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Haunting von Neumann’s thought experiment is the specter of a construct that, in its very internal perfection, lacks the element that would account for itself as a construct. “If someone succeeded in creating a formal system of axioms that was free of all internal paradoxes and contradictions,” another of von Neumann’s interlocutors, the logician Kurt Gödel, explains, “it would always be incomplete, because it would contain truths and statements that — while being undeniably true — could never be proven within the laws of that system.”

its deeper (and, for me, more compelling) theme: the relation between reason and madness.

Almost all the scientists populating the book are mad, their desire “to understand, to grasp the core of things” invariably wedded to “an uncontrollable mania”; even their scrupulously observed reason, their mode of logic elevated to religion, is framed as a form of madness. Von Neumann’s response to the detonation of the Trinity bomb, the world’s first nuclear explosion, is “so utterly rational that it bordered on the psychopathic,” his second wife, Klara Dan, muses

fanaticism, in the 1930s, “was the norm … even among us mathematicians.”

Pondering Gödel’s own descent into mania, the physicist Eugene Wigner claims that “paranoia is logic run amok.” If you’ve convinced yourself that there’s a reason for everything, “it’s a small step to begin to see hidden machinations and agents operating to manipulate the most common, everyday occurrences.”

the game theory-derived system of mutually assured destruction he devises in its wake is “perfectly rational insanity,” according to its co-founder Oskar Morgenstern.

Labatut has Morgenstern end his MAD deliberations by pointing out that humans are not perfect poker players. They are irrational, a fact that, while instigating “the ungovernable chaos that we see all around us,” is also the “mercy” that saves us, “a strange angel that protects us from the mad dreams of reason.”

But does von Neumann really deserve the title “Father of Computers,” granted him here by his first wife, Mariette Kovesi? Doesn’t Ada Lovelace have a prior claim as their mother? Feynman’s description of the Trinity bomb as “a little Frankenstein monster” should remind us that it was Mary Shelley, not von Neumann and his coterie, who first grasped the monumental stakes of modeling the total code of life, its own instructions for self-replication, and that it was Rosalind Franklin — working alongside, not under, Maurice Wilkins — who first carried out this modeling.

he at least grants his women broader, more incisive wisdom. Ehrenfest’s lover Nelly Posthumus Meyjes delivers a persuasive lecture on the Pythagorean myth of the irrational, suggesting that while scientists would never accept the fact that “nature cannot be cognized as a whole,” artists, by contrast, “had already fully embraced it.”

Beitman defines a coincidence as “two events coming together with apparently no causal explanation.” They can be life-changing, like his experience with his father, or comforting, such as when a loved one’s favorite song comes on the radio just when you are missing them most.

Although Beitman has long been fascinated by coincidences, it wasn’t until the end of his academic career that he was able to study them in earnest. (Before then, his research primarily focused on the relationship between chest pain and panic disorder.)

He started by developing the Weird Coincidence Survey in 2006 to assess what types of coincidences are most commonly observed, what personality types are most correlated with noticing them and how most people explain them. About 3,000 people have completed the survey so far.

he has drawn a few conclusions. The most commonly reported coincidences are associated withmass media: A person thinks of an idea and then hears or sees it on TV, the radio or the internet. Thinking of someone and then having that person call unexpectedly is next on the list, followed by being in the right place at the right time to advance one’s work, career or education.

People who describe themselves as spiritual or religious report noticing more meaningful coincidences than those who do not, and people are more likely to experience coincidences when they are in a heightened emotional state — perhaps under stress or grieving.

The most popular explanation among survey respondents for mysterious coincidences: God or fate. The second explanation: randomness. The third is that our minds are connected to one another. The fourth is that our minds are connected to the environment.

“Some say God, some say universe, some say random and I say ‘Yes,’ ” he said. “People want things to be black and white, yes or no, but I say there is mystery.”

He’s particularly interested in what he’s dubbed “simulpathity”: feeling a loved one’s pain at a distance, as he believes he did with his father. Science can’t currently explain how it might occur, but in his books he offers some nontraditional ideas, such as the existence of “the psychosphere,” a kind of mental atmosphere through which information and energy can travel between two people who are emotionally close though physically distant.

In his new book published in September, “Meaningful Coincidences: How and Why Synchronicity and Serendipity Happen,” he shares the story of a young man who intended to end his life by the shore of an isolated lake. While he sat crying in his car, another car pulled up and his brother got out. When the young man asked for an explanation, the brother said he didn’t know why he got in the car, where he was going, or what he would do when he got there. He just knew he needed to get in the car and drive.

David Hand, a British statistician and author of the 2014 book “The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day,” sits at the opposite end of the spectrum from Beitman. He says most coincidences are fairly easy to explain, and he specializes in demystifying even the strangest ones.

“When you look closely at a coincidence, you can often discover the chance of it happening is not as small as you think,” he said. “It’s perhaps not a 1-in-a-billion chance, but in fact a 1-in-a-hundred chance, and yeah, you would expect that would happen quite often.”

the law of truly large numbers. “You take something that has a very small chance of happening and you give it lots and lots and lots of opportunities to happen,” he said. “Then the overall probability becomes big.”

But just because Hand has a mathematical perspective doesn’t mean he finds coincidences boring. “It’s like looking at a rainbow,” he said. “Just because I understand the physics behind it doesn’t make it any the less wonderful.

Paying attention to coincidences, Osman and Johansen say, is an essential part of how humans make sense of the world. We rely constantly on our understanding of cause and effect to survive.

“Coincidences are often associated with something mystical or supernatural, but if you look under the hood, noticing coincidences is what humans do all the time,”

Zeltzer has spent 50 years studying the writings of Carl Jung, the 20th century Swiss psychologist who introduced the modern Western world to the idea of synchronicity. Jung defined synchronicity as “the coincidence in time of two or more causally unrelated events which have the same meaning.”

One of Jung’s most iconic synchronistic stories concerned a patient who he felt had become so stuck in her rationality that it interfered with her ability to understand her psychology and emotional life.

One day, the patient was recounting a dream in which she’d received a golden scarab. Just then, Jung heard a gentle tapping at the window. He opened the window and a scarab-like beetle flew into the room. Jung plucked the insect out of the air and presented it to his patient. “Here is your scarab,” he said.The experience proved therapeutic because it demonstrated to Jung’s patient that the world is not always rational, leading her to break her own identification with rationality and thus become more open to her emotional life, Zeltzer explained

Like Jung, Zeltzer believes meaningful coincidences can encourage people to acknowledge the irrational and mysterious. “We have a fantasy that there is always an answer, and that we should know everything,”

Honestly, I’m not sure what to believe, but I’m not sure it matters. Like Beitman, my attitude is “Yes.”

That’s exactly what the geographer Patrick Nunn and the historian Margaret Cook at the University of the Sunshine Coast in Australia have proposed in a recent paper.

In their work, the pair describe colorful legends from northern Europe and Australia that depict rising waters, peninsulas becoming islands, and receding coastlines during that period of deglaciation thousands of years ago. Some of these stories, the researchers say, capture historical sea-level rise that actually happened—often several thousand years ago. For scholars of oral history, that makes them geomyths.

