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Rabies moves at a predictable rate, replicating every eight to 10 hours, moving rapidly through chains of neurons and revealing a network. The researchers could allow the virus to move up the nervous system and reach the brain but could sacrifice the monkey before it showed any symptoms of infection.

When the virus has had enough time to travel a predictable distance, the researchers anesthetize the animal, wash out its blood, perfuse the central nervous system with fixatives, and use antibodies to detect where the virus has spread. The kills were timed to various stages to create a map. By the time you’ve gone through several sets of synapses that mapping is an enormous task. There’s an exponential increase in the number of neurons.

the researchers were astounded at what they saw. The motor areas in the brain connect to the adrenal glands. In the primary motor cortex of the brain, there’s a map of the human body—areas that correspond to the face, arm, and leg area, as well as a region that controls the axial body muscles (known to many people now as “the core”).

“Something about axial control has an impact on stress responses,” Strick reasons. “There’s all this evidence that core strengthening has an impact on stress. And when you see somebody that's depressed or stressed out, you notice changes in their posture. When you stand up straight, it has an effect on how you project yourself and how you feel.  Well, lo and behold, core muscles have an impact on stress. And I suspect that if you activate core muscles inappropriately with poor posture, that’s going to have an impact on stress.”

“These neural pathways might explain our intuitive sense for why there are many different strategies for coping with stress,” said Bruno. “I like the examples they give in the paper—that maybe this is why yoga and pilates are so successful. But there are lots of other things where people talk about mental imagery and all sorts of other ways that people deal with stress. I think having so many neural pathways having direct lines to the stress control system, that’s really interesting.”

Bruno specializes more in sensory neuroscience, so he read a more into the findings in the primary somatosensory cortex. Some of these tactile areas in the brain seem to be providing as much input to the adrenal medulla as the cortical areas. “To me that's really new and interesting,” said Bruno. “It might explain why certain sensations we find very relaxing or stressful.”

“It's not clear to me—from our work, and from their work—that what we call motor cortex is really motor cortex,” he said. “Maybe the primary sensory cortex is doing something more than we thought. When I see results like these, I go, hm, maybe these areas aren’t so simple.”

With this come implications for what’s currently known as “psychosomatic illness”—how the mind has an impact over organ functions. The name tends to have a bad connotation. The notion that this mind-body connection isn’t really real; that psychosomatic illnesses are “all in your head.” Elaborate connections like this would explain that, yes, it is all in your head. The fact that cortical areas in the brain that have multi-synaptic connections that control organ function could strip the negative connotations

As he put it, “How we move, think, and feel have an impact on the stress response through real neural connections.”

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

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

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.

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.

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.

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.

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.

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.

"The twenties were the highest peak of joy-related words that we see," he says. "They really were roaring." But then there came 1941, which, of course, marked the beginning of America's entry into World War II. It doesn't take a historian to see that peaks and valleys like these roughly mirror the major economic and social events of the century. "In 1941, sadness is at its peak," Bently says.

They weren't just novels or books about current events, Bentley says. Many were books without clear emotional content — technical manuals about plants and animals, for example, or automotive repair guides. "It's not like the change in emotion is because people are writing about the Depression, and people are writing about the war," he says. "There might be a little bit of that, but this is just, kind of, averaged over all books and it's just kind of creeping in."

Generally speaking the usage of these commonly known emotion words has been in decline over the 20th century," Bentley says. We used words that expressed our emotions less in the year 2000 than we did 100 years earlier — words about sadness, and joy, and anger, and disgust and surprise. In fact, there is only one exception that Bentley and his colleagues found: fear. "The fear-related words start to increase just before the 1980s," he says.

For psychologists, he says, there are only a handful of ways to try to understand what is actually going on with somebody emotionally. "One is what a person says," Pennebaker explains, "kind of the 'self report' of emotion. Another might be the physiological links, and the third is what slips out when they're talking to other people, when they're writing a book or something like that."

Using the traditional privacy idea that once something's public, it is public for any purpose, you're lead down a very narrow path of reasoning about this app's appropriateness and what the services it was built on could do about it.

using Nissenbaum's theory, the bad feelings that people have around the app make sense: People gave data to Foursquare or Facebook in one context and then it showed up in another context that they weren't expecting.

In the United States, 81 percent replied in the affirmative

six to ten months children have already learned to be sensitive to the basic sounds, known as phonemes, that matter in their native language.

language requires real-time mappings between words and their meanings. This requires that the sounds heard in speech – decoded in the auditory cortex – must be integrated with knowledge about what they mean – in the frontal cortex.

Modern theories on connectionism – the idea that knowledge is distributed across different parts of the brain and not tucked into dedicated modules like Broca’s area – have compelled researchers to take a closer look.

