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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]

Microsoft leaders felt “enormous urgency” for it to be the company to bring this technology to market, because others around the world are working on similar tech but might not have the resources or inclination to build it as responsibly, says Sarah Bird, a leader on Microsoft’s responsible AI team.

One common starting point for such models is what is essentially a download or “scrape” of most of the internet. In the past, these language models were used to try to understand text, but the new generation of them, part of the revolution in “generative” AI, uses those same models to create texts by trying to guess, one word at a time, the most likely word to come next in any given sequence.

Wide-scale testing gives Microsoft and OpenAI a big competitive edge by enabling them to gather huge amounts of data about how people actually use such chatbots. Both the prompts users input into their systems, and the results their AIs spit out, can then be fed back into a complicated system—which includes human content moderators paid by the companies—to improve it.

, being first to market with a chat-based AI gives these companies a huge initial lead over companies that have been slower to release their own chat-based AIs, such as Google.

rarely has an experiment like Microsoft and OpenAI’s been rolled out so quickly, and at such a broad scale.

Among those who build and study these kinds of AIs, Mr. Altman’s case for experimenting on the global public has inspired responses ranging from raised eyebrows to condemnation.

The fact that we’re all guinea pigs in this experiment doesn’t mean it shouldn’t be conducted, says Nathan Lambert, a research scientist at the AI startup Huggingface.

“I would kind of be happier with Microsoft doing this experiment than a startup, because Microsoft will at least address these issues when the press cycle gets really bad,” says Dr. Lambert. “I think there are going to be a lot of harms from this kind of AI, and it’s better people know they are coming,” he adds.

Others, particularly those who study and advocate for the concept of “ethical AI” or “responsible AI,” argue that the global experiment Microsoft and OpenAI are conducting is downright dangerous

Celeste Kidd, a professor of psychology at University of California, Berkeley, studies how people acquire knowledge

Her research has shown that people learning about new things have a narrow window in which they form a lasting opinion. Seeing misinformation during this critical initial period of exposure to a new concept—such as the kind of misinformation that chat-based AIs can confidently dispense—can do lasting harm, she says.

Dr. Kidd likens OpenAI’s experimentation with AI to exposing the public to possibly dangerous chemicals. “Imagine you put something carcinogenic in the drinking water and you were like, ‘We’ll see if it’s carcinogenic.’ After, you can’t take it back—people have cancer now,”

Part of the challenge with AI chatbots is that they can sometimes simply make things up. Numerous examples of this tendency have been documented by users of both ChatGPT and OpenA

These models also tend to be riddled with biases that may not be immediately apparent to users. For example, they can express opinions gleaned from the internet as if they were verified facts

When millions are exposed to these biases across billions of interactions, this AI has the potential to refashion humanity’s views, at a global scale, says Dr. Kidd.

OpenAI has talked publicly about the problems with these systems, and how it is trying to address them. In a recent blog post, the company said that in the future, users might be able to select AIs whose “values” align with their own.

“We believe that AI should be a useful tool for individual people, and thus customizable by each user up to limits defined by society,” the post said.

Eliminating made-up information and bias from chat-based search engines is impossible given the current state of the technology, says Mark Riedl, a professor at Georgia Institute of Technology who studies artificial intelligence

He believes the release of these technologies to the public by Microsoft and OpenAI is premature. “We are putting out products that are still being actively researched at this moment,” he adds. 

in other areas of human endeavor—from new drugs and new modes of transportation to advertising and broadcast media—we have standards for what can and cannot be unleashed on the public. No such standards exist for AI, says Dr. Riedl.

To modify these AIs so that they produce outputs that humans find both useful and not-offensive, engineers often use a process called “reinforcement learning through human feedback.

that’s a fancy way of saying that humans provide input to the raw AI algorithm, often by simply saying which of its potential responses to a query are better—and also which are not acceptable at all.

Microsoft’s and OpenAI’s globe-spanning experiments on millions of people are yielding a fire hose of data for both companies. User-entered prompts and the AI-generated results are fed back through a network of paid human AI trainers to further fine-tune the models,

Huggingface’s Dr. Lambert says that any company, including his own, that doesn’t have this river of real-world usage data helping it improve its AI is at a huge disadvantage

In chatbots, in some autonomous-driving systems, in the unaccountable AIs that decide what we see on social media, and now, in the latest applications of AI, again and again we are the guinea pigs on which tech companies are testing new technology.

It may be the case that there is no other way to roll out this latest iteration of AI—which is already showing promise in some areas—at scale. But we should always be asking, at times like these: At what price?

, we know from the science of linguistics and the philosophy of knowledge that they differ profoundly from how humans reason and use language. These differences place significant limitations on what these programs can do, encoding them with ineradicable defects.

