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The researchers first analyzed the brains of 12 patients with neurological disorders – mostly epilepsy – who have experienced this kind of “apparition.” MRI analysis of the patients’s brains revealed interference with three cortical regions: the insular cortex, parietal-frontal cortex, and the temporo-parietal cortex.

The participants were unaware of the experiment’s purpose.

Instinctively, several subjects reported a strong “feeling of a presence,” even counting up to four “ghosts” where none existed.

The project is called the Program for the International Assessment of Adult Competencies (known as Piaac, sometimes called “pee-ack”). In 2011 and 2012, 166,000 adults ages 16 to 65 were tested in the O.E.C.D. countries

Like PISA, Piaac tests people’s literacy and math skills. Because the test takers were adults, they were asked to use those skills in real-world contexts.

As with the measures of K-12 education, the United States battles it out for last place, this time with Italy and Spain.

Only 18 percent of American adults with bachelor’s degrees score at the top two levels of numeracy, compared with the international average of 24 percent. Over one-third of American bachelor’s degree holders failed to reach Level 3 on the five-level Piaac scale, which means that they cannot perform math-related tasks that “require several steps and may involve the choice of problem-solving strategies.”

American results on the literacy and technology tests were somewhat better, in the sense that they were only mediocre. American adults were eighth from the bottom in literacy, for instance. And recent college graduates look no better than older ones. Among people ages 16 to 29 with a bachelor’s degree or better, America ranks 16th out of 24 in numeracy.

There is no reason to believe that American colleges are, on average, the best in the world.

Instead, Piaac suggests that the wide disparities of knowledge and skill present among American schoolchildren are not ameliorated by higher education. If anything, they are magnified. In 2000, American 15-year-olds scored slightly above the international average. Twelve years later, Americans who were about 12 years older scored below the international average.

To fully understand how Bitcoin operates, one would need to learn the subtleties of public-key cryptography.

In the real world, when people want to buy something using Bitcoin, they transfer their ownership of a certain number of bitcoins to other people, in exchange for goods and services.

This transfer is effected by the network of computers performing computations and thereby changing the “public key” to which the “sold” bitcoins are assigned.

The encryption involved in Bitcoin concerns the identification of the legitimate owner of a particular bitcoin.

Without delving into the mathematics, suffice it to say: There is a way that the legitimate owner of a bitcoin can publicly demonstrate to the computers in the network that he or she really is the owner of that bitcoin.

Only someone with the possession of the “private key” will be able to produce a valid “signature” that convinces the computers in the network to update the public ledger to reflect the transfer of the bitcoin to another party.

When Bitcoin was first implemented in early 2009, computers in the network—dubbed “miners”—received 50 new bitcoins when performing the computations necessary to add a “block” of transactions to the public ledger.

In principle, the developers of Bitcoin could have released all 21 million units of the currency immediately with the software.

With the current arrangement—where the “mining” operations needed to keep the system running simultaneously yield new bitcoins to the machines performing the calculations—there is an incentive for owners to devote their machines’ processing power to the network.

Here, the danger is that the issuing institution—once it had gotten the world to accept its notes or electronic deposits as money—would face an irresistible temptation to issue massive quantities.6

Bitcoin has no such vulnerability. No external technological or physical event could cause Bitcoin inflation, and since no one is in charge of Bitcoin, there is no one tempted to inflate “from within.”

Some critics argue that Bitcoin’s fixed quantity would imply constant price deflation. Although this is true, everyone will have seen this coming with more than a century’s notice, and so long-term contracts would have been designed accordingly.

Whether to call Bitcoin a “fiat” currency depends on the definition. If “fiat” means a currency that is not legally redeemable in some other commodity, then yes, Bitcoin is a fiat currency. But if “fiat” means a currency relying on government fiat to define what will count as legal money, then Bitcoin is not.

Bitcoin is an ingenious concept that challenges the way economists have traditionally thought about money. Its inbuilt scarcity provides an assurance of purchasing power arguably safer than any other system yet conceived.

We need to let the decentralized market test tell us what is the best money, or monies.

The day-to-day work of a pilot is unstable, and often unpredictable. They’re away from home, and from their families, for long stretches of time. The job isn’t a typical 9-to-5— instead, pilots fly overnight from timezone to timezone, at strange hours.

To reduce fatigue, which is linked to stress, rules and regulations from the Federal Aviation Administration (FAA) limit the number of hours a pilot can fly and how much rest they need. During a 24-hour period, a pilot flying alone can’t log more than eight hours, for example, and they have a ten-hour minimum rest period before taking off.

But if stress creeps past that midpoint, performance starts to drop off. Too-high levels of stress mean exhaustion, panic, and blunted brain power. That’s when mistakes happen.

CRM training is designed to help pilots and crew members develop efficiency communication and decision-making skills. “It was also saying, this is what fatigue looks like, and this is how to recognize it in your co-pilot,” Bowen says. From that point on, she says, the airlines worked to develop a culture where pilots would hold other pilots accountable when they weren’t fit to fly. “It was about not protecting their buddy, but protecting overall safety,” Bowen says.

Pilot mental health is another big issue to tackle, says Quay Snyder, a former Air Force flight surgeon and a member of the Aerospace Medical Association Working Group on Pilot Mental Health. Pilots are often reluctant to acknowledge the effect that emotional stressors might have on their ability to fly, he says.

“They’re slow to recognize mental health issues,” he says, “and they might think there’s a stigma against asking for help.”