Mandarin Chinese is a tonal language in which the same basic sounds can refer to vastly different things based on the tone with which it is spoken

non-tonal language such as English, tone might convey emotional information about the speaker, but indicates nothing about the meaning of the word that is spoken

found that these differences between Mandarin Chinese and English change the way the brain’s networks work.

researchers took advantage of the basic differences between Mandarin Chinese and English to investigate the differences between the language networks of native speakers of tonal and non-tonal languages. Thirty native Chinese speakers were matched on age, gender, and handedness (they were all right-handed) with a sample of native English speakers. All participants listened to intelligible and unintelligible speech and were asked to judge the gender of the speaker.

The first difference was the operation of the brain networks shared by English and Chinese speakers

English speakers showed stronger connectivity leading from Wernicke’s area to Broca’s area. This increased connectivity was attributed to English relying more heavily on phonological information, or sounds rather than tones.

Chinese speakers had stronger connections leading from an area of the brain called the anterior superior temporal gyrus – which has been identified as a “semantic hub” critical in supporting language – to both Broca’s and Wernicke’s area.

increased connectivity is attributed to the enhanced mapping of sound and meaning going on in people who speak tonal languages.

second difference showed activation in an area of the brain’s right hemisphere, but only among the Chinese speakers

findings emphasise the importance of developing a bilateral network between the two brain hemispheres to speak and understand languages, particularly for tonal languages like Mandarin Chinese.

Aiello and co were careful to ensure that the crawler did not engage with anybody on the network in any way other than to visit his or her node. Their idea was to isolate a single, minimal social activity and test how effective it was in gaining popularity.

They began to record the reactions to lajello’s visits including the number of messages it received, their content, the links it received and how they varied over time and so on.

By December 2011, lajello’s profile had become one of the most popular on the entire social network. It had received more than 66,000 visits as well as 2435 messages from more than 1200 different people.  In terms of the number of different message received, a well-known writer was the most popular on this network but lajello was second.

“Our experiment gives strong support to the thesis that popularity can be gained just with continuous “social probing”,” conclude Aiello and co. “We have shown that a very simple spambot can attract great interest even without emulating any aspects of typical human behavior.”

Having created all this popularity, Aiello and co wanted to find out how influential the spam bot could be. So they started using the bot to send recommendations to users on who else to connect to.The spam bot could either make a recommendation chosen at random or one that was carefully selected by a recommendation engine. It then made its recommendations to users that had already linked to lajello and to other users chosen at random.

“Among the 361 users who created at least one social connection in the 36 hours after the recommendation, 52 per cent followed suggestion given by the bot,” they say.

shows just how easy it is for an automated bot to play a significant role in a social network. Popularity appears easy to buy using nothing more than page visits, at least in this experiment. What is more, this popularity can be easily translated into influence

It is not hard to see the significance of this work. Social bots are a fact of life on almost every social network and many have become so sophisticated they are hard to distinguish from humans. If the simplest of bots created by Aiello and co can have this kind of impact, it is anybody’s guess how more advanced bots could influence everything from movie reviews and Wikipedia entries to stock prices and presidential elections.

The problem, he says, is that we don’t have a watertight definition of what a country is. “Which as a geographer, is kind of shocking

The globe, it turns out, is full of small (and not so small) regions that have all the trappings of a real country

and are ignored on most world maps.

Middleton, a geographer at the University of Oxford, has now charted these hidden lands in his new book, An Atlas of Countries that Don’t Exist

Middleton’s quest began, appropriately enough, with Narnia

a defined territory, a permanent population, a government, and “the capacity to enter into relations with other states”.

In Australia, meanwhile, the Republic of Murrawarri was founded in 2013, after the indigenous tribe wrote a letter to Queen Elizabeth II asking her to prove her legitimacy to govern their land.

Yet many countries that meet these criteria aren‘t members of the United Nations (commonly accepted as the final seal of a country’s statehood).

many of them are instead members of the “Unrepresented United Nations – an alternative body to champion their rights.

A handful of the names will be familiar to anyone who has read a newspaper: territories such as Taiwan, Tibet, Greenland, and Northern Cyprus.

The others are less famous, but they are by no means less serious

One of the most troubling histories, he says, concerns the Republic of Lakotah (with a population of 100,000). Bang in the centre of the United States of America (just east of the Rocky Mountains), the republic is an attempt to reclaim the sacred Black Hills for the Lakota Sioux tribe.

Their plight began in the 18th Century, and by 1868 they had finally signed a deal with the US government that promised the right to live on the Black Hills. Unfortunately, they hadn’t accounted for a gold rush

Similar battles are being fought across every continent.

In fact, you have almost certainly, unknowingly, visited one.

Christiania, an enclave in the heart of Copenhagen.

On 26 September that year, they declared it independent, with its own “direct democracy”, in which each of the inhabitants (now numbering 850) could vote on any important matter.

a blind eye to the activities

perhaps we need to rethink the concept of the nation-state altogether? He points to Antarctica, a continent shared peacefully among the international community

The last pages of Middleton’s Atlas contain two radical examples that question everything we think we mean by the word ‘country’.

