceremonies, include blown instruments, whose sounds are less pure, but thereby also embed vibrations from the performer’s abdomen. For example, the Tibetan horn, the didgeridoo or the Jewish shofar.

Some experiences involve the sonic properties of the space itself, such as reverberation patterns in a cathedral (e.g., the Caveau Phonocamptique), or the echo-enhancing meditation space in Auroville’s Matrimandir.  These point to the final benefit of sound baths: they’re social. A group of people in a quiet room automatically bathe one another in a soup of imperceptible human-generated vibrations, reference signals as useful as sounds from bowls and rattles. We can “heal” each other just by breathing.

So understanding our brains as vibration managers easily de-calibrated by modern life shows us what to avoid and what to do. Any self-learning processor needs to avoid artificial and artificially interesting signals, so tech-made sounds and fractured soundscapes in and of themselves de-calibrate nervous systems. Fortunately, that same processor can recalibrate itself with simple sounds from solid objects, one of the cheapest and safest ways to make the nervous system sing again.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post The Physics and Biophysics of Sound “Healing” appeared first on Fair Observer.

The reasons are ordered with the most important ones at the end.

1. Bad Light: Low-Contrast Blue

Low-contrast: Solid, physical objects illuminated by natural light have very high contrast ratios as with the contrast between direct sun and deep shadow, surpassing 10,000:1. The best passively-illuminated screens, like the Kindle Paperwhite, are hundreds of times worse (15:1). A few backlit monitors manage 1000:1 contrast ratios (as viewed in normal light), which is still worse than natural objects.

Blue: The human circuitry for setting day-night patterns (circadian rhythms) is sensitive blue light, which in nature it only sees from dawn to dusk, never at night. Any screen that looks white contains blue light; viewing during the wrong times will damage sleep-wake cycles.

2. Fixed Focus 

Our eyes evolved to look at objects at a whole variety of distances, not just half a meter directly in front of the face. Keeping any set of muscles in exactly the same position for long periods tends to “overtrain” those muscles into less flexibility, and the eye muscles are no different. As a result, screens are increasing both eyestrain (computer vision syndrome) and myopia worldwide.

3. Oculocentric

Normal, physical objects like paper interact not just with the eyes, but with all the senses. Paper makes crinkling sounds when you crumple it, it feels rough or smooth, it may smell of perfume or even taste bitter when you make spitballs, or eat your words. Since the main purpose of brains is to stitch and meld together signals from multiple senses (sensory fusion), using just one sense in place of five is a big mistake. In particular, screens completely leave out the tactile channel of reciprocal touch, the channel primates rely on most for forming interpersonal trust.

4. Too Smooth, Flat and Shiny

Smooth: The mechano-receptors in our fingertips are incredibly sensitive to a wide variety of natural textures. Glass is unnaturally smooth, and that smoothness deprives your skin of essential tactile information. Furthermore, overexposure to a single stimulus mistrains the nervous system.

Naturally writable: You can write on normal physical objects, like paper or whiteboards, which gives your sensorimotor system far more autonomy and control than if touch is missing or clunky, as with screens.

Glare: Our eyes evolved to look at natural objects, very few of which are shiny. Shininess on its own already causes certain kinds of visual miscalibration (see #7 below), but it becomes especially distracting to the visual system when layered in front of what you’re looking at, as with the shiny glass reflections that sometimes make screen-based text hard to read.

Flat: There are almost no truly flat objects in the natural world. If human eyes work best and learn best when looking at a wide variety of natural shapes, then they must correspondingly suffer from hours of looking at the exact same shape, and an unnaturally flat one at that.

5. Fractured in Space and Time

Pixelated: Natural objects have microscopic detail and structure down to the molecular level, containing far more visual information than we can be consciously aware of (hyperacuity). So for the pixelated images of screens, even if the pixels are so closely spaced the screen looks sharp. The nervous system as a whole still isn’t fooled.

Flickering: Screens and their pixels flicker from 50 to 100 times per second, which is faster than conscious awareness, so we don’t see the flicker. Unfortunately, the nervous system is highly sensitive to all changes, especially sudden changes, at timescales yet a thousand times faster. To your nervous system, a plain white computer screen is like a disco strobe at hyperspeed.