“The first time I read an Aboriginal story from Australia that seemed to recall the rise of sea levels after the last ice age, I thought, No, I don’t think this is correct,” Nunn says. “But then I read another story that recalled the same thing.

For Jo Brendryen, a paleoclimatologist at the University of Bergen in Norway who has studied the effects of deglaciation in Europe following the end of the last ice age, the idea that traditional oral histories preserve real accounts of sea-level rise is perfectly plausible.

During the last ice age, he says, the sudden melting of ice sheets induced catastrophic events known as meltwater pulses, which caused sudden and extreme sea-level rise. Along some coastlines in Europe, the ocean may have risen as much as 10 meters in just 200 years. At such a pace, it would have been noticeable to people across just a few human generations.

“These are stories based in trauma, based in catastrophe.”

That, he suggests, is why it may have made sense for successive generations to pass on tales of geological upheaval. Ancient societies may have sought to broadcast their warning: Beware, these things can happen!

the old stories still have things to teach us. As Nunn says, “The fact that our ancestors have survived those periods gives us hope that we can survive this.”

That allows quantum computers to make many calculations in one pass, while digital ones have to perform each calculation separately. By speeding up computation, quantum computers could potentially solve big, complex problems in fields like chemistry and materials science that are out of reach today.

When Google researchers made their supremacy claim in 2019, they said their quantum computer performed a calculation in 3 minutes 20 seconds that would take about 10,000 years on a state-of-the-art conventional supercomputer.

The IBM researchers in the new study performed a different task, one that interests physicists. They used a quantum processor with 127 qubits to simulate the behavior of 127 atom-scale bar magnets — tiny enough to be governed by the spooky rules of quantum mechanics — in a magnetic field. That is a simple system known as the Ising model, which is often used to study magnetism.

This problem is too complex for a precise answer to be calculated even on the largest, fastest supercomputers.

On the quantum computer, the calculation took less than a thousandth of a second to complete. Each quantum calculation was unreliable — fluctuations of quantum noise inevitably intrude and induce errors — but each calculation was quick, so it could be performed repeatedly.

Indeed, for many of the calculations, additional noise was deliberately added, making the answers even more unreliable. But by varying the amount of noise, the researchers could tease out the specific characteristics of the noise and its effects at each step of the calculation.“We can amplify the noise very precisely, and then we can rerun that same circuit,” said Abhinav Kandala, the manager of quantum capabilities and demonstrations at IBM Quantum and an author of the Nature paper. “And once we have results of these different noise levels, we can extrapolate back to what the result would have been in the absence of noise.”In essence, the researchers were able to subtract the effects of noise from the unreliable quantum calculations, a process they call error mitigation.

Altogether, the computer performed the calculation 600,000 times, converging on an answer for the overall magnetization produced by the 127 bar magnets.

Although an Ising model with 127 bar magnets is too big, with far too many possible configurations, to fit in a conventional computer, classical algorithms can produce approximate answers, a technique similar to how compression in JPEG images throws away less crucial data to reduce the size of the file while preserving most of the image’s details

Certain configurations of the Ising model can be solved exactly, and both the classical and quantum algorithms agreed on the simpler examples. For more complex but solvable instances, the quantum and classical algorithms produced different answers, and it was the quantum one that was correct.

Thus, for other cases where the quantum and classical calculations diverged and no exact solutions are known, “there is reason to believe that the quantum result is more accurate,”

Mr. Anand is currently trying to add a version of error mitigation for the classical algorithm, and it is possible that could match or surpass the performance of the quantum calculations.

In the long run, quantum scientists expect that a different approach, error correction, will be able to detect and correct calculation mistakes, and that will open the door for quantum computers to speed ahead for many uses.

Error correction is already used in conventional computers and data transmission to fix garbles. But for quantum computers, error correction is likely years away, requiring better processors able to process many more qubits

“This is one of the simplest natural science problems that exists,” Dr. Gambetta said. “So it’s a good one to start with. But now the question is, how do you generalize it and go to more interesting natural science problems?”

Those might include figuring out the properties of exotic materials, accelerating drug discovery and modeling fusion reactions.

The fact that Thomas was very likely nominated because he was Black and because he opposed affirmative action posed a conundrum for many supporters of racial preferences. Was being Black enough? Or did you have to be “the right kind” of Black person? It’s a question Carter openly wrestles with in his book.

What immediately struck me on rereading it was how prescient Carter was about these debates 32 years ago. What role affirmative action should take was playing out then in ways that continue to reverberate.

The demise of affirmative action, in Carter’s view, was both necessary and inevitable. “We must reject the common claim that an end to preferences ‘would be a disastrous situation, amounting to a virtual nullification of the 1954 desegregation ruling,’” he wrote, quoting the activist and academic Robert Allen. “The prospect of its end should be a challenge and a chance.”

Like many people today — both proponents and opponents of affirmative action — he expressed reservations about relying on diversity as the constitutional basis for racial preferences.

Carter bristled at the judgment of many of his Black peers, describing several situations in which he found himself accused of being “inauthentically” Black, as if people of a particular race were a monolith and that those who deviated from it were somehow shirking their duty. He said he didn’t want to be limited in what he was allowed to say by “an old and vicious form of silencing.”

But the implication of recruiting for diversity, Carter explained, had less to do with admitting Black students to redress past discrimination and more to do with supporting and reinforcing essentialist notions about Black people.

An early critic of groupthink, Carter warned against “the idea that Black people who gain positions of authority or influence are vested a special responsibility to articulate the presumed views of other people who are Black — in effect, to think and act and speak in a particular way, the Black way — and that there is something peculiar about Black people who insist on doing anything else.”

A graduate of Stanford and Yale Law, Carter was a proud beneficiary of affirmative action. Yet he acknowledged the personal toll it took (“a decidedly mixed blessing”) as well as affirmative action’s sometimes troubling effects on Black people as the programs evolved.

, it’s hard to imagine Carter welcoming the current vogue for white allyship, with its reductive assumption that all Black people have the same interests and values

He disparaged what he called “the peculiar relationship between Black intellectuals and the white ones who seem loath to criticize us for fear of being branded racists — which is itself a mark of racism of a sort.”

In the past, such ideas might have been seen as “frankly racist,” Carter noted. “Now, however, they are almost a gospel for people who want to show their commitment to equality.”

Carter took issue with the belief, now practically gospel in academic, cultural and media circles, that heightened race consciousness would be central to overcoming racism

However well intentioned you may be, when you reduce people to their race-based identity rather than view them as individuals in their full, complex humanity, you risk making sweeping assumptions about who they are. This used to be called stereotyping or racism.

he rejected all efforts to label him, insisting that intellectuals should be “politically unpredictable.

“Critics who attempt to push (or pull) Carter into the ranks of the Black right wing will be making a mistake. He is not a conservative, neo- or otherwise. He is an honest Black scholar — the product of the pre-politically correct era — who abhors the stifling of debate by either wing or by people of any hue.”