“They all raise the possibility that countries as we know them are not the only legitimate basis for ordering the planet,

David Marr, a neuroscientist colleague of Chomsky's at MIT, defined a general framework for studying complex biological systems (like the brain) in his influential book Vision,

a complex biological system can be understood at three distinct levels. The first level ("computational level") describes the input and output to the system, which define the task the system is performing. In the case of the visual system, the input might be the image projected on our retina and the output might our brain's identification of the objects present in the image we had observed. The second level ("algorithmic level") describes the procedure by which an input is converted to an output, i.e. how the image on our retina can be processed to achieve the task described by the computational level. Finally, the third level ("implementation level") describes how our own biological hardware of cells implements the procedure described by the algorithmic level.

The emphasis here is on the internal structure of the system that enables it to perform a task, rather than on external association between past behavior of the system and the environment. The goal is to dig into the "black box" that drives the system and describe its inner workings, much like how a computer scientist would explain how a cleverly designed piece of software works and how it can be executed on a desktop computer.

As written today, the history of cognitive science is a story of the unequivocal triumph of an essentially Chomskyian approach over Skinner's behaviorist paradigm -- an achievement commonly referred to as the "cognitive revolution,"

While this may be a relatively accurate depiction in cognitive science and psychology, behaviorist thinking is far from dead in related disciplines. Behaviorist experimental paradigms and associationist explanations for animal behavior are used routinely by neuroscientists

Chomsky critiqued the field of AI for adopting an approach reminiscent of behaviorism, except in more modern, computationally sophisticated form. Chomsky argued that the field's heavy use of statistical techniques to pick regularities in masses of data is unlikely to yield the explanatory insight that science ought to offer. For Chomsky, the "new AI" -- focused on using statistical learning techniques to better mine and predict data -- is unlikely to yield general principles about the nature of intelligent beings or about cognition.

Behaviorist principles of associations could not explain the richness of linguistic knowledge, our endlessly creative use of it, or how quickly children acquire it with only minimal and imperfect exposure to language presented by their environment.

it has been argued in my view rather plausibly, though neuroscientists don't like it -- that neuroscience for the last couple hundred years has been on the wrong track.

Implicit in this endeavor is the assumption that with enough sophisticated statistical tools and a large enough collection of data, signals of interest can be weeded it out from the noise in large and poorly understood biological systems.

Brenner, a contemporary of Chomsky who also participated in the same symposium on AI, was equally skeptical about new systems approaches to understanding the brain. When describing an up-and-coming systems approach to mapping brain circuits called Connectomics, which seeks to map the wiring of all neurons in the brain (i.e. diagramming which nerve cells are connected to others), Brenner called it a "form of insanity."

These debates raise an old and general question in the philosophy of science: What makes a satisfying scientific theory or explanation, and how ought success be defined for science?

Ever since Isaiah Berlin's famous essay, it has become a favorite pastime of academics to place various thinkers and scientists on the "Hedgehog-Fox" continuum: the Hedgehog, a meticulous and specialized worker, driven by incremental progress in a clearly defined field versus the Fox, a flashier, ideas-driven thinker who jumps from question to question, ignoring field boundaries and applying his or her skills where they seem applicable.

Chomsky's work has had tremendous influence on a variety of fields outside his own, including computer science and philosophy, and he has not shied away from discussing and critiquing the influence of these ideas, making him a particularly interesting person to interview.

If you take a look at the progress of science, the sciences are kind of a continuum, but they're broken up into fields. The greatest progress is in the sciences that study the simplest systems. So take, say physics -- greatest progress there. But one of the reasons is that the physicists have an advantage that no other branch of sciences has. If something gets too complicated, they hand it to someone else.

If a molecule is too big, you give it to the chemists. The chemists, for them, if the molecule is too big or the system gets too big, you give it to the biologists. And if it gets too big for them, they give it to the psychologists, and finally it ends up in the hands of the literary critic, and so on.

An unlikely pair, systems biology and artificial intelligence both face the same fundamental task of reverse-engineering a highly complex system whose inner workings are largely a mystery

neuroscience developed kind of enthralled to associationism and related views of the way humans and animals work. And as a result they've been looking for things that have the properties of associationist psychology.

. The firms’ employees, who often overlap, had contact in 2014 and 2015 with executives from Lukoil, the Russian oil giant.

Lukoil was interested in how data was used to target American voters, according to two former company insiders who said there were at least three meetings with Lukoil executives in London and Turkey.

Cambridge Analytica also included extensive questions about Russia’s president, Vladimir V. Putin, in surveys it was carrying out in American focus groups in 2014. It is not clear what — or which client — prompted the line of questioning, which asked for views on topics ranging from Mr. Putin’s popularity to Russian expansionism.