6. Edge-enhanced

Objects in the natural world have edges. They don’t have “edge-enhanced” edges, which look weirdly extra-sharp. (To see this effect, find a modern, high-definition display and look closely at a moving football player.) The uncanny sharpness comes from algorithmically adding extra bands of bright and dark that highlight the edge in a flat image — an effective way of tricking a brain’s processing circuitry. But the more a brain gets accustomed to consuming pre-sharpened, unnatural data streams, the less well it can detect and sharpen natural ones on its own.

7. Over-Attractive

Random views of nature are pretty boring and often hard to make sense of (dirt, grass, leaves). Screens, on the other hand, have the boring and ambiguous stuff removed and add in lots of extra-bright colors, eye-catching motions and crisp clear patterns. Unfortunately, what makes something interesting is how unusual it is, which is why we evolved to have an appetite for it. And, as a matter of principle, overdosing on unusual stimuli makes them not unusual anymore, and thereby de-calibrates the nervous system all by itself.

8. Sudden interruptions

In nature, there are no true interruptions. Even a thunderclap is preceded by lightning, and the lightning preceded by a cloud. A wireless interruption like a text or call, on the other hand, comes literally out of nowhere, unpredictably, startling the nervous system deeply and spiking markers of anxiety, like the hormone cortisol. Electrical or not, sudden shocks are always shocking.

9. Persuasive

What appears most often on screens is not just specially selected to make you look at it, but optimized to make you do something: buy, subscribe, vote, retweet or at least look more. That makes it a form of persuasive technology — a technology whose primary purpose is to make people do less of what they want to do, and more of what some business wants them to.

In other words, the purpose of the technology is to control human perceptions, beliefs and behavior. People behave on average as if addicted to screens because their decisions, on average, are controlled by the screens. Persuasive technology does work, and it works by dangling just the right rewards at just the right times, using principles originally discovered with rats and cocaine levers. The main difference is that the “drug” that screens dispense is images, not chemicals. Habit-forming dopamine circuits work the same for both.

10. Anti-Social 

Humans are the most elaborately social animals on the planet. To form trusting bonds, we need to hear and touch each other even more than we need to see each other. By depriving us of those quick-response signals while pretending to “connect” us visually, screens create the worst kind of socio-sensory deprivation, one that addicts people to monetizable social interactions which make them even lonelier.

In summary, there are many straightforward reasons why highly artificial inputs (like screens) ought to be bad for highly-sensitive creatures like us. Furthermore, there is abundant evidence that screens actually do damage human mental health. Practically every possible form of mental illness — loneliness, depression, anxiety, self-harm, violence, ADHD, “spectrum” disorders, OCD — is on the rise, and each is directly correlated with screen exposure (see Sensory Metrics for clinical references). Mental misery is rising everywhere, and fast.

Mobile video in general, and screen devices in particular, represent a peculiar technological pinnacle that works because it interferes with our perceptions and behaviors. Such technology cannot help being bad for us in large quantities.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post 10 Physics Reasons Why Screens Are Bad for Humans appeared first on Fair Observer.

Since the fall from the real garden of Eden, what some scientists call Paleo Paradise, humans have had trouble living together in peace. So, we dream of ideal societies and try to construct them on purpose. Such utopias take two forms, depending on how long they’re expected to last.

At the temporary end are escapes like parties and festivals, and at the long-term end “intentional communities” like kibbutzim and communes. A well-known example of the first is the annual week-long psychedelic party in Nevada’s bleak Black Rock desert, the sex-drugs-rock-n-roll-machinery-art festival known as Burning Man. The most successful long-term example is Auroville in South India, over 50 years old, inspired by a Gandhi-like guru named Sri Aurobindo, blessed unanimously by the United Nations and reforested from scratch on a barren patch of red dirt. I’m lucky to have visited both Burning Man and Auroville, and would like to share the flavor of each, along with what does and doesn’t work, and why.