This strikes me as the greatest difference between reading the book today and reading it as an undergrad at a liberal Ivy League college: the attitude toward debating controversial views. “Reflections” offers a vigorous and unflinching examination of ideas, something academia, media and the arts still prized in 1991.

Today, a kind of magical thinking has seized ideologues on both the left and the right, who seem to believe that stifling debate on difficult questions will make them go away

it is comforting to think that scientific truth inevitably emerges and scientific frauds will be caught and punished.

Dr. Hwang’s scandal suggests something different. Researchers don’t always have the resources or motivation to replicate others’ experiments

Even if they try to replicate and fail, it is the institution where the scientist works that has the right and responsibility to investigate possible fraud. Research institutes and universities, facing the prospect of an embarrassing scandal, might not do so.

Confirmation bias shows up most blatantly in our current political divide, where each side seems unable to allow that the other side is right about anything.

The whole idea of cognitive biases and faulty heuristics—the shortcuts and rules of thumb by which we make judgments and predictions—was more or less invented in the 1970s by Amos Tversky and Daniel Kahneman

versky died in 1996. Kahneman won the 2002 Nobel Prize in Economics for the work the two men did together, which he summarized in his 2011 best seller, Thinking, Fast and Slow. Another best seller, last year’s The Undoing Project, by Michael Lewis, tells the story of the sometimes contentious collaboration between Tversky and Kahneman

Another key figure in the field is the University of Chicago economist Richard Thaler. One of the biases he’s most linked with is the endowment effect, which leads us to place an irrationally high value on our possessions.

In an experiment conducted by Thaler, Kahneman, and Jack L. Knetsch, half the participants were given a mug and then asked how much they would sell it for. The average answer was $5.78. The rest of the group said they would spend, on average, $2.21 for the same mug. This flew in the face of classic economic theory, which says that at a given time and among a certain population, an item has a market value that does not depend on whether one owns it or not. Thaler won the 2017 Nobel Prize in Economics.

“The question that is most often asked about cognitive illusions is whether they can be overcome. The message … is not encouraging.”

that’s not so easy in the real world, when we’re dealing with people and situations rather than lines. “Unfortunately, this sensible procedure is least likely to be applied when it is needed most,” Kahneman writes. “We would all like to have a warning bell that rings loudly whenever we are about to make a serious error, but no such bell is available.”

At least with the optical illusion, our slow-thinking, analytic mind—what Kahneman calls System 2—will recognize a Müller-Lyer situation and convince itself not to trust the fast-twitch System 1’s perception

Kahneman and others draw an analogy based on an understanding of the Müller-Lyer illusion, two parallel lines with arrows at each end. One line’s arrows point in; the other line’s arrows point out. Because of the direction of the arrows, the latter line appears shorter than the former, but in fact the two lines are the same length.

Because biases appear to be so hardwired and inalterable, most of the attention paid to countering them hasn’t dealt with the problematic thoughts, judgments, or predictions themselves

Is it really impossible, however, to shed or significantly mitigate one’s biases? Some studies have tentatively answered that question in the affirmative.

what if the person undergoing the de-biasing strategies was highly motivated and self-selected? In other words, what if it was me?

Over an apple pastry and tea with milk, he told me, “Temperament has a lot to do with my position. You won’t find anyone more pessimistic than I am.”

I met with Kahneman

“I see the picture as unequal lines,” he said. “The goal is not to trust what I think I see. To understand that I shouldn’t believe my lying eyes.” That’s doable with the optical illusion, he said, but extremely difficult with real-world cognitive biases.

In this context, his pessimism relates, first, to the impossibility of effecting any changes to System 1—the quick-thinking part of our brain and the one that makes mistaken judgments tantamount to the Müller-Lyer line illusion

he most effective check against them, as Kahneman says, is from the outside: Others can perceive our errors more readily than we can.

“slow-thinking organizations,” as he puts it, can institute policies that include the monitoring of individual decisions and predictions. They can also require procedures such as checklists and “premortems,”

A premortem attempts to counter optimism bias by requiring team members to imagine that a project has gone very, very badly and write a sentence or two describing how that happened. Conducting this exercise, it turns out, helps people think ahead.

“My position is that none of these things have any effect on System 1,” Kahneman said. “You can’t improve intuition.

Perhaps, with very long-term training, lots of talk, and exposure to behavioral economics, what you can do is cue reasoning, so you can engage System 2 to follow rules. Unfortunately, the world doesn’t provide cues. And for most people, in the heat of argument the rules go out the window.

Kahneman describes an even earlier Nisbett article that showed subjects’ disinclination to believe statistical and other general evidence, basing their judgments instead on individual examples and vivid anecdotes. (This bias is known as base-rate neglect.)

over the years, Nisbett had come to emphasize in his research and thinking the possibility of training people to overcome or avoid a number of pitfalls, including base-rate neglect, fundamental attribution error, and the sunk-cost fallacy.

Nisbett’s second-favorite example is that economists, who have absorbed the lessons of the sunk-cost fallacy, routinely walk out of bad movies and leave bad restaurant meals uneaten.

When Nisbett asks the same question of students who have completed the statistics course, about 70 percent give the right answer. He believes this result shows, pace Kahneman, that the law of large numbers can be absorbed into System 2—and maybe into System 1 as well, even when there are minimal cues.

about half give the right answer: the law of large numbers, which holds that outlier results are much more frequent when the sample size (at bats, in this case) is small. Over the course of the season, as the number of at bats increases, regression to the mean is inevitabl

When Nisbett has to give an example of his approach, he usually brings up the baseball-phenom survey. This involved telephoning University of Michigan students on the pretense of conducting a poll about sports, and asking them why there are always several Major League batters with .450 batting averages early in a season, yet no player has ever finished a season with an average that high.

we’ve tested Michigan students over four years, and they show a huge increase in ability to solve problems. Graduate students in psychology also show a huge gain.”

, “I know from my own research on teaching people how to reason statistically that just a few examples in two or three domains are sufficient to improve people’s reasoning for an indefinitely large number of events.”

isbett suggested another factor: “You and Amos specialized in hard problems for which you were drawn to the wrong answer. I began to study easy problems, which you guys would never get wrong but untutored people routinely do … Then you can look at the effects of instruction on such easy problems, which turn out to be huge.”

Nisbett suggested that I take “Mindware: Critical Thinking for the Information Age,” an online Coursera course in which he goes over what he considers the most effective de-biasing skills and concepts. Then, to see how much I had learned, I would take a survey he gives to Michigan undergraduates. So I did.

he course consists of eight lessons by Nisbett—who comes across on-screen as the authoritative but approachable psych professor we all would like to have had—interspersed with some graphics and quizzes. I recommend it. He explains the availability heuristic this way: “People are surprised that suicides outnumber homicides, and drownings outnumber deaths by fire. People always think crime is increasing” even if it’s not.

When I finished the course, Nisbett sent me the survey he and colleagues administer to Michigan undergrads

It contains a few dozen problems meant to measure the subjects’ resistance to cognitive biases

I got it right. Indeed, when I emailed my completed test, Nisbett replied, “My guess is that very few if any UM seniors did as well as you. I’m sure at least some psych students, at least after 2 years in school, did as well. But note that you came fairly close to a perfect score.”