On two promotional documents obtained by The New York Times, SCL said it did business in Russia. In both documents, the country is highlighted on world maps that specify the location of SCL clients, with one of the maps noting that the clients were for the firm’s elections division. In a statement, SCL said an employee had done “commercial work” about 25 years ago “for a private company in Russia.”

Asked about the Russian oil company, a spokesman for SCL said that in 2014 the firm’s commercial division “discussed helping Lukoil Turkey better engage with its loyalty-card customers at gas stations.” The spokesman said SCL was not ultimately hired.

But Christopher Wylie, who helped found Cambridge Analytica and develop the company’s voter-profiling technology, said Lukoil showed interest in how the company used data to tailor messaging to American voters.

“I remember being super confused,” said Mr. Wylie, who took part in one of the Lukoil meetings.“I kept asking Alexander, ‘Can you explain to me what they want?’” he said, referring to Mr. Nix. “I don’t understand why Lukoil wants to know about political targeting in America.”

“We’re sending them stuff about political targeting — they then come and ask more about political targeting,” Mr. Wylie said, adding that Lukoil “just didn’t seem to be interested” in how the techniques could be used commercially.

A second person familiar with the discussions backed up Mr. Wylie’s account, but spoke on the condition of anonymity because of a confidentiality agreement.

Though Lukoil is not state-owned, it depends on Kremlin support, and its chief executive, Vagit Alekperov, has met with Mr. Putin on a number of occasions. Reuters reported last year that Lukoil and other companies received instructions from the state energy ministry on providing news stories favorable to Russian leadership.

By removing the tangible product from the center of commerce, surveillance capitalism upsets the equilibrium. Whenever we use free apps and online services, it’s often said, we become the products, our attention harvested and sold to advertisers

this truism gets it wrong. Surveillance capitalism’s real products, vaporous but immensely valuable, are predictions about our future behavior — what we’ll look at, where we’ll go, what we’ll buy, what opinions we’ll hold — that internet companies derive from our personal data and sell to businesses, political operatives, and other bidders.

Unlike financial derivatives, which they in some ways resemble, these new data derivatives draw their value, parasite-like, from human experience.To the Googles and Facebooks of the world, we are neither the customer nor the product. We are the source of what Silicon Valley technologists call “data exhaust” — the informational byproducts of online activity that become the inputs to prediction algorithms

Another 2015 study, appearing in the Journal of Computer-Mediated Communication, showed that when people hear their phone ring but are unable to answer it, their blood pressure spikes, their pulse quickens, and their problem-solving skills decline.

The smartphone has become a repository of the self, recording and dispensing the words, sounds and images that define what we think, what we experience and who we are. In a 2015 Gallup survey, more than half of iPhone owners said that they couldn’t imagine life without the device.

So what happens to our minds when we allow a single tool such dominion over our perception and cognition?

Not only do our phones shape our thoughts in deep and complicated ways, but the effects persist even when we aren’t using the devices. As the brain grows dependent on the technology, the research suggests, the intellect weakens.

he has seen mounting evidence that using a smartphone, or even hearing one ring or vibrate, produces a welter of distractions that makes it harder to concentrate on a difficult problem or job. The division of attention impedes reasoning and performance.

internet companies operate in what Zuboff terms “extreme structural independence from people.” When databases displace goods as the engine of the economy, our own interests, as consumers but also as citizens, cease to be part of the negotiation. We are no longer one of the forces guiding the market’s invisible hand. We are the objects of surveillance and control.

Social skills and relationships seem to suffer as well.

In both tests, the subjects whose phones were in view posted the worst scores, while those who left their phones in a different room did the best. The students who kept their phones in their pockets or bags came out in the middle. As the phone’s proximity increased, brainpower decreased.

In subsequent interviews, nearly all the participants said that their phones hadn’t been a distraction—that they hadn’t even thought about the devices during the experiment. They remained oblivious even as the phones disrupted their focus and thinking.

The researchers recruited 520 undergraduates at UCSD and gave them two standard tests of intellectual acuity. One test gauged “available working-memory capacity,” a measure of how fully a person’s mind can focus on a particular task. The second assessed “fluid intelligence,” a person’s ability to interpret and solve an unfamiliar problem. The only variable in the experiment was the location of the subjects’ smartphones. Some of the students were asked to place their phones in front of them on their desks; others were told to stow their phones in their pockets or handbags; still others were required to leave their phones in a different room.

the “integration of smartphones into daily life” appears to cause a “brain drain” that can diminish such vital mental skills as “learning, logical reasoning, abstract thought, problem solving, and creativity.”

 Smartphones have become so entangled with our existence that, even when we’re not peering or pawing at them, they tug at our attention, diverting precious cognitive resources. Just suppressing the desire to check our phone, which we do routinely and subconsciously throughout the day, can debilitate our thinking.