SIMILAR PLACES, DIFFERENT LOCATIONS

The failure modes of utopias, but especially their successes, matter a lot to humankind right now. Worldwide, depression and suicide are up. The more technology presses in, the more get-away-from-it-all escapes can help make sense of life. Burning Man aims at a peak resonance experience, a big bang; Auroville at continuous, ongoing resonance, a steady thrum. Both succeed, both are becoming corrupted by money, both have immediate potential to transform the world, and both are sponsored, in part, by billionaires who want to make a difference. Utopia might seem silly to some, but getting it right is the best and maybe only chance we have left. It helps to study any utopias that almost work.

My own perspective matters here. I grew up in Silicon Valley, the land of cults and startups. Like other inhabitants of the valley, I made the pilgrimage to Burning Man, where I’ve “burned” seven times. This year, I made my way to India to visit family and to fulfil two  more motivations: receive authentic advice on Ayurvedic medicine and visit Svaram in Auroville, the world center of vibrational healing. Visiting Svaram and meeting its founder, Aurelio, was important to me because the focus of my biophysics research is vibrational healing. I certainly didn’t come to Auroville thinking of Burning Man.

But from the outset, the physical similarities between Burning Man and Auroville were immediately obvious. Both are laid out in circles with diameters of 3 kilometers, their perimeter guarded and fenced, their wide-open central circles filled with celebration, bonfires and worship focused on a massive, artistic structures built dead-center of both circles. Additionally, both are flat, hot and dry, unpaved, dusty, crisscrossed by bikes and noisy smoking vehicles. Outside the central common area, habitats are divided into quirky self-governing communes, called “theme camps” at Burning Man and “settlements” in Auroville, each shaded and decorated by geometric fabric tarps, awnings and artworks — all visually countercultural. In both places, here and there viewing towers rise above the flats.

The people living in both Auroville and Burning Man are generous and kind, and prone to wearing practical, desert-wear like dust masks, headscarves and flowing cotton drapes. Many go by unusual single names, honorifics given specially for the place. Both locations offer far too many healthy daily activities for any one person to consume: yoga, dance, discussions, myriad hippie-style workshops such as dancing, breathing, massaging, meditating, “healing,” chanting and relating.

Both places are hard to get into and, as a result, are filled with enthusiastic people who pay money and work hard to be there. They are both full of like-minded souls who want to be around each other. Burning Man and Auroville “work” as real-world utopias, but that’s where the resemblance ends.

THE AMERICAN ESSENCE OF BURNING MAN

Burning Man is a giant party, as temporary and unsustainable as can be. It is a raucous art-and-noise festival on a desert lakebed, caked with antiseptic lye-laced dust, which is rinsed clean by rain each winter and blown into opaque yellow clouds each summer by hurricane-force winds and dust-storms every afternoon. Burning Man is named after the huge ceremonial burning effigy of “the Man,” an abstract wooden human form 25-meters tall that visually anchors the center of Black Rock City, day and night.

Burning Man 2015 © BLM Nevada

Apart from the Man, the Burning Man festival also burns much of its garbage, such as paper plates and most large wooden structures, instead of taking them apart and dragging them home. Taking things back home is inconvenient and, besides, burning them is fun. And Burning Man burns literally tons of fossil fuel in vehicles to get to and from the desert, and generators to fuel sound, light, art and parties, day and night, all taking far more energy than simply staying home. At its peak, Burning Man is filled with 70,000 close-packed partygoers, making it a blasted, giant, over-lit refugee camp — Mad Max meets Las Vegas.

The difficulty of getting in and living there is part of the point. Commerce “on-playa” isn’t allowed. You have to bring everything yourself, food and water included, everything except portable latrines, the only thing provided. And you have to carry out all your trash, down to every scrap of lint. The injunction “leave no trace” is taken religiously. There are no garbage cans, on purpose, to enforce personal responsibility for trash. That eco-consciousness is ironic when set against the overall indulgence and wastefulness of the festival as a whole.