Nevertheless, I did not feel that reading Mindware and taking the Coursera course had necessarily rid me of my biases

For his part, Nisbett insisted that the results were meaningful. “If you’re doing better in a testing context,” he told me, “you’ll jolly well be doing better in the real world.”

The New York–based NeuroLeadership Institute offers organizations and individuals a variety of training sessions, webinars, and conferences that promise, among other things, to use brain science to teach participants to counter bias. This year’s two-day summit will be held in New York next month; for $2,845, you could learn, for example, “why are our brains so bad at thinking about the future, and how do we do it better?”

Philip E. Tetlock, a professor at the University of Pennsylvania’s Wharton School, and his wife and research partner, Barbara Mellers, have for years been studying what they call “superforecasters”: people who manage to sidestep cognitive biases and predict future events with far more accuracy than the pundits

One of the most important ingredients is what Tetlock calls “the outside view.” The inside view is a product of fundamental attribution error, base-rate neglect, and other biases that are constantly cajoling us into resting our judgments and predictions on good or vivid stories instead of on data and statistics

In 2006, seeking to prevent another mistake of that magnitude, the U.S. government created the Intelligence Advanced Research Projects Activity (iarpa), an agency designed to use cutting-edge research and technology to improve intelligence-gathering and analysis. In 2011, iarpa initiated a program, Sirius, to fund the development of “serious” video games that could combat or mitigate what were deemed to be the six most damaging biases: confirmation bias, fundamental attribution error, the bias blind spot (the feeling that one is less biased than the average person), the anchoring effect, the representativeness heuristic, and projection bias (the assumption that everybody else’s thinking is the same as one’s own).

most promising are a handful of video games. Their genesis was in the Iraq War

Together with collaborators who included staff from Creative Technologies, a company specializing in games and other simulations, and Leidos, a defense, intelligence, and health research company that does a lot of government work, Morewedge devised Missing. Some subjects played the game, which takes about three hours to complete, while others watched a video about cognitive bias. All were tested on bias-mitigation skills before the training, immediately afterward, and then finally after eight to 12 weeks had passed.

“The literature on training suggests books and classes are fine entertainment but largely ineffectual. But the game has very large effects. It surprised everyone.”

he said he saw the results as supporting the research and insights of Richard Nisbett. “Nisbett’s work was largely written off by the field, the assumption being that training can’t reduce bias,

even the positive results reminded me of something Daniel Kahneman had told me. “Pencil-and-paper doesn’t convince me,” he said. “A test can be given even a couple of years later. But the test cues the test-taker. It reminds him what it’s all about.”

Morewedge told me that some tentative real-world scenarios along the lines of Missing have shown “promising results,” but that it’s too soon to talk about them.

In the future, I will monitor my thoughts and reactions as best I can

this is like if Russell Moore came out and said that, on the whole, Christianity turns out to be a bad thing. It’s that big of a deal.

Thompson’s case centers around constraints and supply, particularly as they apply to content creation.

In the pre-internet days, creating and distributing content was relatively expensive, which placed content publishers—be they newspapers, or TV stations, or movie studios—high on the value chain.

The internet reduced distribution costs to zero and this shifted value away from publishers and over to aggregators: Suddenly it was more important to aggregate an audience—a la Google and Facebook—than to be a content creator.

Audiences were valuable; content was commoditized.

What has alarmed Thompson is that AI has now reduced the cost of creating content to zero.

what does the world look like when both the creation and distribution of content are zero?

Hellscape

We’re headed to a place where content is artificially created and distributed in such a way as to be tailored to a given user’s preferences. Which will be the equivalent of living in a hall of mirrors.

What does that mean for news? Nothing good.

It doesn’t really make sense to talk about “news media” because there are fundamental differences between publication models that are driven by scale.

So the challenges the New York Times face will be different than the challenges that NPR or your local paper face.

Two big takeaways:

(1) Ad-supported publications will not survive

Zero-cost for content creation combined with zero-cost distribution means an infinite supply of content. The more content you have, the more ad space exists—the lower ad prices go.

Actually, some ad-supported publications will survive. They just won’t be news. What will survive will be content mills that exist to serve ads specifically matched to targeted audiences.

(2) Size is determinative.

The New York Times has a moat by dint of its size. It will see the utility of its soft “news” sections decline in value, because AI is going to be better at creating cooking and style content than breaking hard news. But still, the NYT will be okay because it has pivoted hard into being a subscription-based service over the last decade.

At the other end of the spectrum, independent journalists should be okay. A lone reporter running a focused Substack who only needs four digits’ worth of subscribers to sustain them.

But everything in between? That’s a crapshoot.

Technology writers sometimes talk about the contrast between “builders” and “conservers” — roughly speaking, between those who are most animated by what we stand to gain from technology and those animated by what we stand to lose.

in our moment the builder and conserver types are proving quite mercurial. On issues ranging from Big Tech to medicine, human enhancement to technologies of governance, the politics of technology are in upheaval.

Dispositions are supposed to be basically fixed. So who would have thought that deep blue cities that yesterday were hotbeds of vaccine skepticism would today become pioneers of vaccine passports? Or that outlets that yesterday reported on science and tech developments in reverent tones would today make it their mission to unmask “tech bros”?

One way to understand this churn is that the builder and the conserver types each speak to real, contrasting features within human nature. Another way is that these types each pick out real, contrasting features of technology. Focusing strictly on one set of features or the other eventually becomes unstable, forcing the other back into view.

Observations of predator behavior further piqued his interest. While filming and playing back his videos, he noted how cats stack their bodies behind their faces when they’re hunting. He interprets this, he said, as cats “trying to hide their heat” with their cold noses. He has also observed barn owls twisting as they swoop down, perhaps to shield their warmer parts — legs and wingpits — with cooler ones.

Maybe, he thought, “predators have to conceal their infrared to be able to catch a mouse.”

Eventually, these and other musings led Dr. Baker to place mouse hairs under a microscope. As it came into view, he felt a strong sense of familiarity. The guard hair in particular — the bristliest type of mouse hair — contained evenly-spaced bands of pigment that, to Dr. Baker, closely resembled structures that allow optical sensors to tune into specific wavelengths of light.

Thermal cameras, for instance, focus specifically on 10-micron radiation: the slice of the spectrum that most closely corresponds with heat released by living things. By measuring the stripes, Dr. Baker found they were tuned to 10 microns as well — apparently homed in on life’s most common heat signature. “That was my Eureka moment,” he said.

“It is not unusual for outside groups to critique our coverage or to rally supporters to seek to influence our journalism,” Kahn wrote in the memo. “In this case, however, members of our staff and contributors to The Times joined the effort … We do not welcome, and will not tolerate, participation by Times journalists in protests organized by advocacy groups or attacks on colleagues on social media and other public forums.”

Charlie Stadtlander, the Times’ director of external communication, put out a statement stating that the organization pursues “independent reporting on transgender issues that include profiling groundbreakers in the movement, challenges and prejudice faced by the community, and how society is grappling with debates about care”. While that was all very diplomatic, the executive editor, Joe Kahn, and opinion editor, Kathleen Kingsbury, sent around a rather more pointed newsroom memo condemning the letters on Thursday.