They found that students who didn’t bring their phones to the classroom scored a full letter-grade higher on a test of the material presented than those who brought their phones. It didn’t matter whether the students who had their phones used them or not: All of them scored equally poorly.

A study of nearly a hundred secondary schools in the U.K., published last year in the journal Labour Economics, found that when schools ban smartphones, students’ examination scores go up substantially, with the weakest students benefiting the most.

Data, the novelist and critic Cynthia Ozick once wrote, is “memory without history.” Her observation points to the problem with allowing smartphones to commandeer our brains

Because smartphones serve as constant reminders of all the friends we could be chatting with electronically, they pull at our minds when we’re talking with people in person, leaving our conversations shallower and less satisfying.

In a 2013 study conducted at the University of Essex in England, 142 participants were divided into pairs and asked to converse in private for ten minutes. Half talked with a phone in the room, half without a phone present. The subjects were then given tests of affinity, trust and empathy. “The mere presence of mobile phones,” the researchers reported in the Journal of Social and Personal Relationships, “inhibited the development of interpersonal closeness and trust” and diminished “the extent to which individuals felt empathy and understanding from their partners.”

The evidence that our phones can get inside our heads so forcefully is unsettling. It suggests that our thoughts and feelings, far from being sequestered in our skulls, can be skewed by external forces we’re not even aware o

 Scientists have long known that the brain is a monitoring system as well as a thinking system. Its attention is drawn toward any object that is new, intriguing or otherwise striking — that has, in the psychological jargon, “salience.”

even in the history of captivating media, the smartphone stands out. It is an attention magnet unlike any our minds have had to grapple with before. Because the phone is packed with so many forms of information and so many useful and entertaining functions, it acts as what Dr. Ward calls a “supernormal stimulus,” one that can “hijack” attention whenever it is part of our surroundings — and it is always part of our surroundings.

Imagine combining a mailbox, a newspaper, a TV, a radio, a photo album, a public library and a boisterous party attended by everyone you know, and then compressing them all into a single, small, radiant object. That is what a smartphone represents to us. No wonder we can’t take our minds off it.

The irony of the smartphone is that the qualities that make it so appealing to us — its constant connection to the net, its multiplicity of apps, its responsiveness, its portability — are the very ones that give it such sway over our minds.

Phone makers like Apple and Samsung and app writers like Facebook, Google and Snap design their products to consume as much of our attention as possible during every one of our waking hours

Social media apps were designed to exploit “a vulnerability in human psychology,” former Facebook president Sean Parker said in a recent interview. “[We] understood this consciously. And we did it anyway.”

A quarter-century ago, when we first started going online, we took it on faith that the web would make us smarter: More information would breed sharper thinking. We now know it’s not that simple.

As strange as it might seem, people’s knowledge and understanding may actually dwindle as gadgets grant them easier access to online data stores

In a seminal 2011 study published in Science, a team of researchers — led by the Columbia University psychologist Betsy Sparrow and including the late Harvard memory expert Daniel Wegner — had a group of volunteers read forty brief, factual statements (such as “The space shuttle Columbia disintegrated during re-entry over Texas in Feb. 2003”) and then type the statements into a computer. Half the people were told that the machine would save what they typed; half were told that the statements would be erased.

Afterward, the researchers asked the subjects to write down as many of the statements as they could remember. Those who believed that the facts had been recorded in the computer demonstrated much weaker recall than those who assumed the facts wouldn’t be stored. Anticipating that information would be readily available in digital form seemed to reduce the mental effort that people made to remember it

The researchers dubbed this phenomenon the “Google effect” and noted its broad implications: “Because search engines are continually available to us, we may often be in a state of not feeling we need to encode the information internally. When we need it, we will look it up.”

as the pioneering psychologist and philosopher William James said in an 1892 lecture, “the art of remembering is the art of thinking.”

Only by encoding information in our biological memory can we weave the rich intellectual associations that form the essence of personal knowledge and give rise to critical and conceptual thinking. No matter how much information swirls around us, the less well-stocked our memory, the less we have to think with.

As Dr. Wegner and Dr. Ward explained in a 2013 Scientific American article, when people call up information through their devices, they often end up suffering from delusions of intelligence. They feel as though “their own mental capacities” had generated the information, not their devices. “The advent of the ‘information age’ seems to have created a generation of people who feel they know more than ever before,” the scholars concluded, even though “they may know ever less about the world around them.”

That insight sheds light on society’s current gullibility crisis, in which people are all too quick to credit lies and half-truths spread through social media. If your phone has sapped your powers of discernment, you’ll believe anything it tells you.

A second experiment conducted by the researchers produced similar results, while also revealing that the more heavily students relied on their phones in their everyday lives, the greater the cognitive penalty they suffered.

When we constrict our capacity for reasoning and recall or transfer those skills to a gadget, we sacrifice our ability to turn information into knowledge. We get the data but lose the meaning

We need to give our minds more room to think. And that means putting some distance between ourselves and our phones.