A group of would-be “burners” needs weeks or months of preparation to assemble and haul enough food, water, shade-structure, generators, fuel, decorations and, especially, party supplies to not only survive, but also thrive. Burners need provisions on a flat, harsh, hostile plain to survive and to make their camp attractive enough to pull in fellow souls. Entertaining others is the goal of almost everyone.

Apart from logistical barriers, the $500 entry tickets keep out riff-raff. By rigorously checking tickets, the security station keeps out anyone without tickets. With its hours-long wait, invasive vehicle searches for stowaways, and ever-spinning radar and night-vision coverage of the surrounding open plain that is capable of spotting jackrabbits miles away, those without tickets have little chance of sneaking in. Getting into Burning Man is an all-or-nothing affair and the whole thing reeks of Checkpoint Charlie. Yet once inside you’re free to do practically anything, the ultimate dream of the American West, ironically made possible by enforcement emulated from the Eastern Block.

Go naked. Get drunk. Make noise. Do drugs. Burn your stuff. Create giant fireballs, with permission of course, so that people don’t get hurt. Drive or be driven in giant rolling structures —“art cars” whose purpose is to look nothing like vehicles — or even ride your bike. The roads, or rather the portions of hardened dust marked off with sticks and signs that pretend-play at roads, form a regular radial grid: concentric circular ring-roads labeled A through K or so, and spokes named in 30-minute, clock-face increments. This leads to weird-sounding appointments, such as “I’ll see you at 4:30 and F at 6:00.” It also leads to cognitive dissonance if you return in subsequent years, because the streets remains the same while the locations of landmark camps shift.

The regular road infrastructure and the banks of portable toilets every few hundred meters is all that your $500 ticket buys. That fierce, capital-intensive individualism, an American specialty, drives Burning Man. It is home-built entertainment to the extreme. Groups build and bring giant art, climbing structures, roller-discos and dance domes. Hundreds of homemade bars enthusiastically serve free drinks all day and night. During the day, one might roam by bike across the wide-open center, stumbling across unexpected weird constructions, or friends you didn’t expect to see. At night, the roads are choked with dust, kicked up by people wearing elaborate furry, fuzzy, blinky costumes and their decorated bikes. Burning Man is the ultimate privatized party with everyone dedicated to grabbing each other’s attention.

The density, flashiness and amplified sound ramp up all week to a pinnacle on Saturday night, when The Man burns in a frenzy of fire-dance, whooping and hollering. This is the week-long party at its craziest, even as Black Rock City starts disassembling itself for the long drive home. Burning Man is so temporary, it celebrates its own demise.

While many burners are spiritual people, only one place on the playa is built for spirituality: the Temple. This is an ornate walk-in sculpture, different each year, half a kilometer beyond the Man in the wide open desert. People move reverently in the Temple, pinning pictures of departed loved ones or scrawling messages to them on its walls, sighing and crying in escape from the overstimulation all around. When the Temple burns the Sunday after, roaring and crackling as its embers soar upwards, one hears no whoops and hollers, only hush.

THE INDIAN SPIRIT OF AUROVILLE

The Temple offers spiritual solace in Burning Man, but it is banished both physically and psychologically to the periphery. In Auroville, quiet spirituality radiates from its center and has kept it alive for 50 years.

Auroville is named after Sri Aurobindo, an Indian sage who celebrated human unity. He was a contemporary of Gandhi, a fellow revolutionary who was jailed by the British. A disciple of his, a Frenchwoman now revered the as the Mother, proposed a pan-human city in his name. Newly-independent India provided 20 square kilometers of hot eroded dirt, and the United Nations did the cheerleading. Several hundred altruistic volunteers began reforesting the place by hand, living on the shadeless, waterless plain not just for weeks as in Burning Man, but for years. Now the millions of trees they planted cool the place, and machines dispense free drinking water. Cookware isn’t burnable plastic and paper, but indestructible stainless steel.