It is at once comic and tragic, as Borges might have noted, that so much money and attention should be concentrated on so little a thing — something so trivial when contrasted with the human mind, which by dint of language, in the words of Wilhelm von Humboldt, can make “infinite use of finite means,” creating ideas and theories with universal reach.

The human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data and extrapolating the most likely conversational response or most probable answer to a scientific question

the human mind is a surprisingly efficient and even elegant system that operates with small amounts of information; it seeks not to infer brute correlations among data points but to create explanations

such programs are stuck in a prehuman or nonhuman phase of cognitive evolution. Their deepest flaw is the absence of the most critical capacity of any intelligence: to say not only what is the case, what was the case and what will be the case — that’s description and prediction — but also what is not the case and what could and could not be the case

Those are the ingredients of explanation, the mark of true intelligence.

Here’s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, “The apple falls.” That is a description. A prediction might have been the statement “The apple will fall if I open my hand.”

an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like “Any such object would fall,” plus the additional clause “because of the force of gravity” or “because of the curvature of space-time” or whatever. That is a causal explanation: “The apple would not have fallen but for the force of gravity.” That is thinking.

The crux of machine learning is description and prediction; it does not posit any causal mechanisms or physical laws

any human-style explanation is not necessarily correct; we are fallible. But this is part of what it means to think: To be right, it must be possible to be wrong. Intelligence consists not only of creative conjectures but also of creative criticism. Human-style thought is based on possible explanations and error correction, a process that gradually limits what possibilities can be rationally considered.

ChatGPT and similar programs are, by design, unlimited in what they can “learn” (which is to say, memorize); they are incapable of distinguishing the possible from the impossible.

Whereas humans are limited in the kinds of explanations we can rationally conjecture, machine learning systems can learn both that the earth is flat and that the earth is round. They trade merely in probabilities that change over time.

For this reason, the predictions of machine learning systems will always be superficial and dubious.

some machine learning enthusiasts seem to be proud that their creations can generate correct “scientific” predictions (say, about the motion of physical bodies) without making use of explanations (involving, say, Newton’s laws of motion and universal gravitation). But this kind of prediction, even when successful, is pseudoscienc

While scientists certainly seek theories that have a high degree of empirical corroboration, as the philosopher Karl Popper noted, “we do not seek highly probable theories but explanations; that is to say, powerful and highly improbable theories.”

The theory that apples fall to earth because mass bends space-time (Einstein’s view) is highly improbable, but it actually tells you why they fall. True intelligence is demonstrated in the ability to think and express improbable but insightful things.

This means constraining the otherwise limitless creativity of our minds with a set of ethical principles that determines what ought and ought not to be (and of course subjecting those principles themselves to creative criticism)

True intelligence is also capable of moral thinking

To be useful, ChatGPT must be empowered to generate novel-looking output; to be acceptable to most of its users, it must steer clear of morally objectionable content

In 2016, for example, Microsoft’s Tay chatbot (a precursor to ChatGPT) flooded the internet with misogynistic and racist content, having been polluted by online trolls who filled it with offensive training data. How to solve the problem in the future? In the absence of a capacity to reason from moral principles, ChatGPT was crudely restricted by its programmers from contributing anything novel to controversial — that is, important — discussions. It sacrificed creativity for a kind of amorality.

Here, ChatGPT exhibits something like the banality of evil: plagiarism and apathy and obviation. It summarizes the standard arguments in the literature by a kind of super-autocomplete, refuses to take a stand on anything, pleads not merely ignorance but lack of intelligence and ultimately offers a “just following orders” defense, shifting responsibility to its creators.

In short, ChatGPT and its brethren are constitutionally unable to balance creativity with constraint. They either overgenerate (producing both truths and falsehoods, endorsing ethical and unethical decisions alike) or undergenerate (exhibiting noncommitment to any decisions and indifference to consequences). Given the amorality, faux science and linguistic incompetence of these systems, we can only laugh or cry at their popularity.

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.

New financial constraints on family formation are a potential cause, as implied by another striking finding in the Journal poll — 78 percent of adults lack confidence this generation of children will enjoy a better life than they do.

Yet a recent analysis for the Aspen Economic Strategy Group by Melissa S. Kearney and Phillip B. Levine, economics professors at the University of Maryland and Wellesley College, respectively, determined that “beyond the temporary effects of the Great Recession, no recent economic or policy change is responsible for a meaningful share of the decline in the US fertility rate since 2007.”

Their study took account of such factors as the high cost of child care, student debt service and housing as well as Medicaid coverage and the wider availability of long-acting reversible contraception. Yet they had “no success finding evidence” that any of these were decisive.