Google’s once-patient investors grew restive, demanding that the founders figure out a way to make money, preferably lots of it.

nder pressure, Page and Brin authorized the launch of an auction system for selling advertisements tied to search queries. The system was designed so that the company would get paid by an advertiser only when a user clicked on an ad. This feature gave Google a huge financial incentive to make accurate predictions about how users would respond to ads and other online content. Even tiny increases in click rates would bring big gains in income. And so the company began deploying its stores of behavioral data not for the benefit of users but to aid advertisers — and to juice its own profits. Surveillance capitalism had arrived.

Google’s business now hinged on what Zuboff calls “the extraction imperative.” To improve its predictions, it had to mine as much information as possible from web users. It aggressively expanded its online services to widen the scope of its surveillance.

Through Gmail, it secured access to the contents of people’s emails and address books. Through Google Maps, it gained a bead on people’s whereabouts and movements. Through Google Calendar, it learned what people were doing at different moments during the day and whom they were doing it with. Through Google News, it got a readout of people’s interests and political leanings. Through Google Shopping, it opened a window onto people’s wish lists,

The company gave all these services away for free to ensure they’d be used by as many people as possible. It knew the money lay in the data.

the organization grew insular and secretive. Seeking to keep the true nature of its work from the public, it adopted what its CEO at the time, Eric Schmidt, called a “hiding strategy” — a kind of corporate omerta backed up by stringent nondisclosure agreements.

Page and Brin further shielded themselves from outside oversight by establishing a stock structure that guaranteed their power could never be challenged, neither by investors nor by directors.

What’s most remarkable about the birth of surveillance capitalism is the speed and audacity with which Google overturned social conventions and norms about data and privacy. Without permission, without compensation, and with little in the way of resistance, the company seized and declared ownership over everyone’s information

The companies that followed Google presumed that they too had an unfettered right to collect, parse, and sell personal data in pretty much any way they pleased. In the smart homes being built today, it’s understood that any and all data will be beamed up to corporate clouds.

Google conducted its great data heist under the cover of novelty. The web was an exciting frontier — something new in the world — and few people understood or cared about what they were revealing as they searched and surfed. In those innocent days, data was there for the taking, and Google took it

Google also benefited from decisions made by lawmakers, regulators, and judges — decisions that granted internet companies free use of a vast taxpayer-funded communication infrastructure, relieved them of legal and ethical responsibility for the information and messages they distributed, and gave them carte blanche to collect and exploit user data.

Consider the terms-of-service agreements that govern the division of rights and the delegation of ownership online. Non-negotiable, subject to emendation and extension at the company’s whim, and requiring only a casual click to bind the user, TOS agreements are parodies of contracts, yet they have been granted legal legitimacy by the court

Law professors, writes Zuboff, “call these ‘contracts of adhesion’ because they impose take-it-or-leave-it conditions on users that stick to them whether they like it or not.” Fundamentally undemocratic, the ubiquitous agreements helped Google and other firms commandeer personal data as if by fiat.

n the choices we make as consumers and private citizens, we have always traded some of our autonomy to gain other rewards. Many people, it seems clear, experience surveillance capitalism less as a prison, where their agency is restricted in a noxious way, than as an all-inclusive resort, where their agency is restricted in a pleasing way

Zuboff makes a convincing case that this is a short-sighted and dangerous view — that the bargain we’ve struck with the internet giants is a Faustian one

but her case would have been stronger still had she more fully addressed the benefits side of the ledger.

there’s a piece missing. While Zuboff’s assessment of the costs that people incur under surveillance capitalism is exhaustive, she largely ignores the benefits people receive in return — convenience, customization, savings, entertainment, social connection, and so on

hat the industries of the future will seek to manufacture is the self.

Behavior modification is the thread that ties today’s search engines, social networks, and smartphone trackers to tomorrow’s facial-recognition systems, emotion-detection sensors, and artificial-intelligence bots.

All of Facebook’s information wrangling and algorithmic fine-tuning, she writes, “is aimed at solving one problem: how and when to intervene in the state of play that is your daily life in order to modify your behavior and thus sharply increase the predictability of your actions now, soon, and later.”

“The goal of everything we do is to change people’s actual behavior at scale,” a top Silicon Valley data scientist told her in an interview. “We can test how actionable our cues are for them and how profitable certain behaviors are for us.”