Entry into Auroville is free to visitors, but not to their vehicles. Only local motorbikes and tuk-tuks, locally known as autos, ply Auroville’s dusty roads, which are allegedly arrayed in regular spirals like a galaxy. In practice, these roads curve almost randomly, making the place difficult for newcomers to navigate, but also making it seem larger and more mysterious than it is. Few signs show where you are, and none show distances. With fewer straight sightlines than Burning Man, 20-fold fewer people and lots of trees, Auroville’s residential portions are a mix of modest mansions. Modernist concrete structures and quaint creative communes lie semi-hidden in a scrubby forest as sprawling estates of faded luxury.

Auroville’s reputation for environmental technology has grown alongside its forests. It now leads the way in permaculture, water management, solar energy and similar conservation techniques. The stream of tourists, housed and fed, provide steady revenue. Tourists also buy — and Auroville exports — fancy clothes, soaps, oils, incense, handicrafts and (my favorite) sonic instruments. The Aurovillian settlement called Svaram invents and deploys the most beautiful and beautiful-sounding chimes, bells, gongs and rattles used in the therapy called “sound healing.”

Svaram was why I came to Auroville: to understand its most potent products, techniques and philosophy. Long discussions with Svaram founder Aurelio confirmed my professional instincts about why sound healing works. In a simple neuromechanical view, the body is a big wad of jelly, whose jiggles the brain wants to control minutely. But tuning a jiggle-managing brain needs pure vibrations as reference signals, just like tuning a violin needs a pure pitch. Svaram makes pure sources of three-dimensional vibrations to stimulate the entire body, not just the ears: continuous thrums like singing bowls for pure centerless pitch, chimes and rattles for sudden spots in spacetime. When people relax into such a sonic soup, letting the sound wash over them, their nervous systems recalibrate. At least that’s what biophysics predicts, and what people say.

Auroville © Vikram Ramakrishnan

Back to Auroville. More than half the people in Auroville at any given time are Europeans, mostly speaking French. After all, it was a French colony till 1954. During four days, my wife and I heard only one American voice besides our own. The rest of the people are Indians, mostly servants, and mostly living outside Auroville. Although there is a place called “African Pavilion,” I didn’t see a single African. I did, however, meet a native Aurovillian, a man about my age, born in Auroville in 1968. Nothing else proves sustainability like happy second-generation natives.

South India is a conservative place. There is not only no nudity, but there are barely bared shoulders, leaving the clothing a mix of saris, buttoned shirts and flowing hippie cotton. Among the Europeans, thin, middle-aged women dominate, often in pairs, a natural demographic for the myriad yoga workshops, other spiritual activities and organic meals. The food is safe to eat, but, unlike on the Playa, the dust is not safe to breathe, since it contains pulverized fecal matter from cows and dogs. I almost died from pneumonia caused by dust like that before, so I know the dust-masks people wear are health precautions.

Auroville has no bars at all, little if any alcohol or drugs, not many lights and barely any music. The place is dead at night, except for quiet workshops here and there, and even those are difficult to find in the dark. Auroville is quiet on purpose, and it even has signs asking people to be silent or speak slowly.

Auroville does have one especially attractive kind of drug. But it can’t be bought with money, only with the common human currencies of planning, time and effort. This “drug” involves not chemicals, but human proximity. I’ve tasted it three times. They call it “the divine”; I call it human resonance. A modest form can happen when a few dozen people in a quiet room, led by an expert choir-master, sing or hum a simple, meaningless tone in unison or harmony. In such acoustic synchrony, the vibrations of an individual’s vocal chords synch with those of the chest, spine and ears, and then with those of others nearby, and thereby with their bodies too. Without the distractions of words, a whole group of people can fall into sympathetic vibration, spontaneously and organically. It feels amazing.

SILENCE AND THE SENSES

Auroville’s most potent form of resonance takes place in the central meditation (aka “concentration”) space, and entry is by reservation only. That circular room, inside the enormous 24k gold-covered ball called the Matrimandir, is luminously white, open carpet encircled by tall marble walls and columns, centered on a huge glass sphere, skewered and illuminated by a vertical shaft of sunlight from above. It is a central, physical, geometrical image of divine perfection. Everyone sitting sees the same view and hears the same silence, cherishing the kind of togetherness that can only be spoiled by words. Fifteen minutes of that silence feels like eternity. No wonder people go back, and back again, to sip from the divine.