Kearney and Levine speculated instead that the answers lie in the cultural zeitgeist — “shifting priorities across cohorts of young adults,”

the timing and the magnitude of such a demographic sea-change cry out for explanation. What happened in 2007?

another event that year: Apple released the first iPhone, a revolutionary cultural moment if there ever was one. The ensuing smartphone-enabled social media boom — Facebook had opened membership to anyone older than 13 in 2006 — forever changed how human beings relate with one another.

We are just beginning to understand this development’s effect on mental health, education, religious observance, community cohesion — everything. Why wouldn’t it also affect people’s willingness to have children?

one indirect way new media affect childbearing rates is through “time competition effects” — essentially, hours spent watching the tube cannot be spent forming romantic partnerships.

a 2021 review of survey data on young adults and adolescents in the United States and other countries, the years between 2009 and 2018 saw a marked decline in reported sexual activity.

the authors hypothesized that people are distracted from the search for partners by “increasing use of computer games and social media.

during the late 20th century, Brazil’s fertility rates fell after women who watched soap operas depicting smaller families sought to emulate them by having fewer children themselves.

This may be an area where incentives do not influence behavior, at least not enough. Whether the cultural shift to lower birthrates occurs on an accelerated basis, as in the United States after 2007, or gradually, as it did in Japan, it appears permanent — “sticky,” as policy wonks say.

While people praised Finland’s strong social safety net and spoke glowingly of the psychological benefits of nature and the personal joys of sports or music, they also talked about guilt, anxiety and loneliness. Rather than “happy,” they were more likely to characterize Finns as “quite gloomy,” “a little moody” or not given to unnecessary smiling

Many also shared concerns about threats to their way of life, including possible gains by a far-right party in the country’s elections in April, the war in Ukraine and a tense relationship with Russia, which could worsen now that Finland is set to join NATO.

It turns out even the happiest people in the world aren’t that happy. But they are something more like content.

Finns derive satisfaction from leading sustainable lives and perceive financial success as being able to identify and meet basic need

“In other words,” he wrote in an email, “when you know what is enough, you are happy.”

“‘Happiness,’ sometimes it’s a light word and used like it’s only a smile on a face,” Teemu Kiiski, the chief executive of Finnish Design Shop, said. “But I think that this Nordic happiness is something more foundational.”

e conventional wisdom is that it’s easier to be happy in a country like Finland where the government ensures a secure foundation on which to build a fulfilling life and a promising future. But that expectation can also create pressure to live up to the national reputation.

“We are very privileged and we know our privilege,” said Clara Paasimaki, 19, one of Ms. Hansen’s students in Kokkola, “so we are also scared to say that we are discontent with anything, because we know that we have it so much better than other people,” especially in non-Nordic countries.

“The fact that Finland has been ‘the happiest country on earth’ for six years in a row could start building pressure on people,” he wrote in an email. “If we Finns are all so happy, why am I not happy?

Since immigrating from Zimbabwe in 1992, Julia Wilson-Hangasmaa, 59, has come to appreciate the freedom Finland affords people to pursue their dreams without worrying about meeting basic needs

“Back in the day when it wasn’t that easy to survive the winter, people had to struggle, and then it’s kind of been passed along the generations,” said Ms. Paasimaki’s classmate Matias From, 18. “Our parents were this way. Our grandparents were this way. Tough and not worrying about everything. Just living life.”

The Finnish way of life is summed up in “sisu,” a trait said to be part of the national character. The word roughly translates to “grim determination in the face of hardships,” such as the country’s long winters: Even in adversity, a Finn is expected to persevere, without complaining.

When she returns to her home country, she is struck by the “good energy” that comes not from the satisfaction of sisu but from exuberant joy.

“What I miss the most, I realize when I enter Zimbabwe, are the smiles,” she said, among “those people who don’t have much, compared to Western standards, but who are rich in spirit.”

Many of our subjects cited the abundance of nature as crucial to Finnish happiness: Nearly 75 percent of Finland is covered by forest, and all of it is open to everyone thanks to a law known as “jokamiehen oikeudet,” or “everyman’s right,” that entitles people to roam freely throughout any natural areas, on public or privately owned land.

“I enjoy the peace and movement in nature,” said Helina Marjamaa, 66, a former track athlete who represented the country at the 1980 and 1984 Olympic Games. “That’s where I get strength. Birds are singing, snow is melting, and nature is coming to life. It’s just incredibly beautiful.”

“I am worried with this level of ignorance we have toward our own environment,” he said, citing endangered species and climate change. The threat, he said, “still doesn’t seem to shift the political thinking.”

Born 17 years after Finland won independence from Russia, Eeva Valtonen has watched her homeland transform: from the devastation of World War II through years of rebuilding to a nation held up as an exemplar to the world.