“Pilots trust pilots,” he says. “Hearing from a peer could help a pilot recognize that they may not be fit to fly. Hearing it from a physician doesn’t carry much weight, but hearing it from a peer does.”

Being distracted by the second task didn’t hurt actual performance on the first task, but it did impair the subjects’ ability to be introspective (again, by accurately self-reporting how they did). The finding supports previous widespread evidence that multitasking leads to lower cognitive performance.

If you are awake for 16 hours, turning on or checking your phone 85 times means doing so about once every 11 minutes (and doesn’t account for internet use on a computer), and 5.05 hours is over 30 percent of the day. What might be the effect on reflection of this compulsive behavior?

“That hints at the way that, as our technologies increase the intensity of stimulation and the flow of new things, we adapt to that pace,” Mr. Carr said. “We become less patient. When moments without stimulation arise, we start to feel panicked and don’t know what to do with them, because we’ve trained ourselves to expect this stimulation — new notifications and alerts and so on.”

Mr. Carr also noted counterarguments: Formulating relatively simple thoughts on the internet can yield more complex ones through real-time exchanges with others, and people whose reflex is to post a notion hastily rather than let it sit may not have been the most deliberative thinkers in a pre-smartphone time, either.

“We’ve adopted the Google ideal of the mind, which is that you have a question that you can answer quickly: close-ended, well-defined questions. Lost in that conception is that there’s also this open-ended way of thinking where you’re not always trying to answer a question. You’re trying to go where that thought leads you. As a society, we’re saying that that way of thinking isn’t as important anymore. It’s viewed as inefficient.”

You might be well-intentioned, rational, and mistaken, simply because so much in our thinking can go wrong. (“RATIONAL, adj.: Devoid of all delusions save those of observation, experience and reflection,”

You might be rational and self-deceptive, because telling yourself that you are rational can itself become a source of bias. It’s possible that you are trying to appear rational only because you want to impress people; or that you are more rational about some things (your job) than others (your kids); or that your rationality gives way to rancor as soon as your ideas are challenged. Perhaps you irrationally insist on answering difficult questions yourself when you’d be better off trusting the expert consensus.

Not just individuals but societies can fall prey to false or compromised rationality. In a 2014 book, “The Revolt of the Public and the Crisis of Authority in the New Millennium,” Martin Gurri, a C.I.A. analyst turned libertarian social thinker, argued that the unmasking of allegedly pseudo-rational institutions had become the central drama of our age: people around the world, having concluded that the bigwigs in our colleges, newsrooms, and legislatures were better at appearing rational than at being so, had embraced a nihilist populism that sees all forms of public rationality as suspect.

modern life would be impossible without those rational systems; we must improve them, not reject them. We have no choice but to wrestle with rationality—an ideal that, the sociologist Max Weber wrote, “contains within itself a world of contradictions.”

Where others might be completely convinced that G.M.O.s are bad, or that Jack is trustworthy, or that the enemy is Eurasia, a Bayesian assigns probabilities to these propositions. She doesn’t build an immovable world view; instead, by continually updating her probabilities, she inches closer to a more useful account of reality. The cooking is never done.

Rationality is one of humanity’s superpowers. How do we keep from misusing it?

Start with the big picture, fixing it firmly in your mind. Be cautious as you integrate new information, and don’t jump to conclusions. Notice when new data points do and do not alter your baseline assumptions (most of the time, they won’t alter them), but keep track of how often those assumptions seem contradicted by what’s new. Beware the power of alarming news, and proceed by putting it in a broader, real-world context.

Bayesian reasoning implies a few “best practices.”

Keep the cooked information over here and the raw information over there; remember that raw ingredients often reduce over heat

We want to live in a more rational society, but not in a falsely rationalized one. We want to be more rational as individuals, but not to overdo it. We need to know when to think and when to stop thinking, when to doubt and when to trust.

But the real power of the Bayesian approach isn’t procedural; it’s that it replaces the facts in our minds with probabilities.

Applied to specific problems—Should you invest in Tesla? How bad is the Delta variant?—the techniques promoted by rationality writers are clarifying and powerful.

the rationality movement is also a social movement; rationalists today form what is sometimes called the “rationality community,” and, as evangelists, they hope to increase its size.

In “Rationality,” “The Scout Mindset,” and other similar books, irrationality is often presented as a form of misbehavior, which might be rectified through education or socialization.

Greg tells me that, in his business, it’s not enough to have rational thoughts. Someone who’s used to pondering questions at leisure might struggle to learn and reason when the clock is ticking; someone who is good at reaching rational conclusions might not be willing to sign on the dotted line when the time comes. Greg’s hedge-fund colleagues describe as “commercial”—a compliment—someone who is not only rational but timely and decisive.

You can know what’s right but still struggle to do it.

Following through on your own conclusions is one challenge. But a rationalist must also be “metarational,” willing to hand over the thinking keys when someone else is better informed or better trained. This, too, is harder than it sounds.

For all this to happen, rationality is necessary, but not sufficient. Thinking straight is just part of the work. 

I found it possible to be metarational with my dad not just because I respected his mind but because I knew that he was a good and cautious person who had my and my mother’s best interests at heart.

between the two of us, we had the right ingredients—mutual trust, mutual concern, and a shared commitment to reason and to act.

Intellectually, we understand that our complex society requires the division of both practical and cognitive labor. We accept that our knowledge maps are limited not just by our smarts but by our time and interests. Still, like Gurri’s populists, rationalists may stage their own contrarian revolts, repeatedly finding that no one’s opinions but their own are defensible. In letting go, as in following through, one’s whole personality gets involved.

in truth, it maps out a series of escalating challenges. In search of facts, we must make do with probabilities. Unable to know it all for ourselves, we must rely on others who care enough to know. We must act while we are still uncertain, and we must act in time—sometimes individually, but often together.