That silent experience involves the same neuromechanical mechanisms as Svaram’s sound healing, except in this case the resonating sources are not gongs but fellow humans, engaging frequencies from infrasonic to ultrasonic. These are not too far off from the potent silences shared at the Temple at Burning Man, silences that also move people to tears. Harnessing those silences will be the key to reinvigorating these utopias.

Auroville, of course, could reduce ambient engine noise toward electric levels and below, and could limit distracting mobile phones, the most anti-spiritual form of technology in existence, by far. At the other extreme, noisy Burning Man would be improved in proportion to how it protects and enlarges zones of dark and silence, twin foundations of any paleo sensory diet. At present, Burning Man’s attention-grabbing economy and amplification-heavy technology drive native desert silence into hiding, leaving quiet human togetherness off the table. I fantasize about “Quiet Man,” with the motto “Leave No Trace, Nor Sound Nor Light.”

Burning Man and Auroville were both founded on principles and practices of human togetherness and autonomy. Both goals are being undermined, inexorably, by technologies that come between humans. In the case of Burning Man, these are technologies of blaring sound and hyper-flickering, hyper-colorized LED displays. In Auroville’s case, wireless interruptions and miscommunications are fracturing live human connection. The good news is that once leaders and sponsors in these places come to understand how humans really interact, they’ll rewrite rules around solid neuromechanical principles, and make the utopian experience really sing.

In fact, all of India might follow the same track. Over three weeks, I focused my neuromechanical lens on all kinds of experiences between Chennai and Puducherry. The Aurvedic self-massage prescribed for me using slippery thick oils turned out to be an ultimately delicious and transformative experience, even without the sleep and diet tricks. The high-speed, high-stakes traffic dance of interweaving buses, cabs and motorbikes; the  throngs of chattering schoolchildren; the high-fiving strangers; the sight of friends walking and laughing close by, hand on shoulder or arm in arm; and rich ladies lunching in a fancy fashion café are abiding vignettes in my memory.

Those high-bandwidth sensorimotor interactions are what the human species needs everywhere — not just in India. And they are what is missing from the Western world. If India could just ignore the receding mirage of software wealth and refocus on its ancient core of human vibration, it might yet set the example the world needs: more of Auroville.

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

The post Burning Man and Auroville: Understanding the Human Condition appeared first on Fair Observer.

The tech honeymoon is over. Students in Brooklyn, New York, walked out in protest against a tech-heavy educational program. The very first conference on “screen addiction” attracted 200 teachers, parents and psychologists from three continents, almost all paying their own way. Facebook CEO Mark Zuckerberg was grilled on the US Senate floor. France banned cellphones in schools.

The more technology tries and claims to “connect” people, the more distrustful and disconnected people seem to be. Metrics of mental misery are rising worldwide, from loneliness and depression to suicides and suicide-killings. Many ordinary people blame technology.

Douglas Rushkoff’s new book, Team Human, decries the human damage done by digital technologies, some of which I helped create. He says the nemesis of humanity is “team algorithm,” and I was Silicon Valley’s first “algorithm officer.” He denounces smartphones, and I collaborated with the guy who invented them. He says we need to get back into lived, touchy-feely experience — for years I wrote my own code and still live by math.

Rushkoff, an American media theorist, has been writing books criticizing technology for years; two of the most recent were Throwing Rocks at the Google Bus and Program or Be Programmed. You get the idea. The current hardback is bright red and yellow, the colors of McDonald’s, or communism, take your pick.

Team Human is cleanly organized into 14 chapters containing a hundred two-page, bite-sized ideas, such a tight design that with the first sentence of each essay you can fairly represent the whole book’s arc. His entire case can also be extracted from the first two pages, forming a different but equally crisp miniature.

Rushkoff’s theses together form a manifesto against “the machine,” a social broadside reminiscent of Martin Luther’s 95 theses on the church door 500 years ago. The Wall Street Journal caricatured Rushkoff’s book using the phrase “Users of the World, Unite!”