“My mother used to say, ‘Remember, the blessing in life is in work, and every work you do, do it well,’” Ms. Valtonen, 88, said. “I think Finnish people have been very much the same way. Everybody did everything together and helped each other.”

Maybe it isn’t that Finns are so much happier than everyone else. Maybe it’s that their expectations for contentment are more reasonable, and if they aren’t met, in the spirit of sisu, they persevere.

“We don’t whine,” Ms. Eerikainen said. “We just do.”

Musk seems willing to grant this power to racists, conspiracy theorists, and trolls. This isn’t great for reasonable people who want to have nuanced conversations on social media, but the joke has always been on them. Twitter isn’t that place, and it never will be.

one of Musk’s first moves after taking over was to fire the company’s head of policy—an individual who had publicly stated a commitment to both free speech and preventing abuse.

On Friday, Musk tweeted that Twitter would be “forming a content moderation council with widely diverse viewpoints,” noting that “no major content decisions [would] happen before that council convenes.” Just three hours later, replying to a question about lifting a suspension on The Daily Wire’s Jordan Peterson, Musk signaled that maybe that wasn’t exactly right; he tweeted: “Anyone suspended for minor & dubious reasons will be freed from Twitter jail.” He says he wants a democratic council, yet he’s also setting policy by decree.

Perhaps most depressingly, this behavior is quite familiar. As Techdirt’s Mike Masnick has pointed out, we are all stuck “watching Musk speed run the content moderation learning curve” and making the same mistakes that social-media executives made with their platforms in their first years at the helm.

Musk has charged himself with solving the central, seemingly intractable issue at the core of hundreds of years of debate about free speech. In the social-media era, no entity has managed to balance preserving both free speech and genuine open debate across the internet at scale.

Musk hasn’t just given himself a nearly impossible task; he’s also created conditions for his new company’s failure. By acting incoherently as a leader and lording the prospect of mass terminations over his employees, he’s created a dysfunctional and chaotic work environment for the people who will ultimately execute his changes to the platform

What happened in 2012, when the oldest Gen-Z babies were in their middle teens? That was the year Facebook acquired Instagram and young people flocked to the latter site. It was also “the beginning of the selfie era.”

Mr. Haidt’s research, confirmed by that of others, shows that depression rates started to rise “all of a sudden” around 2013, “especially for teen girls,” but “it’s only Gen Z, not the older generations.” If you’d stopped collecting data in 2011, he says, you’d see little change from previous years. “By 2015 it’s an epidemic.” (His data are available in an open-source document.)

Mr. Haidt imagines “literally launching our children into outer space” and letting their bodies grow there: “They would come out deformed and broken. Their limbs wouldn’t be right. You can’t physically grow up in outer space. Human bodies can’t do that.” Yet “we basically do that to them socially. We launched them into outer space around the year 2012,” he says, “and then we expect that they will grow up normally without having normal human experiences.”

He calls this phenomenon “compare and despair” and says: “It seems social because you’re communicating with people. But it’s performative. You don’t actually get social relationships. You get weak, fake social links.”

That meant the first social-media generation was one of “weakened kids” who “hadn’t practiced the skills of adulthood in a low-stakes environment” with other children. They were deprived of “the normal toughening, the normal strengthening, the normal anti-fragility.

Now, their childhood “is largely just through the phone. They no longer even hang out together.” Teenagers even drive less than earlier generations did.

Mr. Haidt especially worries about girls. By 2020 more than 25% of female teenagers had “a major depression.” The comparable number for boys was just under 9%.

The comparable numbers for millennials at the same age registered at half the Gen-Z rate: about 13% for girls and 5% for boys. “Kids are on their devices all the time,”

Most girls, by contrast, are drawn to “visual platforms,” Instagram and TikTok in particular. “Those are about display and performance. You post your perfect life, and then you flip through the photos of other girls who have a more perfect life, and you feel depressed.

Mr. Haidt says he has no antipathy toward the young, and he calls millennials “amazing.”

“Social media is incompatible with liberal democracy because it has moved conversation, and interaction, into the center of the Colosseum. We’re not there to talk to each other. We’re there to perform” before spectators who “want blood.”

To illustrate his point about Gen Z, Mr. Haidt challenges people to name young people today who are “really changing the world, who are doing big things that have an impact beyond their closed ecosystem.”

He can think of only two, neither of them American: Greta Thunberg, 19, the Swedish climate militant, and Malala Yousafzai, 25, the Pakistani advocate for female education

I’m predicting that they will be less effective, less impactful, than previous generations.” Why? “You should always keep your eye on whether people are in ‘discover mode’ or ‘defend mode.’ ” In the former mode, you seize opportunities to be creative. In the latter, “you’re not creative, you’re not future-thinking, you’re focused on threats in the present.”