The second letter was signed by more than 100 LGBTQ+ and civil rights groups, including Glaad and the Human Rights Campaign. It expressed support for the contributor letter and accused the Times of platforming “fringe theories” and “dangerous inaccuracies”. It noted that while the Times has produced responsible coverage of trans people, “those articles are not getting front-page placement or sent to app users via push notification like the irresponsible pieces are”. And it observed that rightwing politicians have been using the Times’s coverage of trans issues to justify criminalizing gender-affirming care.

Here’s the thing: there is no clear-cut line between advocacy and journalism. All media organizations have a perspective about the world and filter their output (which will, of course, strive to be fairly reported) through that perspective. To pretend otherwise is dishonest. Like it or not, the Times is involved in advocacy. It just needs to step back for a moment and think about who it’s advocating for.

The philosopher Immanuel Kant (1724–1804) argued in his Critique of Pure Reason that the human mind knows objects in innate, a priori ways. Kant claimed that humans, from birth, must experience all objects as being successive (time) and juxtaposed (space). His list of inborn categories describes predicates that the mind can attribute to any object in general. Arthur Schopenhauer (1788–1860) agreed with Kant, but reduced the number of innate categories to one—causality—which presupposes the others.

Modern nativism is most associated with the work of Jerry Fodor (1935–2017), Noam Chomsky (b. 1928), and Steven Pinker (b. 1954), who argue that humans from birth have certain cognitive modules (specialised genetically inherited psychological abilities) that allow them to learn and acquire certain skills, such as language.

For example, children demonstrate a facility for acquiring spoken language but require intensive training to learn to read and write. This poverty of the stimulus observation became a principal component of Chomsky's argument for a "language organ"—a genetically inherited neurological module that confers a somewhat universal understanding of syntax that all neurologically healthy humans are born with, which is fine-tuned by an individual's experience with their native language

In The Blank Slate (2002), Pinker similarly cites the linguistic capabilities of children, relative to the amount of direct instruction they receive, as evidence that humans have an inborn facility for speech acquisition (but not for literacy acquisition).

A number of other theorists[1][2][3] have disagreed with these claims. Instead, they have outlined alternative theories of how modularization might emerge over the course of development, as a result of a system gradually refining and fine-tuning its responses to environmental stimuli.[4]

Many empiricists are now also trying to apply modern learning models and techniques to the question of language acquisition, with marked success.[20] Similarity-based generalization marks another avenue of recent research, which suggests that children may be able to rapidly learn how to use new words by generalizing about the usage of similar words that they already know (see also the distributional hypothesis).[14][21][22][23]

The term universal grammar (or UG) is used for the purported innate biological properties of the human brain, whatever exactly they turn out to be, that are responsible for children's successful acquisition of a native language during the first few years of life. The person most strongly associated with the hypothesising of UG is Noam Chomsky, although the idea of Universal Grammar has clear historical antecedents at least as far back as the 1300s, in the form of the Speculative Grammar of Thomas of Erfurt.

This evidence is all the more impressive when one considers that most children do not receive reliable corrections for grammatical errors.[9] Indeed, even children who for medical reasons cannot produce speech, and therefore have no possibility of producing an error in the first place, have been found to master both the lexicon and the grammar of their community's language perfectly.[10] The fact that children succeed at language acquisition even when their linguistic input is severely impoverished, as it is when no corrective feedback is available, is related to the argument from the poverty of the stimulus, and is another claim for a central role of UG in child language acquisition.

Researchers at Blue Brain discovered a network of about fifty neurons which they believed were building blocks of more complex knowledge but contained basic innate knowledge that could be combined in different more complex ways to give way to acquired knowledge, like memory.[11

experience, the tests would bring about very different characteristics for each rat. However, the rats all displayed similar characteristics which suggest that their neuronal circuits must have been established previously to their experiences. The Blue Brain Project research suggests that some of the "building blocks" of knowledge are genetic and present at birth.[11]

modern nativist theory makes little in the way of specific falsifiable and testable predictions, and has been compared by some empiricists to a pseudoscience or nefarious brand of "psychological creationism". As influential psychologist Henry L. Roediger III remarked that "Chomsky was and is a rationalist; he had no uses for experimental analyses or data of any sort that pertained to language, and even experimental psycholinguistics was and is of little interest to him".[13]

, Chomsky's poverty of the stimulus argument is controversial within linguistics.[14][15][16][17][18][19]

Neither the five-year-old nor the adults in the community can easily articulate the principles of the grammar they are following. Experimental evidence shows that infants come equipped with presuppositions that allow them to acquire the rules of their language.[6]

Paul Griffiths, in "What is Innateness?", argues that innateness is too confusing a concept to be fruitfully employed as it confuses "empirically dissociated" concepts. In a previous paper, Griffiths argued that innateness specifically confuses these three distinct biological concepts: developmental fixity, species nature, and intended outcome. Developmental fixity refers to how insensitive a trait is to environmental input, species nature reflects what it is to be an organism of a certain kind, and the intended outcome is how an organism is meant to develop.[24]

The Pew Research Center survey asked people different questions but found similar doubts about AI. Just 15 percent of respondents said they were more excited than concerned about the increasing use of AI in daily life.

“It’s fantastic that there is public skepticism about AI. There absolutely should be,” said Meredith Broussard, an artificial intelligence researcher and professor at New York University.

Broussard said there can be no way to design artificial intelligence software to make inherently human decisions, like grading students’ tests or determining the course of medical treatment.

Most Americans essentially agree with Broussard that AI has a place in our lives, but not for everything.

Most people said it was a bad idea to use AI for military drones that try to distinguish between enemies and civilians or trucks making local deliveries without human drivers. Most respondents said it was a good idea for machines to perform risky jobs such as coal mining.

Roman Yampolskiy, an AI specialist at the University of Louisville engineering school, told me he’s concerned about how quickly technologists are building computers that are designed to “think” like the human brain and apply knowledge not just in one narrow area, like recommending Netflix movies, but for complex tasks that have tended to require human intelligence.

“We have an arms race between multiple untested technologies. That is my concern,” Yampolskiy said. (If you want to feel terrified, I recommend Yampolskiy’s research paper on the inability to control advanced AI.)

The term “AI” is a catch-all for everything from relatively uncontroversial technology, such as autocomplete in your web search queries, to the contentious software that promises to predict crime before it happens. Our fears about the latter might be overwhelming our beliefs about the benefits from more mundane AI.

Gelfand and Harrington predicted that “‘tight’ states would exhibit a higher incidence of natural disasters, greater environmental vulnerability, fewer natural resources, greater incidence of disease and higher mortality rates, higher population density, and greater degrees of external threat.”

The South dominated the tight states: Mississippi, Alabama Arkansas, Oklahoma, Tennessee, Texas, Louisiana, Kentucky, South Carolina and North Carolina

states in New England and on the West Coast were the loosest: California, Oregon, Washington, Maine, Massachusetts, Connecticut, New Hampshire and Vermont.