Perhaps The WSJ painted him as a has-been hippie because of this quote: “Capitalism’s vision of the individual as a completely self-interested being, whose survival was a Darwinian battle royale, is at odds with our social evolution and our neurobiology.” Or maybe this quote from Team Human’s final chapter: “As much as we think we’re separate individuals, we’re wired from birth and before to share, bond, learn from, and even heal one another. We humans are all part of the same collective nervous system. This is not a religious conviction but an increasingly accepted biological fact.”

Rushkoff Is Right

There are all kinds of scientific “facts.” The most common so-called facts are at the evidence-end of the truth spectrum, facts gathered with time and money, often incentivized and organized to serve an agenda and, therefore, even worse than hearsay. At the other end of the truth spectrum, only a rare few scientific are formal, mathematical facts — facts about numbers themselves, facts so absolute even Albert Einstein would accept them sight unseen. Facts that would be true on Mars or on Alpha Centauri. What Rushkoff doesn’t tell you is that hard-wired human sociability is the second sort. Human social resonance isn’t hearsay or paid-for propaganda, it is a mathematical fact.

That is the conclusion of one peer-reviewed paper Team Human cites, “Sensory Metrics of Neuromechanical Trust.” In fact, that paper concludes with an anti-capitalist claim as totalizing and absolute as Rushkoff’s final fanfare: “Like all other nervous systems, ours evolved to forage, not produce. Humankind uniquely produces things which captivate its senses, and now they do.”

In fact, that second statement goes beyond being anti-capitalist, all the way to being anti-productive. I know because my wife and I wrote it. Criscillia Benford and I agree with Rushkoff, he interviewed us on his podcast Team Human and we like him. Most of all, we reached the same conclusions as Rushkoff independently, a single answer originating from three different disciplines (media theory, literature and neurophysics).

These are the same basic conclusions also expressed ages ago in stories like The Machine Stops, Brave New World, Fahrenheit 451 and recently in an essay by computer-historian George Dyson’s called “Childhood’s End.” A universal set of truths is emerging, a coherent consensus among intellectuals about the existence and spread of inherently toxic patterns in the modern human behavior and  communications system. Historically, when so many smart people independently reach the same answer, it’s the right one.

Rushkoff is the first to distill the coherent consensus into book form, and I know he’s right. Plus, among the world-class brilliant people I’ve interacted with, I think he’s even more brilliant, high in the firmament near Freeman Dyson. So, this review is biased toward Rushkoff.

While I can’t remove my bias toward mathematical truth (my parents were both nuclear physicists), I can explain where math supports Rushkoff, and where it doesn’t, by explaining a few of his culture/media-theory ideas in our information-theory, data-science terms. I’ll start with what’s obviously in Team Human, then what is implied but not elaborated and then end with some specifically wonderful solutions even Professor Rushkoff doesn’t know yet.

Tech, Screen Addition and Human Interaction

Team Human’s core warning is that human-created technology on the whole, including even words and writing, damages human interpersonal interaction and affection via a tangle of runaway vicious circles that are accelerating year on year. Its core advice is to revive and practice our hard-wired natural capacity for social resonance.

More specifically, Rushkoff says that one-way communications like broadcast media undermine human resonance and trust in a particularly specific vicious cycle: Technology makes us feel and act less human, and thereby makes us see and treat others as less human too. This erosion of trust caused by indirect (mediated) communications began thousands of years ago with micro-insults like memorization and writing, but is now exploding in potency to dazzle our anxieties with fake news and cyberstalking.

Math says Rushkoff is right. Mathematically, trust is built from lots and lots of back-and-forth interactions among autonomous individuals. Trust accumulates statistically, from data, as it does in any data-processing algorithm. Through that lens, two people talking and touching face-to-face share so many millions of micro-messages a minute they have plenty of time to lock in and confirm that they’re on the same page. They can trust each other’s “content” (whatever that is) because they can see and interact in real space and real time at maximum sensory-motor bandwidth, which is the native communications protocol for homo sapiens’ 3-D nervous systems.