University students who matriculated starting in 2014 or so have arrived on campus in defend mode: “Here they are in the safest, most welcoming, most inclusive, most antiracist places on the planet, but many of them were acting like they were entering some sort of dystopian, threatening, immoral world.”

56% of liberal women 18 to 29 responded affirmatively to the question: Has a doctor or other healthcare provider ever told you that you have a mental health condition? “Some of that,” Mr. Haidt says, “has to be just self-presentational,” meaning imagined.

This new ideology . . . valorizes victimhood. And if your sub-community motivates you to say you have an anxiety disorder, how is this going to affect you for the rest of your life?” He answers his own question: “You’re not going to take chances, you’re going to ask for accommodations, you’re going to play it safe, you’re not going to swing for the fences, you’re not going to start your own company.”

Whereas millennial women are doing well, “Gen-Z women, because they’re so anxious, are going to be less successful than Gen-Z men—and that’s saying a lot, because Gen-Z men are messed up, too.”

The problem, he says, is distinct to the U.S. and other English-speaking developed countries: “You don’t find it as much in Europe, and hardly at all in Asia.” Ideas that are “nurtured around American issues of race and gender spread instantly to the U.K. and Canada. But they don’t necessarily spread to France and Germany, China and Japan.”

something I hear from a lot of managers, that it’s very difficult to supervise their Gen-Z employees, that it’s very difficult to give them feedback.” That makes it hard for them to advance professionally by learning to do their jobs better.

“this could severely damage American capitalism.” When managers are “afraid to speak up honestly because they’ll be shamed on Twitter or Slack, then that organization becomes stupid.” Mr. Haidt says he’s “seen a lot of this, beginning in American universities in 2015. They all got stupid in the same way. They all implemented policies that backfire.”

Mr. Haidt, who describes himself as “a classical liberal like John Stuart Mill,” also laments the impact of social media on political discourse

Social media and selfies hit a generation that had led an overprotected childhood, in which the age at which children were allowed outside on their own by parents had risen from the norm of previous generations, 7 or 8, to between 10 and 12.

Is there a solution? “I’d raise the age of Internet adulthood to 16,” he says—“and enforce it.”

By contrast, “life went onto phone-based apps 10 years ago, and the protections we have for children are zero, absolutely zero.” The damage to Generation Z from social media “so vastly exceeds the damage from Covid that we’re going to have to act.”

Gen Z, he says, “is not in denial. They recognize that this app-based life is really bad for them.” He reports that they wish they had childhoods more like those of their parents, in which they could play outside and have adventur

The Samsung threat represented the first potential crack in Google’s seemingly impregnable search business, which was worth $162 billion last year.

Modernizing its search engine has become an obsession at Google, and the planned changes could put new A.I. technology in phones and homes all over the world.

Google has been worried about A.I.-powered competitors since OpenAI, a San Francisco start-up that is working with Microsoft, demonstrated a chatbot called ChatGPT in November. About two weeks later, Google created a task force in its search division to start building A.I. products,

Google has been doing A.I. research for years. Its DeepMind lab in London is considered one of the best A.I. research centers in the world, and the company has been a pioneer with A.I. projects, such as self-driving cars and the so-called large language models that are used in the development of chatbots. In recent years, Google has used large language models to improve the quality of its search results, but held off on fully adopting A.I. because it has been prone to generating false and biased statements.

Now the priority is winning control of the industry’s next big thing. Last month, Google released its own chatbot, Bard, but the technology received mixed reviews.

The system would learn what users want to know based on what they’re searching when they begin using it. And it would offer lists of preselected options for objects to buy, information to research and other information. It would also be more conversational — a bit like chatting with a helpful person.

Magi would keep ads in the mix of search results. Search queries that could lead to a financial transaction, such as buying shoes or booking a flight, for example, would still feature ads on their results pages.

Last week, Google invited some employees to test Magi’s features, and it has encouraged them to ask the search engine follow-up questions to judge its ability to hold a conversation. Google is expected to release the tools to the public next month and add more features in the fall, according to the planning document.

The company plans to initially release the features to a maximum of one million people. That number should progressively increase to 30 million by the end of the year. The features will be available exclusively in the United States.

Google has also explored efforts to let people use Google Earth’s mapping technology with help from A.I. and search for music through a conversation with a chatbot

A tool called GIFI would use A.I. to generate images in Google Image results.

Tivoli Tutor, would teach users a new language through open-ended A.I. text conversations.

Yet another product, Searchalong, would let users ask a chatbot questions while surfing the web through Google’s Chrome browser. People might ask the chatbot for activities near an Airbnb rental, for example, and the A.I. would scan the page and the rest of the internet for a response.