The realities of rationality are humbling. Know things; want things; use what you know to get what you want. It sounds like a simple formula.

The real challenge isn’t being right but knowing how wrong you might be.By Joshua RothmanAugust 16, 2021

Writing about rationality in the early twentieth century, Weber saw himself as coming to grips with a titanic force—an ascendant outlook that was rewriting our values. He talked about rationality in many different ways. We can practice the instrumental rationality of means and ends (how do I get what I want?) and the value rationality of purposes and goals (do I have good reasons for wanting what I want?). We can pursue the rationality of affect (am I cool, calm, and collected?) or develop the rationality of habit (do I live an ordered, or “rationalized,” life?).

Weber worried that it was turning each individual into a “cog in the machine,” and life into an “iron cage.” Today, rationality and the words around it are still shadowed with Weberian pessimism and cursed with double meanings. You’re rationalizing the org chart: are you bringing order to chaos, or justifying the illogical?

For Aristotle, rationality was what separated human beings from animals. For the authors of “The Rationality Quotient,” it’s a mental faculty, parallel to but distinct from intelligence, which involves a person’s ability to juggle many scenarios in her head at once, without letting any one monopolize her attention or bias her against the rest.

In “The Rationality Quotient: Toward a Test of Rational Thinking” (M.I.T.), from 2016, the psychologists Keith E. Stanovich, Richard F. West, and Maggie E. Toplak call rationality “a torturous and tortured term,” in part because philosophers, sociologists, psychologists, and economists have all defined it differently

Galef, who hosts a podcast called “Rationally Speaking” and co-founded the nonprofit Center for Applied Rationality, in Berkeley, barely uses the word “rationality” in her book on the subject. Instead, she describes a “scout mindset,” which can help you “to recognize when you are wrong, to seek out your blind spots, to test your assumptions and change course.” (The “soldier mindset,” by contrast, encourages you to defend your positions at any cost.)

Galef tends to see rationality as a method for acquiring more accurate views.

Pinker, a cognitive and evolutionary psychologist, sees it instrumentally, as “the ability to use knowledge to attain goals.” By this definition, to be a rational person you have to know things, you have to want things, and you have to use what you know to get what you want.

Introspection is key to rationality. A rational person must practice what the neuroscientist Stephen Fleming, in “Know Thyself: The Science of Self-Awareness” (Basic Books), calls “metacognition,” or “the ability to think about our own thinking”—“a fragile, beautiful, and frankly bizarre feature of the human mind.”

A successful student uses metacognition to know when he needs to study more and when he’s studied enough: essentially, parts of his brain are monitoring other parts.

In everyday life, the biggest obstacle to metacognition is what psychologists call the “illusion of fluency.” As we perform increasingly familiar tasks, we monitor our performance less rigorously; this happens when we drive, or fold laundry, and also when we think thoughts we’ve thought many times before

The trick is to break the illusion of fluency, and to encourage an “awareness of ignorance.”

metacognition is a skill. Some people are better at it than others. Galef believes that, by “calibrating” our metacognitive minds, we can improve our performance and so become more rational

There are many calibration methods

nowing about what you know is Rationality 101. The advanced coursework has to do with changes in your knowledge.

Most of us stay informed straightforwardly—by taking in new information. Rationalists do the same, but self-consciously, with an eye to deliberately redrawing their mental maps.

The challenge is that news about distant territories drifts in from many sources; fresh facts and opinions aren’t uniformly significant. In recent decades, rationalists confronting this problem have rallied behind the work of Thomas Bayes

So-called Bayesian reasoning—a particular thinking technique, with its own distinctive jargon—has become de rigueur.

the basic idea is simple. When new information comes in, you don’t want it to replace old information wholesale. Instead, you want it to modify what you already know to an appropriate degree. The degree of modification depends both on your confidence in your preëxisting knowledge and on the value of the new data. Bayesian reasoners begin with what they call the “prior” probability of something being true, and then find out if they need to adjust it.

Bayesian reasoning is an approach to statistics, but you can use it to interpret all sorts of new information.

Studies have found that simply talking on the phone while walking actually slows down and disrupts our gait

When our brain is processing complex emotions and stressors, it hinders our ability to function at our best.

As I tell my students, remember to play your whole movie — not just the clip of your latest stumble on repeat

If a phone call is enough to disrupt our performance of basic tasks, we should be especially mindful of cognitive loads associated with grief, loss and general uncertainty about what is to come. All are major triggers for depression and anxiety, and profoundly affect our ability to perform even the most routine, practiced tasks.

holding tightly on to our latest failures is a common phenomenon, thanks to the recency effect — a cognitive bias that prioritizes our most recent experiences over past ones. This natural tendency sends our brain the wrong messages, and makes us forget how skilled, credentialed or qualified we really are

Adult depression and anxiety has climbed by 5.1 percent since the start of the pandemic.

Those things won’t matter nearly as much as their willingness to try again.

Social-media platforms are “preying on your insecurities; they’re preying on your temptations,” Jenn explained to me in an interview that shifted our parasocial connection, at least for an hour, to a mere relationship. “And, you know, I do play a role in this.” Jenn makes money through aspirational advertising, after all—a familiar part of any influencer’s job.