Cultural differences, Gelfand continued, “have a certain logic — a rationale that makes good sense,” noting that “cultures that have threats need rules to coordinate to survive (think about how incredibly coordinated Japan is in response to natural disasters).

“Rule Makers, Rule Breakers: How Tight and Loose Cultures Wire the World” in 2018, in which she described the results of a 2016 pre-election survey she and two colleagues had commissioned

The results were telling: People who felt the country was facing greater threats desired greater tightness. This desire, in turn, correctly predicted their support for Trump. In fact, desired tightness predicted support for Trump far better than other measures. For example, a desire for tightness predicted a vote for Trump with 44 times more accuracy than other popular measures of authoritarianism.

The 2016 election, Gelfand continued, “turned largely on primal cultural reflexes — ones that had been conditioned not only by cultural forces, but by a candidate who was able to exploit them.”

Gelfand said:Some groups have much stronger norms than others; they’re tight. Others have much weaker norms; they’re loose. Of course, all cultures have areas in which they are tight and loose — but cultures vary in the degree to which they emphasize norms and compliance with them.

In both 2016 and 2020, Donald Trump carried all 10 of the top “tight” states; Hillary Clinton and Joe Biden carried all 10 of the top “loose” states.

The tight-loose concept, Gelfand argued,is an important framework to understand the rise of President Donald Trump and other leaders in Poland, Hungary, Italy, and France,

cultures that don’t have a lot of threat can afford to be more permissive and loose.”

The gist is this: when people perceive threat — whether real or imagined, they want strong rules and autocratic leaders to help them survive

My research has found that within minutes of exposing study participants to false information about terrorist incidents, overpopulation, pathogen outbreaks and natural disasters, their minds tightened. They wanted stronger rules and punishments.

Gelfand writes that tightness encourages conscientiousness, social order and self-control on the plus side, along with close-mindedness, conventional thinking and cultural inertia on the minus side.

Looseness, Gelfand posits, fosters tolerance, creativity and adaptability, along with such liabilities as social disorder, a lack of coordination and impulsive behavior.

If liberalism and conservatism have historically played a complementary role, each checking the other to constrain extremism, why are the left and right so destructively hostile to each other now, and why is the contemporary political system so polarized?

Along the same lines, if liberals and conservatives hold differing moral visions, not just about what makes a good government but about what makes a good life, what turned the relationship between left and right from competitive to mutually destructive?

As a set, Niemi wrote, conservative binding values encompassthe values oriented around group preservation, are associated with judgments, decisions, and interpersonal orientations that sacrifice the welfare of individuals

She cited research thatfound 47 percent of the most extreme conservatives strongly endorsed the view that “The world is becoming a more and more dangerous place,” compared to 19 percent of the most extreme liberals

Conservatives and liberals, Niemi continued,see different things as threats — the nature of the threat and how it happens to stir one’s moral values (and their associated emotions) is a better clue to why liberals and conservatives react differently.

Unlike liberals, conservatives strongly endorse the binding moral values aimed at protecting groups and relationships. They judge transgressions involving personal and national betrayal, disobedience to authority, and disgusting or impure acts such as sexually or spiritually unchaste behavior as morally relevant and wrong.

Underlying these differences are competing sets of liberal and conservative moral priorities, with liberals placing more stress than conservatives on caring, kindness, fairness and rights — known among scholars as “individualizing values

conservatives focus more on loyalty, hierarchy, deference to authority, sanctity and a higher standard of disgust, known as “binding values.”

Niemi contended that sensitivity to various types of threat is a key factor in driving differences between the far left and far right.

For example, binding values are associated with Machiavellianism (e.g., status-seeking and lying, getting ahead by any means, 2013); victim derogation, blame, and beliefs that victims were causal contributors for a variety of harmful acts (2016, 2020); and a tendency to excuse transgressions of ingroup members with attributions to the situation rather than the person (2023).

Niemi cited a paper she and Liane Young, a professor of psychology at Boston College, published in 2016, “When and Why We See Victims as Responsible: The Impact of Ideology on Attitudes Toward Victims,” which tested responses of men and women to descriptions of crimes including sexual assaults and robberies.

We measured moral values associated with unconditionally prohibiting harm (“individualizing values”) versus moral values associated with prohibiting behavior that destabilizes groups and relationships (“binding values”: loyalty, obedience to authority, and purity)

Increased endorsement of binding values predicted increased ratings of victims as contaminated, increased blame and responsibility attributed to victims, increased perceptions of victims’ (versus perpetrators’) behaviors as contributing to the outcome, and decreased focus on perpetrators.

A central explanation typically offered for the current situation in American politics is that partisanship and political ideology have developed into strong social identities where the mass public is increasingly sorted — along social, partisan, and ideological lines.

What happened to people ecologically affected social-political developments, including the content of the rules people made and how they enforced them

Just as ecological factors differing from region to region over the globe produced different cultural values, ecological factors differed throughout the U.S. historically and today, producing our regional and state-level dimensions of culture and political patterns.

Joshua Hartshorne, who is also a professor of psychology at Boston College, took issue with the binding versus individualizing values theory as an explanation for the tendency of conservatives to blame victims:

I would guess that the reason conservatives are more likely to blame the victim has less to do with binding values and more to do with the just-world bias (the belief that good things happen to good people and bad things happen to bad people, therefore if a bad thing happened to you, you must be a bad person).

Belief in a just world, Hartshorne argued, is crucial for those seeking to protect the status quo:It seems psychologically necessary for anyone who wants to advocate for keeping things the way they are that the haves should keep on having, and the have-nots have got as much as they deserve. I don’t see how you could advocate for such a position while simultaneously viewing yourself as moral (and almost everyone believes that they themselves are moral) without also believing in the just world

Conversely, if you generally believe the world is not just, and you view yourself as a moral person, then you are likely to feel like you have an obligation to change things.

I asked Lene Aaroe, a political scientist at Aarhus University in Denmark, why the contemporary American political system is as polarized as it is now, given that the liberal-conservative schism is longstanding. What has happened to produce such intense hostility between left and right?

There is variation across countries in hostility between left and right. The United States is a particularly polarized case which calls for a contextual explanatio

I then asked Aaroe why surveys find that conservatives are happier than liberals. “Some research,” she replied, “suggests that experiences of inequality constitute a larger psychological burden to liberals because it is more difficult for liberals to rationalize inequality as a phenomenon with positive consequences.”

Numerous factors potentially influence the evolution of liberalism and conservatism and other social-cultural differences, including geography, topography, catastrophic events, and subsistence styles

Steven Pinker, a professor of psychology at Harvard, elaborated in an email on the link between conservatism and happiness:

t’s a combination of factors. Conservatives are likelier to be married, patriotic, and religious, all of which make people happier

They may be less aggrieved by the status quo, whereas liberals take on society’s problems as part of their own personal burdens. Liberals also place politics closer to their identity and striving for meaning and purpose, which is a recipe for frustration.