“If we are the leading search engine and this is a new attribute, a new feature, a new characteristic of search engines, we want to make sure that we’re in this race as well,”

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

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

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

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

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

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

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

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

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

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

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

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

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

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

In an Atlantic essay, “Why The Past Ten Years of American Life have Been Uniquely Stupid,” and in a follow-up piece, Haidt argued that the Age of Gutenberg–of books and the depth understanding that comes with them–ended somewhere around 2014 with the rise of “Share,” “Like” and “Retweet” buttons that opened the way for trolls, hucksters and Trumpists

The new age of “hyper-virality,” he writes, has given us both January 6 and cancel culture–ugly polarization in both directions. On the subject of stupidification, we should add the fact that high school students now get virtually their entire stock of knowledge about the world from digital platforms.

Haidt proposed several reforms, including modifying Facebook’s “Share” function and requiring “user verification” to get rid of trolls. But he doesn’t really believe in his own medicine

Haidt said that the era of “shared understanding” is over–forever. When I asked if he could envision changes that would help protect democracy, Haidt quoted Goldfinger: “Do you expect me to talk?” “No, Mr. Bond, I expect you to die!”

Social media is a public health hazard–the cognitive equivalent of tobacco and sugary drinks. Adopting a public health model, we could, for examople, ban the use of algorithms to reduce virality, or even require social media platforms to adopt a subscription rather than advertising revenue model and thus remove their incentive to amass ev er more eyeballs.

We could, but we won’t, because unlike other public health hazards, digital platforms are forms of speech. Fox New is probably responsible for more polarization than all social media put together, but the federal government could not compel it–and all other media firms–to change its revenue model.

If Mark Zuckerberg or Elon Musk won’t do so out of concern for the public good–a pretty safe bet–they could be compelled to do so only by public or competitive pressure. 

Taiwan has provide resilient because its society is resilient; people reject China’s lies. We, here, don’t lack for fact-checkers, but rather for people willing to believe them. The problem is not the technology, but ourselves.

you have to wonder if people really are repelled by our poisonous discourse, or by the hailstorm of disinformation, or if they just want to live comfortably inside their own bubble, and not somebody else’

If Jonathan Haidt is right, it’s not because we’ve created a self-replicating machine that is destined to annihilate reason; it’s because we are the self-replicating machine.

One calculation performed by an audience demographics firm found 32 million connections to male followers among the 5,000 accounts examined by The Times.

Interacting with the men opens the door to abuse. Some flatter, bully and blackmail girls and their parents to get racier and racier images. The Times monitored separate exchanges on Telegram, the messaging app, where men openly fantasize about sexually abusing the children they follow on Instagram and extol the platform for making the images so readily available.

“It’s like a candy store

The troubling interactions on Instagram come as social media companies increasingly dominate the cultural landscape and the internet is seen as a career path of its own.

Nearly one in three preteens lists influencing as a career goal, and 11 percent of those born in Generation Z, between 1997 and 2012, describe themselves as influencers.

The so-called creator economy surpasses $250 billion worldwide, according to Goldman Sachs, with U.S. brands spending more than $5 billion a year on influencers.

Health and technology experts have recently cautioned that social media presents a “profound risk of harm” for girls. Constant comparisons to their peers and face-altering filters are driving negative feelings of self-worth and promoting objectification of their bodies, researchers found.

he pursuit of online fame, particularly through Instagram, has supercharged the often toxic phenomenon, The Times found, encouraging parents to commodify their children’s images. Some of the child influencers earn six-figure incomes, according to interviews.

Because right-wing commentators aren’t the only ones who think Biden’s mind is basically gone—lots of voters think so too

Since mainstream media venues by and large epistemically rely on the views of the masses to supply journalists with their coverage frames, news operations end up treating popular concerns about Biden’s age as a kind of sacrosanct window into reality rather than as a hype cycle perpetually fed into the ambient collective consciousness by anti-Biden voices intending to sink his reelection chances.

By contrast, most of the news sources the right sees as hyperpartisan Biden spin machines actually strain at being fair-minded and objective, which disinclines them toward producing any sort of muscular pushback against the right’s relentless mischaracterizations.

Of course, a major reason why the public thinks this is because the entirety of the right-wing information superstructure is devoted, on a daily basis, to depicting Biden as severely cognitively compromised

even if we grant every single concern that Klein and others have voiced, it is indisputably true that Joe Biden remains an intellectual giant next to Donald Trump

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.”

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.)

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.”

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.”

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.

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

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?”

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.

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.”