This goal, she suggests, is not limited to Facebook. It is coming to guide much of the economy, as financial and social power shifts to the surveillance capitalists

Combining rich information on individuals’ behavioral triggers with the ability to deliver precisely tailored and timed messages turns out to be a recipe for behavior modification on an unprecedented scale.

it was Facebook, with its incredibly detailed data on people’s social lives, that grasped digital media’s full potential for behavior modification. By using what it called its “social graph” to map the intentions, desires, and interactions of literally billions of individuals, it saw that it could turn its network into a worldwide Skinner box, employing psychological triggers and rewards to program not only what people see but how they react.

spying on the populace is not the end game. The real prize lies in figuring out ways to use the data to shape how people think and act. “The best way to predict the future is to invent it,” the computer scientist Alan Kay once observed. And the best way to predict behavior is to script it.

competition for personal data intensified. It was no longer enough to monitor people online; making better predictions required that surveillance be extended into homes, stores, schools, workplaces, and the public squares of cities and towns. Much of the recent innovation in the tech industry has entailed the creation of products and services designed to vacuum up data from every corner of our lives

“The typical complaint is that privacy is eroded, but that is misleading,” Zuboff writes. “In the larger societal pattern, privacy is not eroded but redistributed . . . . Instead of people having the rights to decide how and what they will disclose, these rights are concentrated within the domain of surveillance capitalism.” The transfer of decision rights is also a transfer of autonomy and agency, from the citizen to the corporation.

What we lose under this regime is something more fundamental than privacy. It’s the right to make our own decisions about privacy — to draw our own lines between those aspects of our lives we are comfortable sharing and those we are not

Other possible ways of organizing online markets, such as through paid subscriptions for apps and services, never even got a chance to be tested.

Online surveillance came to be viewed as normal and even necessary by politicians, government bureaucrats, and the general public

Google and other Silicon Valley companies benefited directly from the government’s new stress on digital surveillance. They earned millions through contracts to share their data collection and analysis techniques with the National Security Agenc

As much as the dot-com crash, the horrors of 9/11 set the stage for the rise of surveillance capitalism. Zuboff notes that, in 2000, members of the Federal Trade Commission, frustrated by internet companies’ lack of progress in adopting privacy protections, began formulating legislation to secure people’s control over their online information and severely restrict the companies’ ability to collect and store it. It seemed obvious to the regulators that ownership of personal data should by default lie in the hands of private citizens, not corporations.

The 9/11 attacks changed the calculus. The centralized collection and analysis of online data, on a vast scale, came to be seen as essential to national security. “The privacy provisions debated just months earlier vanished from the conversation more or less overnight,”

So it sounds like a simple fix: Impose more friction at the major platform level and you’ll clean up the public square.

But it’s not actually that simple because friction runs counter to the very idea of the internet.

The fundamental precept of the internet is that it reduces marginal costs to zero. And this fact is why the design paradigm of the internet is to continually reduce friction experienced by users to zero, too. Because if the second unit of everything is free, then the internet has a vested interest in pushing that unit in front of your eyeballs as smoothly as possible.

the internet is “broken,” but rather it’s been functioning exactly as it was designed to:

Perhaps more than any other job in the world, you do not want the President of the United States to live in a frictionless state of posting. The Presidency is not meant to be a frictionless position, and the United States government is not a frictionless entity, much to the chagrin of many who have tried to change it. Prior to this administration, decisions were closely scrutinized for, at the very least, legality, along with the impact on diplomacy, general norms, and basic grammar. This kind of legal scrutiny and due diligence is also a kind of friction--one that we now see has a lot of benefits. 

The deep lesson here isn’t about Donald Trump. It’s about the collision between the digital world and the real world.

In the real world, marginal costs are not zero. And so friction is a desirable element in helping to get to the optimal state. You want people to pause before making decisions.

described friction this summer as: “anything that inhibits user action within a digital interface, particularly anything that requires an additional click or screen.” For much of my time in the technology sector, friction was almost always seen as the enemy, a force to be vanquished. A “frictionless” experience was generally held up as the ideal state, the optimal product state.

Trump was riding the ultimate frictionless optimized engagement Twitter experience: he rode it all the way to the presidency, and then he crashed the presidency into the ground.

From a metrics and user point of view, the abstract notion of the President himself tweeting was exactly what Twitter wanted in its original platonic ideal. Twitter has been built to incentivize someone like Trump to engage and post

The other day we talked a little bit about how fighting disinformation, extremism, and online cults is like fighting a virus: There is no “cure.” Instead, what you have to do is create enough friction that the rate of spread becomes slow.

Our challenge is that when human and digital design comes into conflict, the artificial constraints we impose should be on the digital world to become more in service to us. Instead, we’ve let the digital world do as it will and tried to reconcile ourselves to the havoc it wreaks.

And one of the lessons of the last four years is that when you prize the digital design imperatives—lack of friction—over the human design imperatives—a need for friction—then bad things can happen.

We have an ongoing conflict between the design precepts of humans and the design precepts of computers.

Anyone who works with computers learns to fear their capacity to forget. Like so many things with computers, memory is strictly binary. There is either perfect recall or total oblivion, with nothing in between. It doesn't matter how important or trivial the information is. The computer can forget anything in an instant. If it remembers, it remembers for keeps.