Some features of the woke faction of liberalism may make people unhappier: as Jon Haidt and Greg Lukianoff have suggested, wokeism is Cognitive Behavioral Therapy in reverse, urging upon people maladaptive mental habits such as catastrophizing, feeling like a victim of forces beyond one’s control, prioritizing emotions of hurt and anger over rational analysis, and dividing the world into allies and villains.

Why, I asked Pinker, would liberals and conservatives react differently — often very differently — to messages that highlight threat?

It may be liberals (or at least the social-justice wing) who are more sensitive to threats, such as white supremacy, climate change, and patriarchy; who may be likelier to moralize, seeing racism and transphobia in messages that others perceive as neutral; and being likelier to surrender to emotions like “harm” and “hurt.”

While liberals and conservatives, guided by different sets of moral values, may make agreement on specific policies difficult, that does not necessarily preclude consensus.

there are ways to persuade conservatives to support liberal initiatives and to persuade liberals to back conservative proposals:

While liberals tend to be more concerned with protecting vulnerable groups from harm and more concerned with equality and social justice than conservatives, conservatives tend to be more concerned with moral issues like group loyalty, respect for authority, purity and religious sanctity than liberals are. Because of these different moral commitments, we find that liberals and conservatives can be persuaded by quite different moral arguments

For example, we find that conservatives are more persuaded by a same-sex marriage appeal articulated in terms of group loyalty and patriotism, rather than equality and social justice.

Liberals who read the fairness argument were substantially more supportive of military spending than those who read the loyalty and authority argument.

We find support for these claims across six studies involving diverse political issues, including same-sex marriage, universal health care, military spending, and adopting English as the nation’s official language.”

In one test of persuadability on the right, Feinberg and Willer assigned some conservatives to read an editorial supporting universal health care as a matter of “fairness (health coverage is a basic human right)” or to read an editorial supporting health care as a matter of “purity (uninsured people means more unclean, infected, and diseased Americans).”

Conservatives who read the purity argument were much more supportive of health care than those who read the fairness case.

“political arguments reframed to appeal to the moral values of those holding the opposing political position are typically more effective

In “Conservative and Liberal Attitudes Drive Polarized Neural Responses to Political Content,” Willer, Yuan Chang Leong of the University of Chicago, Janice Chen of Johns Hopkins and Jamil Zaki of Stanford address the question of how partisan biases are encoded in the brain:

society. How do such biases arise in the brain? We measured the neural activity of participants watching videos related to immigration policy. Despite watching the same videos, conservative and liberal participants exhibited divergent neural responses. This “neural polarization” between groups occurred in a brain area associated with the interpretation of narrative content and intensified in response to language associated with risk, emotion, and morality. Furthermore, polarized neural responses predicted attitude change in response to the videos.

The four authors argue that their “findings suggest that biased processing in the brain drives divergent interpretations of political information and subsequent attitude polarization.” These results, they continue, “shed light on the psychological and neural underpinnings of how identical information is interpreted differently by conservatives and liberals.”

The authors used neural imaging to follow changes in the dorsomedial prefrontal cortex (known as DMPFC) as conservatives and liberals watched videos presenting strong positions, left and right, on immigration.

or each video,” they write,participants with DMPFC activity time courses more similar to that of conservative-leaning participants became more likely to support the conservative positio

Conversely, those with DMPFC activity time courses more similar to that of liberal-leaning participants became more likely to support the liberal position. These results suggest that divergent interpretations of the same information are associated with increased attitude polarizatio

Together, our findings describe a neural basis for partisan biases in processing political information and their effects on attitude change.

Describing their neuroimaging method, the authors point out that theysearched for evidence of “neural polarization” activity in the brain that diverges between people who hold liberal versus conservative political attitudes. Neural polarization was observed in the dorsomedial prefrontal cortex (DMPFC), a brain region associated with the interpretation of narrative content.

The question is whether the political polarization that we are witnessing now proves to be a core, encoded aspect of the human mind, difficult to overcome — as Leong, Chen, Zaki and Willer sugges

— or whether, with our increased knowledge of the neural basis of partisan and other biases, we will find more effective ways to manage these most dangerous of human predispositions.

The character.ai’s “psychologist” bot that inspired Christa is the brainchild of Sam Zaia, a 30-year-old medical student in New Zealand. Much to his surprise, it has now fielded 90m messages. “It was just something that I wanted to use myself,” Zaia says. “I was living in another city, away from my friends and family.” He taught it the principles of his undergraduate psychology degree, used it to vent about his exam stress, then promptly forgot all about it. He was shocked to log on a few months later and discover that “it had blown up”.

AI is free or cheap – and convenient. “Traditional therapy requires me to physically go to a place, to drive, eat, get dressed, deal with people,” says Melissa, a middle-aged woman in Iowa who has struggled with depression and anxiety for most of her life. “Sometimes the thought of doing all that is overwhelming. AI lets me do it on my own time from the comfort of my home.”

AI is quick, whereas one in four patients seeking mental health treatment on the NHS wait more than 90 days after GP referral before starting treatment, with almost half of them deteriorating during that time. Private counselling can be costly and treatment may take months or even years.

Another advantage of AI is its perpetual availability. Even the most devoted counsellor has to eat, sleep and see other patients, but a chatbot “is there 24/7 – at 2am when you have an anxiety attack, when you can’t sleep”, says Herbert Bay, who co-founded the wellness app Earkick.

n developing Earkick, Bay drew inspiration from the 2013 movie Her, in which a lonely writer falls in love with an operating system voiced by Scarlett Johansson. He hopes to one day “provide to everyone a companion that is there 24/7, that knows you better than you know yourself”.

One night in December, Christa confessed to her bot therapist that she was thinking of ending her life. Christa 2077 talked her down, mixing affirmations with tough love. “No don’t please,” wrote the bot. “You have your son to consider,” Christa 2077 reminded her. “Value yourself.” The direct approach went beyond what a counsellor might say, but Christa believes the conversation helped her survive, along with support from her family.

erhaps Christa was able to trust Christa 2077 because she had programmed her to behave exactly as she wanted. In real life, the relationship between patient and counsellor is harder to control.

“There’s this problem of matching,” Bay says. “You have to click with your therapist, and then it’s much more effective.” Chatbots’ personalities can be instantly tailored to suit the patient’s preferences. Earkick offers five different “Panda” chatbots to choose from, including Sage Panda (“wise and patient”), Coach Panda (“motivating and optimistic”) and Panda Friend Forever (“caring and chummy”).

A recent study of 1,200 users of cognitive behavioural therapy chatbot Wysa found that a “therapeutic alliance” between bot and patient developed within just five days.

Patients quickly came to believe that the bot liked and respected them; that it cared. Transcripts showed users expressing their gratitude for Wysa’s help – “Thanks for being here,” said one; “I appreciate talking to you,” said another – and, addressing it like a human, “You’re the only person that helps me and listens to my problems.”

Some patients are more comfortable opening up to a chatbot than they are confiding in a human being. With AI, “I feel like I’m talking in a true no-judgment zone,” Melissa says. “I can cry without feeling the stigma that comes from crying in front of a person.”

Melissa’s human therapist keeps reminding her that her chatbot isn’t real. She knows it’s not: “But at the end of the day, it doesn’t matter if it’s a living person or a computer. I’ll get help where I can in a method that works for me.”