These come, as far as I can tell, in two broad types, corresponding to the two fundamental complaints that people voice about their undergraduate experience

The first complaint is that college did not prepare them for the real world: that the whole exercise—papers, busywork, pointless requirements; siloed disciplines and abstract theory—seemed remote from anything that they actually might want to do with their lives. 

Above all, they are student-centered. Participants are enabled (and expected) to direct their education by constructing bespoke curricula out of the resources the program gives them access to. In a word, these endeavors emphasize “engagement.”

A student will identify a problem (a human need, an injustice, an instance of underrepresentation), then devise and implement a response (a physical system, a community-facing program, an art project). 

Professors were often preoccupied, with little patience for mentorship, the open-ended office-hours exploration. Classes, even in fields like philosophy, felt lifeless, impersonal, like engineering but with words instead of numbers. Worst of all were their fellow undergraduates, those climbers and careerists. “It’s hard to build your soul,” as one of my students once put it to me, “when everyone around you is trying to sell theirs.”

Not everything in the world is a problem, and to see the world as a series of problems is to limit the potential of both world and self. What problem does a song address? What problem will reading Voltaire help you solve, in any predictable way? The “problem” approach—the “engagement” approach, the save-the-world approach—leaves out, finally, what I’d call learning.

that is the second complaint that graduates tend to express: that they finished college without the feeling that they had learned anything, in this essential sense.

That there is a treasure out there—call it the Great Books or just great books, the wisdom of the ages or the best that has been thought and said—that its purpose is to activate the treasure inside them, that they had come to one of these splendid institutions (whose architecture speaks of culture, whose age gives earnest of depth) to be initiated into it, but that they had been denied, deprived. For unclear reasons, cheated.

I had students like this at Columbia and Yale. There were never a lot of them, and to judge from what’s been happening to humanities enrollments, there are fewer and fewer. (From 2013 to 2022, the number of people graduating with bachelors degrees in English fell by 36%. As a share of all degrees, it fell by 42%, to less than 1 in 60.)

They would tell me—these pilgrims, these intellectuals in embryo, these kindled souls—how hard they were finding it to get the kind of education they had come to college for.

what bothers me about this educational approach—the “problem” approach, the “STEAM” (STEM + arts) approach—is what it leaves out. It leaves out the humanities. It leaves out books. It leaves out literature and philosophy, history and art history and the history of religion. It leaves out any mode of inquiry—reflection, speculation, conversation with the past—that cannot be turned to immediate practical ends

The Catherine Project sees itself as being in the business of creating “communities of learning”; its principles include “conversation and hospitality, “simplicity [and] transparency.” Classes (called tutorials, in keeping with the practice at St. John’s) are free (BISR’s cost $335), are capped at four to six students (at BISR, the limit is 23), run for two hours a week for twelve weeks, and skew towards the canon: the Greeks and Romans, Pascal and Kierkegaard, Dante and Cervantes (the project also hosts a large number of reading groups, which address a wider range of texts). If BISR aspires to create a fairer market for academic labor—instructors keep the lion’s share of fees—the Catherine Project functions as a gift economy (though plans are to begin to offer tutors modest honoraria).

As Russell Jacoby has noted, the migration of intellectuals into universities in the decades after World War II, which he documented in The Last Intellectuals, has more recently reversed itself. The rise, or re-rise, of little magazines (Dissent, Commentary, Partisan Review then; n+1, The New Inquiry, The Point, The Drift, et al. now) is part of the same story. 

a fourth factor. If there are students who despair at the condition of the humanities on campus, there are professors who do so as well. Many of her teachers, Hitz told me, have regular ladder appointments: “We draw academics—who attend our groups as well as leading them—because the life of the mind is dying or dead in conventional institutions.” Undergraduate teaching, she added, “is a particularly hard pull,” and the Catherine Project offers faculty the chance to teach people “who actually want to learn.

I’d add, who can. Nine years ago, Stephen Greenblatt wrote: “Even the highly gifted students in my Shakespeare classes at Harvard are less likely to be touched by the subtle magic of his words than I was so many years ago or than my students were in the 1980s in Berkeley. … The problem is that their engagement with language … often seems surprisingly shallow or tepid.” By now, of course, the picture is far worse.

The response to the announcement of our pilot programs confirmed for me the existence of a large, unmet desire for text-based exploration, touching on the deepest questions, outside the confines of higher education

Applicants ranged from graduating college seniors to people in their 70s. They included teachers, artists, scientists, and doctoral students from across the disciplines; a submarine officer, a rabbinical student, an accountant, and a venture capitalist; retirees, parents of small children, and twentysomethings at the crossroads. Forms came in from India, Jordan, Brazil, and nine other foreign countries. The applicants were, as a group, tremendously impressive. If it had been possible, we would have taken many more than fifteen.