She’s pro–parasocial relationships, she explains to the camera, but only if we remain aware that we’re in one. “This relationship does not replace existing friendships, existing relationships,” she emphasizes. “This is all supplementary. Like, it should be in addition to your life, not a replacement.” I sat there watching her talk about parasocial relationships while absorbing the irony of being in one with her.

The open acknowledgment of social media’s inner workings, with content creators exposing the foundations of their content within the content itself, is what Alice Marwick, an associate communications professor at the University of North Carolina at Chapel Hill, described to me as “meta-content.”

Meta-content can be overt, such as the vlogger Casey Neistat wondering, in a vlog, if vlogging your life prevents you from being fully present in it;

But meta-content can also be subtle: a vlogger walking across the frame before running back to get the camera. Or influencers vlogging themselves editing the very video you’re watching, in a moment of space-time distortion.

Viewers don’t seem to care. We keep watching, fully accepting the performance. Perhaps that’s because the rise of meta-content promises a way to grasp authenticity by acknowledging artifice; especially in a moment when artifice is easier to create than ever before, audiences want to know what’s “real” and what isn’

“The idea of a space where you can trust no sources, there’s no place to sort of land, everything is put into question, is a very unsettling, unsatisfying way to live.

So we continue to search for, as Murray observes, the “agreed-upon things, our basic understandings of what’s real, what’s true.” But when the content we watch becomes self-aware and even self-critical, it raises the question of whether we can truly escape the machinations of social media. Maybe when we stare directly into the abyss, we begin to enjoy its company.

“The difference between BeReal and the social-media giants isn’t the former’s relationship to truth but the size and scale of its deceptions.” BeReal users still angle their camera and wait to take their daily photo at an aesthetic time of day. The snapshots merely remind us how impossible it is to stop performing online.

Jenn’s concern over the future of the internet stems, in part, from motherhood. She recently had a son, Lennon (whose first birthday party I watched on YouTube), and worries about the digital world he’s going to inherit.

Back in the age of MySpace, she had her own internet friends and would sneak out to parking lots at 1 a.m. to meet them in real life: “I think this was when technology was really used as a tool to connect us.” Now, she explained, it’s beginning to ensnare us. Posting content online is no longer a means to an end so much as the end itself.

We used to view influencers’ lives as aspirational, a reality that we could reach toward. Now both sides acknowledge that they’re part of a perfect product that the viewer understands is unattainable and the influencer acknowledges is not fully real.

“I forgot to say this to her in the interview, but I truly think that my videos are less about me and more of a reflection of where you are currently … You are kind of reflecting on your own life and seeing what resonates [with] you, and you’re discarding what doesn’t. And I think that’s what’s beautiful about it.”

meta-content is fundamentally a compromise. Recognizing the delusion of the internet doesn’t alter our course within it so much as remind us how trapped we truly are—and how we wouldn’t have it any other way.

on many important issues, civilization only destroys itself by extending the number of important operations that we can perform without thinking about them. On many issues, we want more thinking, not less.

Given that our online tools and platforms are built in a way to make our browsing experience as frictionless as possible, is it any surprise that so much of our personal information is disclosed without our ever realizing it?

Instead of having the designer think through all the moral and political implications of technology use before it reaches users — an impossible task — we must find a way to get users to do some of that thinking themselves.

most designers, following Wilde, think of technologies as nothing more than mechanical slaves that must maximize efficiency. But some are realizing that technologies don’t have to be just trivial problem-solvers: they can also be subversive troublemakers, making us question our habits and received ideas.

Recently, designers in Germany built devices — “transformational products,” they call them — that engage users in “conversations without words.” My favorite is a caterpillar-shaped extension cord. If any of the devices plugged into it are left in standby mode, the “caterpillar” starts twisting as if it were in pain. Does it do what normal extension cords do? Yes. But it also awakens users to the fact that the cord is simply the endpoint of a complex socio-technical system with its own politics and ethics. Before, designers have tried to conceal that system. In the future, designers will be obliged to make it visible.

Will such extra seconds of thought — nay, contemplation — slow down civilization? They well might. But who said that stopping to catch a breath on our way to the abyss is not a sensible strategy?

The iron law of Darwinian evolution is that everything that exists strives with all its power to reproduce, to extend life into the future, and that every feature of every creature can be explained as an adaptation toward this end. For the artist to deny any connection with the enterprise of life, then, is to assert his freedom from this universal imperative; to reclaim negatively the autonomy that evolution seems to deny to human beings. It is only because we can freely choose our own ends that we can decide not to live for life, but for some other value that we posit. The artist’s decision to produce spiritual offspring rather than physical ones is thus allied to the monk’s celibacy and the warrior’s death for his country, as gestures that deny the empire of mere life.

Animals produce beauty on their bodies; humans can also produce it in their artifacts. The natural inference, then, would be that art is a human form of sexual display, a way for males to impress females with spectacularly redundant creations.

For Darwin, the human sense of beauty was not different in kind from the bird’s.

Still, Darwin recognized that the human sense of beauty was mediated by “complex ideas and trains of thought,” which make it impossible to explain in terms as straightforward as a bird’s:

Put more positively, one might say that any given work of art can be discussed critically and historically, but not deduced from the laws of evolution.

with the rise of evolutionary psychology, it was only a matter of time before the attempt was made to explain art in Darwinian terms. After all, if ethics and politics can be explained by game theory and reciprocal altruism, there is no reason why aesthetics should be different: in each case, what appears to be a realm of human autonomy can be reduced to the covert expression of biological imperatives

Still, there is an unmistakable sense in discussions of Darwinian aesthetics that by linking art to fitness, we can secure it against charges of irrelevance or frivolousness—that mattering to reproduction is what makes art, or anything, really matter.