Math also says, therefore, that when you break the interactivity, you break trust formation. Because broadcast is one-way, no interaction, therefore the medium of broadcast provides no trust and only consumes it.

To be sure, broadcast does have uses. Among the antelope on the savannah, when one white tail whips, all antelope around take note and flee. No time for interaction during an alarm, just fear or fight or flight. Since even antelope can broadcast, obviously humans can too, so broadcast isn’t bad in and of itself. But broadcast only works for sending fast negative signals like alarm or hostility. No instant, one-way signal could ever carry the back-and-forth signals that slowly accumulate into positive human qualities like empathy, trust, affection, collaboration and love.

Humans don’t actually suck. We aren’t bad people, and people aren’t bad. We’ve just spent so much time looking at each other through a weird kind of glass that filters out the good parts, that we’ve forgotten what the good parts look like or even where to find them. That’s the problem Team Human poses.

Team Human vs. Team Spreadsheet

What Team Human doesn’t and cannot pose is the awful, epic, apocalyptic scale of a problem that originates in the statistical structure of life itself, and whose built-in feedback traps precede all the human ones that Rushkoff cites a million-fold in time. To wit:

1) When self-replicating patterns like RNA and DNA first emerged, the chemo-sphere became a biosphere, starting its slide down a slippery slope called entropy reduction, otherwise known as plummeting diversity. Raw diversity is in fact going down, and not just in human things like languages, ethnic groups and political parties. Diversity was going down in species, genotypes, body architectures and such ever since DNA beat out some other chemical. Survival of the fittest means death of diverse others. It means diversity reduction.

2) When moving animals emerged and roved for nutrients, their only choice in life was stay and focus your search or go afield and blur it out. The catch is that too much focus gets you stuck. Now, modern human brains fall into funneling focus on pinpoint pricks of pixels saying “liked” or “viewed” or “clicked” or “purchased.” Or claiming to say that.

3) Communicating animals reset their nervous systems by making ever-grander attention-seeking gestures, interrupting others to receive a confirmation that they’re really there. Like turning up a megaphone. Making extra noise to be heard is an informational instinct, not a human weakness. Unfortunately, when everyone starts interrupting and yelling at once, especially in an echo-chamber, the communications channel collapses and everything gets worse. For example, the mobile SMS/text channel is already collapsing from undelivered or auto-miscorrected messages; the email channel is collapsing from spam and fraud; and the phone channel is collapsing from robo-calls, dropped calls and gurgling over-compression. Communications technology is getting worse, and thereby disconnecting us.

4) Although automated algorithms (Rushkoff’s “team algorithm”) generate the most anti-human signals, even they aren’t the enemy. The real enemy is the metric values that algorithms calculate to supplant human values: the anti-human values embedded in the spreadsheets used by both algorithms and executives. The real enemy of Team Human is “team spreadsheet.”

That’s a lot of gloom and doom. Fortunately, the same mathematical axioms that deliver the bad news promise many miraculous cures: ultra-resonance, ultra-breathing, ultra-acupuncture, ultra-grounding. Poke your skull at this one spot, make this funny face, hold this muscle just so… and pow — instant relief (sometimes). The good news is that a nervous system which can be hacked by social media and digital deception can be un-hacked too, best through the spine, instantly rebooted to feel instead of to see.

This is the only message missing from Team Human, the most optimistic message of all. Yes, humans are drowning in a tidal wave of toxic technologies separating us. But there are also cheap, simple, safe touch techniques and technologies, right under our noses, which give relief surpassing drugs or surgery, which connect us and which help us heal each other. The really good stuff exists already, unmonetizable and thus unexploited. Finding it, inventing it and collaboratively spreading it in time to help will be the challenge of the ages.

*[Team Human is published by W.W. Norton & Company, 2019]

*[The articles in this column present a set of permanent scientific truths that interlock like jigsaw pieces. They span physics, technology, economics, media, neuroscience, bodies, brains and minds, as quantified by the mathematics of information flow through space and time. Together, they promote the neurosafe agenda: That human interactions with technology do not harm either the nervous system’s function, nor its interests, as measured by neuromechanical trust.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.

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