When asked why they wanted to participate, a number of them spoke about the pathologies of formal education. “We have a really damaged relationship to learning,” said one. “It should be fun, not scary”—as in, you feel that you’re supposed to know the answer, which as a student, as she noted, makes no sense

“We need opportunities for reading and exploration that lie outside the credentialing system of the modern university,” he went on, because there’s so much in the latter that cuts against “the slow way that kind of learning unfolds.”

“How one might choose to live.” For many of our applicants—and this, of course, is what the program is about, what the humanities are about—learning has, or ought to have, an existential weight.

I detected a desire to be free of forces and agendas: the university’s agenda of “relevance,” the professoriate’s agenda of political mobilization, the market’s agenda of productivity, the internet’s agenda of surveillance and addiction. In short, the whole capitalistic algorithmic ideological hairball of coerced homogeneity

The desire is to not be recruited, to not be instrumentalized, to remain (or become) an individual, to resist regression toward the mean, or meme.

That is why it’s crucial that the Matthew Strother Center has no goal—and this is true of the Catherine Project and other off-campus humanities programs, as well—beyond the pursuit of learning for its own sake.

This is freedom. When education isn’t pointed in particular directions, its possibilities are endless

During our leisure time, not counting work, each of us processes 34 gigabytes, or 100,000 words, every day

The world’s 21,274 television stations produce 85,000 hours of original programming every day as we watch an average of five hours of television daily, the equivalent of 20 gigabytes of audio-video images

That’s not counting YouTube, which uploads 6,000 hours of video every hour.

We’ve created a world with 300 exabytes (300,000,000,000,000,000,000 pieces) of human-made information. If each of those pieces of information were written on a 3-by-5-inch index card and then spread out side by side, just one person’s share—your share of this information—would cover every square inch of Massachusetts and Connecticut combined.

Neurons are living cells with a metabolism; they need oxygen and glucose to survive, and when they’ve been working hard, we experience fatigue. Every status update you read on Facebook, every tweet or text message you get from a friend, is competing for resources in your brain with important things like whether to put your savings in stocks or bonds,

The processing capacity of the conscious mind has been estimated (by the researcher Mihaly Csikszentmihalyi and, independently, by Bell Labs engineer Robert Lucky) at 120 bits per second. That bandwidth, or window, is the speed limit for the traffic of information we can pay conscious attention to at any one time.

While a great deal occurs below the threshold of our awareness, and this has an impact on how we feel and what our life is going to be like, in order for something to become encoded as part of your experience, you need to have paid conscious attention to it.

What does this bandwidth restriction—this information speed limit—mean in terms of our interactions with others? In order to understand one person speaking to us, we need to process 60 bits of information per second. With a processing limit of 120 bits per second, this means you can barely understand two people talking to you at the same time

We’re surrounded on this planet by billions of other humans, but we can understand only two at a time at the most! It’s no wonder that the world is filled with so much misunderstanding.

With such attentional restrictions, it’s clear why many of us feel overwhelmed by managing some of the most basic aspects of life. Part of the reason is that our brains evolved to help us deal with life during the hunter-gatherer phase of human history

Attention is the most essential mental resource for any organism. It determines which aspects of the environment we deal with, and most of the time, various automatic, subconscious processes make the correct choice about what gets passed through to our conscious awareness. For this to happen, millions of neurons are constantly monitoring the environment to select the most important things for us to focus on.

These neurons are collectively the “attentional filter.” They work largely in the background, outside of our conscious awareness. This is why most of the perceptual detritus of our daily lives doesn’t registe

The attentional filter is one of evolution’s greatest achievements. In nonhumans, it ensures that they don’t get distracted by irrelevant things

When our protohuman ancestors left the cover of the trees to seek new sources of food, they simultaneously opened up a vast range of new possibilities for nourishment and exposed themselves to a wide range of new predators. Being alert and vigilant to threatening sounds and visual cues is what allowed them to survive; this meant allowing an increasing amount of information through the attentional filter.

Ten thousand years ago, humans plus their pets and livestock accounted for about 0.1% of the terrestrial vertebrate biomass inhabiting the earth; we now account for 98%

Humans are, by most biological measures, the most successful species our planet has seen. We have managed to survive in nearly every climate our planet has offered (so far), and the rate of our population expansion exceeds that of any other known organism

Our success owes in large part to our cognitive capacity, the ability of our brains to flexibly handle information. But our brains evolved in a much simpler world with far less information coming at us. Today, our attentional filters easily become overwhelmed.

Successful people—or those who can afford it—employ layers of other people whose job it is to narrow their own attentional filters.

One of the key themes in "Wise Animals" is the idea that technology is far from neutral. Chatfield argues that the way innovation has progressed was not the only possible path and that we must keep an open mind about the possibilities