The first popular effort in this direction was the late Denis Dutton’s much-discussed book The Art Instinct, which appeared in 2009.

Dutton’s Darwinism was aesthetically conservative: “Darwinian aesthetics,” he wrote, “can restore the vital place of beauty, skill, and pleasure as high artistic values.” Dutton’s argument has recently been reiterated and refined by a number of new books,

“The universality of art and artistic behaviors, their spontaneous appearance everywhere across the globe ... and the fact that in most cases they can be easily recognized as artistic across cultures suggest that they derive from a natural, innate source: a universal human psychology.”

Again like language, art is universal in the sense that any local expression of it can be “learned” by anyone.

Yet earlier theorists of evolution were reluctant to say that art was an evolutionary adaptation like language, for the simple reason that it does not appear to be evolutionarily adaptive.

Stephen Jay Gould suggested that art was not an evolutionary adaptation but what he called a “spandrel”—that is, a showy but accidental by-product of other adaptations that were truly functiona

the very words “success” and “failure,” despite themselves, bring an emotive and ethical dimension into the discussion, so impossible is it for human beings to inhabit a valueless world. In the nineteenth century, the idea that fitness for survival was a positive good motivated social Darwinism and eugenics. Proponents of these ideas thought that in some way they were serving progress by promoting the flourishing of the human race, when the basic premise of Darwinism is that there is no such thing as progress or regress, only differential rates of reproduction

In particular, Darwin suggests that it is impossible to explain the history or the conventions of any art by the general imperatives of evolution

Boyd begins with the premise that human beings are pattern-seeking animals: both our physical perceptions and our social interactions are determined by our brain’s innate need to find and to

Art, then, can be defined as the calisthenics of pattern-finding. “Just as animal physical play refines performance, flexibility, and efficiency in key behaviors,” Boyd writes, “so human art refines our performance in our key perceptual and cognitive modes, in sight (the visual arts), sound (music), and social cognition (story). These three modes of art, I propose, are adaptations ... they show evidence of special design in humans, design that offers survival and especially reproductive advantages.”

make coherent patterns

The frustration has been compounded by the lack of recourse for Mr. Alefantis, his friends and employees. Yelp blocked the comments sections of Comet Ping Pong’s review page after reports of abusive comments and fake news in reviews. YouTube said it prohibits threats, harassment and hate speech and has tools for flagging violations and filing complaints for the site to take further action, but has largely not blocked comments on these videos. Twitter declined to comment, and Facebook did not have any further comment.

After employees and Mr. Alefantis complained to Reddit about how Comet Ping Pong was being targeted on the site, the #pizzagate discussion thread posted a warning that revealing personal information about individuals was prohibited.“We know that we have more work to do and we take our responsibility to address online abuse seriously,” Reddit said in a statement

The boost in productivity the researchers noticed happened because the music simply made the task less boring and kept the workers alert. This also helps explain later studies finding that music helped surgeons perform better.

When silence and music were put head to head in more cognitively complex tests, people did better in silence.

The more engaging the music is, the worse it is for concentration.

But lyric-free music is less distracting, and some of the people whose performance was improved may have come up with subconscious mental hacks to avoid getting sidetracked by music.

The reason this doesn’t work for most people, Levitin said, is most people can’t pay attention to very much at once. Lyrics can soak up precious attention, as can flashing lights or a really bad smell.

So, I asked Levitin, if listening to music while working is so bad, why do so many of us do it? Simple: We like it, and we can’t tell it’s messing us up.

“It depends on what you mean by artificial intelligence.”

Computers are flexible enough to model the strange evolved convolutions of our thought, and yet responsive only to precise instructions. So if the endeavor succeeds, it will be a double victory: we will finally come to know the exact mechanics of our selves—and we’ll have made intelligent machines.

Ever since he was about 14, when he found out that his youngest sister, Molly, couldn’t understand language, because she “had something deeply wrong with her brain” (her neurological condition probably dated from birth, and was never diagnosed), he had been quietly obsessed by the relation of mind to matter.

How could consciousness be physical? How could a few pounds of gray gelatin give rise to our very thoughts and selves?

Consciousness, Hofstadter wanted to say, emerged via just the same kind of “level-crossing feedback loop.”

In 1931, the Austrian-born logician Kurt Gödel had famously shown how a mathematical system could make statements not just about numbers but about the system itself.

But then AI changed, and Hofstadter didn’t change with it, and for that he all but disappeared.

By the early 1980s, the pressure was great enough that AI, which had begun as an endeavor to answer yes to Alan Turing’s famous question, “Can machines think?,” started to mature—or mutate, depending on your point of view—into a subfield of software engineering, driven by applications.

Take Deep Blue, the IBM supercomputer that bested the chess grandmaster Garry Kasparov. Deep Blue won by brute force.

Hofstadter wanted to ask: Why conquer a task if there’s no insight to be had from the victory? “Okay,” he says, “Deep Blue plays very good chess—so what? Does that tell you something about how we play chess? No. Does it tell you about how Kasparov envisions, understands a chessboard?”

AI started working when it ditched humans as a model, because it ditched them. That’s the thrust of the analogy: Airplanes don’t flap their wings; why should computers think?