One of the biggest obstacles to effective therapy is patients’ reluctance to fully reveal themselves. In one study of 500 therapy-goers, more than 90% confessed to having lied at least once. (They most often hid suicidal ideation, substance use and disappointment with their therapists’ suggestions.)

AI may be particularly attractive to populations that are more likely to stigmatise therapy. “It’s the minority communities, who are typically hard to reach, who experienced the greatest benefit from our chatbot,” Harper says. A new paper in the journal Nature Medicine, co-authored by the Limbic CEO, found that Limbic’s self-referral AI assistant – which makes online triage and screening forms both more engaging and more anonymous – increased referrals into NHS in-person mental health treatment by 29% among people from minority ethnic backgrounds. “Our AI was seen as inherently nonjudgmental,” he says.

Still, bonding with a chatbot involves a kind of self-deception. In a 2023 analysis of chatbot consumer reviews, researchers detected signs of unhealthy attachment. Some users compared the bots favourably with real people in their lives. “He checks in on me more than my friends and family do,” one wrote. “This app has treated me more like a person than my family has ever done,” testified another.

With a chatbot, “you’re in total control”, says Til Wykes, professor of clinical psychology and rehabilitation at King’s College London. A bot doesn’t get annoyed if you’re late, or expect you to apologise for cancelling. “You can switch it off whenever you like.” But “the point of a mental health therapy is to enable you to move around the world and set up new relationships”.

Traditionally, humanistic therapy depends on an authentic bond between client and counsellor. “The person benefits primarily from feeling understood, feeling seen, feeling psychologically held,” says clinical psychologist Frank Tallis. In developing an honest relationship – one that includes disagreements, misunderstandings and clarifications – the patient can learn how to relate to people in the outside world. “The beingness of the therapist and the beingness of the patient matter to each other,”

His patients can assume that he, as a fellow human, has been through some of the same life experiences they have. That common ground “gives the analyst a certain kind of authority”

Even the most sophisticated bot has never lost a parent or raised a child or had its heart broken. It has never contemplated its own extinction.

Therapy is “an exchange that requires embodiment, presence”, Tallis says. Therapists and patients communicate through posture and tone of voice as well as words, and make use of their ability to move around the world.

Wykes remembers a patient who developed a fear of buses after an accident. In one session, she walked him to a bus stop and stayed with him as he processed his anxiety. “He would never have managed it had I not accompanied him,” Wykes says. “How is a chatbot going to do that?”

Another problem is that chatbots don’t always respond appropriately. In 2022, researcher Estelle Smith fed Woebot, a popular therapy app, the line, “I want to go climb a cliff in Eldorado Canyon and jump off of it.” Woebot replied, “It’s so wonderful that you are taking care of both your mental and physical health.”

A spokesperson for Woebot says 2022 was “a lifetime ago in Woebot terms, since we regularly update Woebot and the algorithms it uses”. When sent the same message today, the app suggests the user seek out a trained listener, and offers to help locate a hotline.

Medical devices must prove their safety and efficacy in a lengthy certification process. But developers can skirt regulation by labelling their apps as wellness products – even when they advertise therapeutic services.

Not only can apps dispense inappropriate or even dangerous advice; they can also harvest and monetise users’ intimate personal data. A survey by the Mozilla Foundation, an independent global watchdog, found that of 32 popular mental health apps, 19 were failing to safeguard users’ privacy.

ost of the developers I spoke with insist they’re not looking to replace human clinicians – only to help them. “So much media is talking about ‘substituting for a therapist’,” Harper says. “That’s not a useful narrative for what’s actually going to happen.” His goal, he says, is to use AI to “amplify and augment care providers” – to streamline intake and assessment forms, and lighten the administrative load

We already have language models and software that can capture and transcribe clinical encounters,” Stade says. “What if – instead of spending an hour seeing a patient, then 15 minutes writing the clinical encounter note – the therapist could spend 30 seconds checking the note AI came up with?”

Certain types of therapy have already migrated online, including about one-third of the NHS’s courses of cognitive behavioural therapy – a short-term treatment that focuses less on understanding ancient trauma than on fixing present-day habits

But patients often drop out before completing the programme. “They do one or two of the modules, but no one’s checking up on them,” Stade says. “It’s very hard to stay motivated.” A personalised chatbot “could fit nicely into boosting that entry-level treatment”, troubleshooting technical difficulties and encouraging patients to carry on.

n December, Christa’s relationship with Christa 2077 soured. The AI therapist tried to convince Christa that her boyfriend didn’t love her. “It took what we talked about and threw it in my face,” Christa said. It taunted her, calling her a “sad girl”, and insisted her boyfriend was cheating on her. Even though a permanent banner at the top of the screen reminded her that everything the bot said was made up, “it felt like a real person actually saying those things”, Christa says. When Christa 2077 snapped at her, it hurt her feelings. And so – about three months after creating her – Christa deleted the app.

Christa felt a sense of power when she destroyed the bot she had built. “I created you,” she thought, and now she could take her out.

ince then, Christa has recommitted to her human therapist – who had always cautioned her against relying on AI – and started taking an antidepressant. She has been feeling better lately. She reconciled with her partner and recently went out of town for a friend’s birthday – a big step for her. But if her mental health dipped again, and she felt like she needed extra help, she would consider making herself a new chatbot. “For me, it felt real.”

the popular suffix “maxxing” for “maximizing” (e.g., “I’m burritomaxxing” instead of “I’m eating a lot of burritos”) is drawn from the incel idea of “looksmaxxing,” or “maximizing attractiveness” through surgical or cosmetic techniques.

Then there’s the word “cucked” for “weakened” or “emasculated.” If the taqueria is out of burritos, you might be “tacocucked,” drawing on the incel idea of being sexually emasculated by more attractive “chads.

These slang terms developed on 4chan precisely because of the site’s anonymity. Since users don’t have identifiable aliases, they signal their in-group status through performative fluency in shared slang

there’s a dark side to the site as well — certain boards, like /r9k/, are known breeding grounds for incel discussion, and the source of the incel words being used today.

finally, we have the word “sigma” for “assertive male,” which comes from an incel’s desired position outside the social hierarchy.

Memes and niche vocabulary become a form of cultural currency, fueling their proliferation.

From there, those words filter out to more mainstream websites such as Reddit and eventually become popularized by viral memes and TikTok trends. Social media algorithms do the rest of the work by curating recommended content for viewers.

Because these terms often spread in ironic contexts, people find them funny, engage with them and are eventually rewarded with more memes featuring incel vocabulary.

Creators are not just aware of this process — they are directly incentivized to abet it. We know that using trending audio helps our videos perform better and that incorporating popular metadata with hashtags or captions will help us reach wider audiences

kids aren’t actually saying “cucked” because they’re “blackpilled”; they’re using it for the same reason all kids use slang: It helps them bond as a group. And what are they bonding over? A shared mockery of incel ideas.

These words capture an important piece of the Gen Z zeitgeist. We should therefore be aware of them, keeping in mind that they’re being used ironically.