This doesn't map well onto human experience of memory, which is fuzzy. We don't remember anything with perfect fidelity, but we're also not at risk of waking up having forgotten our own name. Memories tend to fade with time, and we remember only the more salient events.

And because we live in a time when storage grows ever cheaper, we learn to save everything, log everything, and keep it forever. You never know what will come in useful. Deleting is dangerous.

Our lives have become split between two worlds with two very different norms around memory.

[A] lot of what's wrong with the Internet has to do with memory. The Internet somehow contrives to remember too much and too little at the same time, and it maps poorly on our concepts of how memory should work.

The digital world is designed to never forget anything. It has perfect memory. Forever. So that one time you made a crude joke 20 years ago? It can now ruin your life.

Memory in the carbon-based world is imperfect. People forget things. That can be annoying if you’re looking for your keys but helpful if you’re trying to broker peace between two cultures. Or simply become a better person than you were 20 years ago.

The digital and carbon-based worlds have different design parameters. Marginal cost is one of them. Memory is another.

2. Forget Me Now

1. Fix Tech, Fix America

For the sake of everyone who stands to gain from a better knowledge of politics, economics and society, the social sciences need to overcome their inferiority complex, reject hypothetico-deductivism and embrace the fact that they are mature disciplines with no need to emulate other sciences.

Or consider the famous “impossibility theorem,” developed by the economist Kenneth Arrow, which shows that no single voting system can simultaneously satisfy several important principles of fairness. There is no need to test this model with data — in fact, there is no way to test it — and yet the result offers policy makers a powerful lesson: there are unavoidable trade-offs in the design of voting systems.

Unfortunately, the belief that every theory must have its empirical support (and vice versa) now constrains the kinds of social science projects that are undertaken, alters the trajectory of academic careers and drives graduate training. Rather than attempt to imitate the hard sciences, social scientists would be better off doing what they do best: thinking deeply about what prompts human beings to behave the way they do.

theoretical models can be of great value even if they are never supported by empirical testing. In the 1950s, for instance, the economist Anthony Downs offered an elegant explanation for why rival political parties might adopt identical platforms during an election campaign. His model relied on the same strategic logic that explains why two competing gas stations or fast-food restaurants locate across the street from each other — if you don’t move to a central location but your opponent does, your opponent will nab those voters (customers). The best move is for competitors to mimic each other. This framework has proven useful to generations of political scientists even though Mr. Downs did not empirically test it and despite the fact that its main prediction, that candidates will take identical positions in elections, is clearly false. The model offered insight into why candidates move toward the center in competitive elections

Likewise, the analysis of empirical data can be valuable even in the absence of a grand theoretical model. Did the welfare reform championed by Bill Clinton in the 1990s reduce poverty? Are teenage employees adversely affected by increases in the minimum wage?

Answering such questions about the effects of public policies does not require sweeping theoretical claims, just careful attention to the data.

theories are like maps: the test of a map lies not in arbitrarily checking random points but in whether people find it useful to get somewhere.

Economists, political scientists and sociologists have long suffered from an academic inferiority complex: physics envy. They often feel that their disciplines should be on a par with the “real” sciences and self-consciously model their work on them, using language (“theory,” “experiment,” “law”) evocative of physics and chemistry.

The ideal of hypothetico-deductivism is flawed for many reasons. For one thing,

Long lives are not the problem. The problem is living in cultures designed for lives half as long as the ones we have.

Retirements that span four decades are unattainable for most individuals and governments; education that ends in the early 20s is ill-suited for longer working lives; and social norms that dictate intergenerational responsibilities between parents and young children fail to address families that include four or five living generations.

Last year, the Stanford Center on Longevity launched an initiative called “The New Map of Life.”

it would be a mistake to replace the old rigid model of life — education first, then family and work, and finally retirement — with a new model just as rigid

there should be many different routes, interweaving leisure, work, education and family throughout life, taking people from birth to death with places to stop, rest, change courses and repeat steps along the way.

To thrive in an age of rapid knowledge transfer, children not only need reading, math and computer literacy, but they also need to learn to think creatively and not hold on to “facts” too tightly. They’ll need to find joy in unlearning and relearning.

Teens could take breaks from high school and take internships in workplaces that intrigue them. Education wouldn’t end in youth but rather be ever-present and take many forms outside of classrooms, from micro-degrees to traveling the world.

There is good reason to think we will work longer, but we can improve work quality with shorter workweeks, flexible scheduling and frequent “retirements.”

Rather than saving ever-larger pots of money for the end of life, we could pool risks in new ways

Generations may share wealth earlier than traditional bequests; we can start savings accounts at birth and allow young adults to work earlier so that compound interest can work in their favor.

Maintaining physical fitness from the beginning to end of life will be paramount. Getting children outside, encouraging sports, reducing the time we sit, and spending more time walking and moving will greatly improve individual lives.