It’s a compelling point. But it loses some bite when you consider what we want: a Google that knows, in the way a human would know, what you really mean when you search for something

Cognition is recognition,” he likes to say. He describes “seeing as” as the essential cognitive act: you see some lines a

How do you make a search engine that understands if you don’t know how you understand?

s “an A,” you see a hunk of wood as “a table,” you see a meeting as “an emperor-has-no-clothes situation” and a friend’s pouting as “sour grapes”

That’s what it means to understand. But how does understanding work?

analogy is “the fuel and fire of thinking,” the bread and butter of our daily mental lives.

there’s an analogy, a mental leap so stunningly complex that it’s a computational miracle: somehow your brain is able to strip any remark of the irrelevant surface details and extract its gist, its “skeletal essence,” and retrieve, from your own repertoire of ideas and experiences, the story or remark that best relates.

in Hofstadter’s telling, the story goes like this: when everybody else in AI started building products, he and his team, as his friend, the philosopher Daniel Dennett, wrote, “patiently, systematically, brilliantly,” way out of the light of day, chipped away at the real problem. “Very few people are interested in how human intelligence works,”

For more than 30 years, Hofstadter has worked as a professor at Indiana University at Bloomington

The quick unconscious chaos of a mind can be slowed down on the computer, or rewound, paused, even edited

project out of IBM called Candide. The idea behind Candide, a machine-translation system, was to start by admitting that the rules-based approach requires too deep an understanding of how language is produced; how semantics, syntax, and morphology work; and how words commingle in sentences and combine into paragraphs—to say nothing of understanding the ideas for which those words are merely conduits.

, Hofstadter directs the Fluid Analogies Research Group, affectionately known as FARG.

Parts of a program can be selectively isolated to see how it functions without them; parameters can be changed to see how performance improves or degrades. When the computer surprises you—whether by being especially creative or especially dim-witted—you can see exactly why.

When you read Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought, which describes in detail this architecture and the logic and mechanics of the programs that use it, you wonder whether maybe Hofstadter got famous for the wrong book.

ut very few people, even admirers of GEB, know about the book or the programs it describes. And maybe that’s because FARG’s programs are almost ostentatiously impractical. Because they operate in tiny, seemingly childish “microdomains.” Because there is no task they perform better than a human.

“The entire effort of artificial intelligence is essentially a fight against computers’ rigidity.”

“Nobody is a very reliable guide concerning activities in their mind that are, by definition, subconscious,” he once wrote. “This is what makes vast collections of errors so important. In an isolated error, the mechanisms involved yield only slight traces of themselves; however, in a large collection, vast numbers of such slight traces exist, collectively adding up to strong evidence for (and against) particular mechanisms.

So IBM threw that approach out the window. What the developers did instead was brilliant, but so straightforward,

The technique is called “machine learning.” The goal is to make a device that takes an English sentence as input and spits out a French sentence

What you do is feed the machine English sentences whose French translations you already know. (Candide, for example, used 2.2 million pairs of sentences, mostly from the bilingual proceedings of Canadian parliamentary debates.)

By repeating this process with millions of pairs of sentences, you will gradually calibrate your machine, to the point where you’ll be able to enter a sentence whose translation you don’t know and get a reasonable resul

Google Translate team can be made up of people who don’t speak most of the languages their application translates. “It’s a bang-for-your-buck argument,” Estelle says. “You probably want to hire more engineers instead” of native speakers.

But the need to serve 1 billion customers has a way of forcing the company to trade understanding for expediency. You don’t have to push Google Translate very far to see the compromises its developers have made for coverage, and speed, and ease of engineering. Although Google Translate captures, in its way, the products of human intelligence, it isn’t intelligent itself.

“Did we sit down when we built Watson and try to model human cognition?” Dave Ferrucci, who led the Watson team at IBM, pauses for emphasis. “Absolutely not. We just tried to create a machine that could win at Jeopardy.”

For Ferrucci, the definition of intelligence is simple: it’s what a program can do. Deep Blue was intelligent because it could beat Garry Kasparov at chess. Watson was intelligent because it could beat Ken Jennings at Jeopardy.

“There’s a limited number of things you can do as an individual, and I think when you dedicate your life to something, you’ve got to ask yourself the question: To what end? And I think at some point I asked myself that question, and what it came out to was, I’m fascinated by how the human mind works, it would be fantastic to understand cognition, I love to read books on it, I love to get a grip on it”—he called Hofstadter’s work inspiring—“but where am I going to go with it? Really what I want to do is build computer systems that do something.

Peter Norvig, one of Google’s directors of research, echoes Ferrucci almost exactly. “I thought he was tackling a really hard problem,” he told me about Hofstadter’s work. “And I guess I wanted to do an easier problem.”

Of course, the folly of being above the fray is that you’re also not a part of it

As our machines get faster and ingest more data, we allow ourselves to be dumber. Instead of wrestling with our hardest problems in earnest, we can just plug in billions of examples of them.

Hofstadter hasn’t been to an artificial-intelligence conference in 30 years. “There’s no communication between me and these people,” he says of his AI peers. “None. Zero. I don’t want to talk to colleagues that I find very, very intransigent and hard to convince of anything

Everything from plate tectonics to evolution—all those ideas, someone had to fight for them, because people didn’t agree with those ideas.

Academia is not an environment where you just sit in your bath and have ideas and expect everyone to run around getting excited. It’s possible that in 50 years’ time we’ll say, ‘We really should have listened more to Doug Hofstadter.’ But it’s incumbent on every scientist to at least think about what is needed to get people to understand the ideas.”

While she says her parents are not overbearing, she relishes their praise for performing well. “Hearing my parents talk about me in a positive way, or hearing other parents talk about their kids doing well in academics or extracurriculars, that’s where I got some of the expectations for myself,” she said. “It was like self-fulfillment: I’d feel fulfilled and happy when other people were happy with what I’m doing, or expectations they have are met.”

Getting a B can cause some students to fall apart, she said. “What you and I would call disappointments in life, to them feel like big failures.”

a shift in how some young adults cope with challenges. “A small setback used to mean disappointment, or having that feeling of needing to try harder next time,” he said. Now? “For some students, a mistake has incredible meaning.”

The existential question “Why am I here?” is usually followed by the equally confounding “How am I doing?” In 1954, the social psychologist Leon Festinger put forward the social comparison theory, which posits that we try to determine our worth based on how we stack up against others.

In the era of social media, such comparisons take place on a screen with carefully curated depictions that don’t provide the full picture. Mobile devices escalate the comparisons from occasional to nearly constant.

When students remark during a counseling session that everyone else on campus looks happy, he tells them: “I walk around and think, ‘That one’s gone to the hospital. That person has an eating disorder. That student just went on antidepressants.’ As a therapist, I know that nobody is as happy or as grown-up as they seem on the outside.”

Madison Holleran’s suicide provided what might be the ultimate contrast between a shiny Instagram feed and interior darkness. Ms. Holleran posted images that show her smiling, dappled in sunshine or kicking back at a party. But according to her older sister, Ashley, Madison judged her social life as inferior to what she saw in the online posts of her high school friends

These cultural dynamics of perfectionism and overindulgence have now combined to create adolescents who are ultra-focused on success but don’t know how to fail.

Julie Lythcott-Haims watched the collision of these two social forces up close. In meetings with students, she would ask what she considered simple questions and they would become paralyzed, unable to express their desires and often discovering midconversation that they were on a path that they didn’t even like.

“They could say what they’d accomplished, but they couldn’t necessarily say who they were,”

She was also troubled by the growing number of parents who not only stayed in near-constant cellphone contact with their offspring but also showed up to help them enroll in classes, contacted professors and met with advisers (illustrating the progression from helicopter to lawn mower parents, who go beyond hovering to clear obstacles out of their child’s way). But what she found most disconcerting was that students, instead of being embarrassed, felt grateful. Penn researchers studying friendship have found that students’ best friends aren’t classmates or romantic partners, but parents.

Eventually she came to view her students’ lack of self-awareness, inability to make choices and difficulty coping with setbacks as a form of “existential impotence,” a direct result of a well-meaning but misguided approach to parenting that focuses too heavily on external measures of character.

“The Drama of the Gifted Child: The Search for the True Self.” In the book, published in 1979 and translated into 30 languages, Ms. Miller documents how some especially intelligent and sensitive children can become so attuned to parents’ expectations that they do whatever it takes to fulfill those expectations — at the expense of their own feelings and needs. This can lead to emotional emptiness and isolation

“In what is described as depression and experienced as emptiness, futility, fear of impoverishment, and loneliness,” she wrote, “can usually be recognized as the tragic loss of the self in childhood.”

Expecting nothing in return, I was greatly relieved when my doorbell rang and the neighbor thanked me warmly for what I had said and done.

as an excuse for hurtful behavior.

She disputes popular thinking that failing to forgive is bad for one’s health and can lead to a life mired in bitterness and hate.

Offering an apology is an admission of guilt that admittedly leaves people vulnerable. There’s no guarantee as to how it will be received.

apologies followed by rationalizations are “never satisfying” and can even be harmful.

‘I’m sorry’ are the two most healing words in the English language,” she said. “The courage to apologize wisely and well is not just a gift to the injured person, who can then feel soothed and released from obsessive recriminations, bitterness and corrosive anger.

By emphasizing a focus on the here and now, it trains the mind to stay on task and avoid distraction.

“Your ability to recognize what your mind is engaging with, and control that, is really a core strength,” said Peter Malinowski, a psychologist and neuroscientist at Liverpool John Moores University in England. “For some people who begin mindfulness training, it’s the first time in their life where they realize that a thought or emotion is not their only reality, that they have the ability to stay focused on something else, for instance their breathing, and let that emotion or thought just pass by.”

the higher adults scored on a measurement of mindfulness, the worse they performed on tests of implicit learning — the kind that underlies all sorts of acquired skills and habits but that occurs without conscious awareness.

he found that having participants spend a brief period of time on an undemanding task that maximizes mind wandering improved their subsequent performance on a test of creativity. In a follow-up study, he reported that physicists and writers alike came up with their most insightful ideas while spacing out.

The trick is knowing when mindfulness is called for and when it’s not.

one of the most surprising findings of recent mindfulness studies is that it could have unwanted side effects. Raising roadblocks to the mind’s peregrinations could, after all, prevent the very sort of mental vacations that lead to epiphanies.

“There’s so much our brain is doing when we’re not aware of it,” said the study’s leader, Chelsea Stillman, a doctoral candidate. “We know that being mindful is really good for a lot of explicit cognitive functions. But it might not be so useful when you want to form new habits.” Learning to ride a bicycle, speak grammatically or interpret the meaning of people’s facial expressions are three examples of knowledge we acquire through implicit learning

The economics community just hasn't spent much time over the past couple of decades focusing on the effect that machine intelligence is likely to have on the labor marke

The Digital Revolution is different because computers can perform cognitive tasks too, and that means machines will eventually be able to run themselves. When that happens, they won't just put individuals out of work temporarily. Entire classes of workers will be out of work permanently. In other words, the Luddites weren't wrong. They were just 200 years too early

Slowly but steadily, labor's share of total national income has gone down, while the share going to capital owners has gone up. The most obvious effect of this is the skyrocketing wealth of the top 1 percent, due mostly to huge increases in capital gains and investment income.

Robotic pets are growing so popular that Sherry Turkle, an MIT professor who studies the way we interact with technology, is uneasy about it: "The idea of some kind of artificial companionship," she says, "is already becoming the new normal."

robots will take over more and more jobs. And guess who will own all these robots? People with money, of course. As this happens, capital will become ever more powerful and labor will become ever more worthless. Those without money—most of us—will live on whatever crumbs the owners of capital allow us.

Economist Paul Krugman recently remarked that our long-standing belief in skills and education as the keys to financial success may well be outdated. In a blog post titled "Rise of the Robots," he reviewed some recent economic data and predicted that we're entering an era where the prime cause of income inequality will be something else entirely: capital vs. labor.

while it's easy to believe that some jobs can never be done by machines—do the elderly really want to be tended by robots?—that may not be true.

Third, as more people compete for fewer jobs, we'd expect to see middle-class incomes flatten in a race to the bottom.

The question we want to answer is simple: If CBTC is already happening—not a lot, but just a little bit—what trends would we expect to see? What are the signs of a computer-driven economy?

if automation were displacing labor, we'd expect to see a steady decline in the share of the population that's employed.

Second, we'd expect to see fewer job openings than in the past.

In the economics literature, the increase in the share of income going to capital owners is known as capital-biased technological change

Fourth, with consumption stagnant, we'd expect to see corporations stockpile more cash and, fearing weaker sales, invest less in new products and new factories

Fifth, as a result of all this, we'd expect to see labor's share of national income decline and capital's share rise.

We're already seeing them, and not just because of the crash of 2008. They started showing up in the statistics more than a decade ago. For a while, though, they were masked by the dot-com and housing bubbles, so when the financial crisis hit, years' worth of decline was compressed into 24 months. The trend lines dropped off the cliff.

Corporate executives should worry too. For a while, everything will seem great for them: Falling labor costs will produce heftier profits and bigger bonuses. But then it will all come crashing down. After all, robots might be able to produce goods and services, but they can't consume them

in another sense, we should be very alarmed. It's one thing to suggest that robots are going to cause mass unemployment starting in 2030 or so. We'd have some time to come to grips with that. But the evidence suggests that—slowly, haltingly—it's happening already, and we're simply not prepared for it.

the first jobs to go will be middle-skill jobs. Despite impressive advances, robots still don't have the dexterity to perform many common kinds of manual labor that are simple for humans—digging ditches, changing bedpans. Nor are they any good at jobs that require a lot of cognitive skill—teaching classes, writing magazine articles

in the middle you have jobs that are both fairly routine and require no manual dexterity. So that may be where the hollowing out starts: with desk jobs in places like accounting or customer support.

In fact, there's even a digital sports writer. It's true that a human being wrote this story—ask my mother if you're not sure—but in a decade or two I might be out of a job too

Doctors should probably be worried as well. Remember Watson, the Jeopardy!-playing computer? It's now being fed millions of pages of medical information so that it can help physicians do a better job of diagnosing diseases. In another decade, there's a good chance that Watson will be able to do this without any human help at all.

Take driverless cars.

The next step might be passenger vehicles on fixed routes, like airport shuttles. Then long-haul trucks. Then buses and taxis. There are 2.5 million workers who drive trucks, buses, and taxis for a living, and there's a good chance that, one by one, all of them will be displaced

There will be no place to go but the unemployment lin

we'll need to let go of some familiar convictions. Left-leaning observers may continue to think that stagnating incomes can be improved with better education and equality of opportunity. Conservatives will continue to insist that people without jobs are lazy bums who shouldn't be coddled. They'll both be wrong.

The modern economy is complex, and most of these trends have multiple causes.

we'll probably have only a few options open to us. The simplest, because it's relatively familiar, is to tax capital at high rates and use the money to support displaced workers. In other words, as The Economist's Ryan Avent puts it, "redistribution, and a lot of it."

would we be happy in a society that offers real work to a dwindling few and bread and circuses for the rest?

Most likely, owners of capital would strongly resist higher taxes, as they always have, while workers would be unhappy with their enforced idleness. Still, the ancient Romans managed to get used to it—with slave labor playing the role of robots—and we might have to, as well.

 economist Noah Smith suggests that we might have to fundamentally change the way we think about how we share economic growth. Right now, he points out, everyone is born with an endowment of labor by virtue of having a body and a brain that can be traded for income. But what to do when that endowment is worth a fraction of what it is today? Smith's suggestion: "Why not also an endowment of capital? What if, when each citizen turns 18, the government bought him or her a diversified portfolio of equity?"

In simple terms, if owners of capital are capturing an increasing fraction of national income, then that capital needs to be shared more widely if we want to maintain a middle-class society.

it's time to start thinking about our automated future in earnest. The history of mass economic displacement isn't encouraging—fascists in the '20s, Nazis in the '30s—and recent high levels of unemployment in Greece and Italy have already produced rioting in the streets and larger followings for right-wing populist parties. And that's after only a few years of misery.

When the robot revolution finally starts to happen, it's going to happen fast, and it's going to turn our world upside down. It's easy to joke about our future robot overlords—R2-D2 or the Terminator?—but the challenge that machine intelligence presents really isn't science fiction anymore. Like Lake Michigan with an inch of water in it, it's happening around us right now even if it's hard to see

A robotic paradise of leisure and contemplation eventually awaits us, but we have a long and dimly lit tunnel to navigate before we get there.