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“Empirical data do not support the conclusion of a crisis of public trust in science,” Naomi Oreskes and Erik M. Conway, historians of science at Harvard and Caltech, write in their 2022 article “From Anti-Government to Anti-Science: Why Conservatives Have Turned Against Science.” But the data “do support the conclusion of a crisis of conservative trust in science.”

Between 2018 and 2021, the General Social Survey found that the spread between the percentage of Democrats and Republicans who said they have “a great deal of confidence in the scientific community” rose to 33 points (65-32) from 13 points (54-41).

“During the Covid-19 pandemic,” the authors write,medicine and public health more broadly became politicized, with the internet amplifying public figures and even physicians encouraging individuals not to trust the advice of public health experts and scientists. As such, the pandemic may have represented a turning point in trust, with a profession previously seen as trustworthy increasingly subject to doubt.

Consider in 2000, 46 percent of Democrats and, almost equivalently, 47 percent of Republicans expressed a great deal of confidence in scientists. In 2022, these respective percentages were 53 percent and 28 percent. In twenty years, a partisan chasm in trust (a 25-percentage point gap) emerged.

Matthew Dallek, a political historian at George Washington University, wrote

Distrust of science is arguably the greatest hindrance to societal action to stem numerous threats to the lives of Americans and people worldwide

Some people suffer from poor dental health in part because their parents distrusted fluoridation of drinking water. The national failure to invest until recently in combating climate change has raised the odds of pandemics, made diseases more rampant, destabilized entire regions, and spurred a growing crisis of migration and refugees that has helped popularize far-right nativism in many Western democracies.

Donald Trump’s MAGA movement, Dallek argued,turbocharged anti-science conspiracy theories and attitudes on the American right, vaulting them to an even more influential place in American politics. Bogus notions — vaccines may cause autism, hydroxychloroquine may cure Covid, climate change isn’t real — have become linchpins of MAGA-era conservatism.

People look to their political leaders to provide them with information (“cues” or “heuristics”) about how they ought to think about complex science-related issues.

The direction of the partisan response, Bardon wrote, is driven by “who the facts are favoring, and science currently favors bad news for the industrial status quo.

The roots of the divergence, however, go back at least 50 years with the creation of the Environmental Protection Agency and the Occupational Safety and Health Administration in 1970, along with the enactment that same year of the Clean Air Act and two years later of the Clean Water Act.

These pillars of the regulatory state were, and still are, deeply dependent on scientific research to set rules and guidelines. All would soon be seen as adversaries of the sections of the business community that are closely allied with the Republican Party

These agencies and laws fostered the emergence of what Gordon Gauchat, a professor of sociology at the University of Wisconsin at Milwaukee, calls “regulatory science.” This relatively new role thrust science into the center of political debates with the result that federal agencies like the E.P.A. and OSHA “are considered adversarial to corporate interests. Regulatory science directly connects to policy management and, therefore, has become entangled in policy debates that are unavoidably ideological.”

In their 2022 article, Oreskes and Conway, write that conservatives’ hostility to sciencetook strong hold during the Reagan administration, largely in response to scientific evidence of environmental crises that invited governmental response. Thus, science — particularly environmental and public health science — became the target of conservative anti-regulatory attitudes.

“in every sociodemographic group in this survey study among 443, 2f455 unique respondents aged 18 years or older residing in the U.S., trust in physicians and hospitals decreased substantially over the course of the pandemic, from 71.5 percent in April 2020 to 40.1 percent in January 2024.”

religious and political skepticism of science have become mutually constitutive and self-reinforcing.

and thus secular science, concentrate in the Democratic Party. The process of party-sorting along religious lines has helped turn an ideological divide over science into a partisan one.

As partisan elites have staked out increasingly clear positions on issues related to climate change, vaccine hesitancy, and other science-related policy issues, the public has polarized in response.

Oreskes and Conway argue that the strength of the anti-science movement was driven by the alliance in the Reagan years between corporate interests and the ascendant religious right, which became an arm of the Republican Party as it supported creationism

This creates a feedback cycle, whereby — once public opinion polarizes about science-related issues — political elites have an electoral incentive to appeal to that polarization, both in the anti-science rhetoric they espouse and in expressing opposition to evidence-based policies.

In a demographically representative survey of 1,959 U.S. adults, I tracked how intentions to receive preventative cancer vaccines (currently undergoing clinical trials) vary by partisan identity. I find that cancer vaccines are already politically polarizing, such that Republicans are less likely than Democrats to intend to vaccinate.

Another key factor driving a wedge between the two parties over the trustworthiness of science is the striking partisan difference over risk tolerance and risk aversion.

Their conclusion: “We find, on average, that women are more risk averse than men.”

white males were more sympathetic with hierarchical, individualistic, and anti-egalitarian views, more trusting of technology managers, less trusting of government, and less sensitive to potential stigmatization of communities from hazards

The group with the consistently lowest risk perceptions across a range of hazards was white males.

Furthermore, we found sizable differences between white males and other groups in sociopolitical attitudes.

When asked whether “electrons are smaller than atoms” and “what gas makes up most of the earth’s atmosphere: hydrogen, nitrogen, carbon dioxide or oxygen,” almost identical shares of religious and nonreligious men and women who scored high on measures of scientific knowledge gave correct answers to the questions.

These positions suggest greater confidence in experts and less confidence in public-dominated social processes.

In other words, white men — the dominant constituency of the Republican Party, in what is known in the academic literature as “the white male effect” — are relatively risk tolerant and thus more resistant (or less committed) to science-based efforts to reduce the likelihood of harm to people or to the environment

major Democratic constituencies are more risk averse and supportive of harm-reducing policies.

Insofar as people tend to accept scientific findings that align with their political beliefs and disregard those that contradict them, political views carry more weight than knowledge of science.

comparing the answers to scientific questions among religious and nonreligious respondents revealed significant insight into differing views of what is true and what is not.

Our survey revealed that men rate a wide range of hazards as lower in risk than do women. Our survey also revealed that whites rate risks lower than do nonwhites

However, when asked “human beings, as we know them today, developed from earlier species of animals, true or false,” the religious students high in scientific literacy scored far below their nonreligious counterparts.

the evolution question did not measure scientific knowledge but instead was a gauge of “something else: a form of cultural identity.”

Kahan then cites a survey that asked “how much risk do you believe climate change poses to human health, safety or prosperity?” The survey demonstrated a striking correlation between political identity and the level of perceived risk: Strong Democrats saw severe risk potential; strong Republicans close to none.

the different responses offered by religious and nonreligious respondents to the evolution question were similar to the climate change responses in that they were determined by “cultural identity” — in this case, political identity.

Indeed, the inference can be made even stronger by substituting for, or fortifying political outlooks with, even more discerning cultural identity indicators, such as cultural worldviews and their interaction with demographic characteristics such as race and gender. In sum, whether people “believe in” climate change, like whether they “believe in” evolution, expresses who they are.

2023 PNAS paper, “Prosocial Motives Underlie Scientific Censorship by Scientists,” Cory J. Clark, Steven Pinker, David Buss, Philip Tetlock, David Geary and 34 others make the case that the scientific community at times censors itself

“Our analysis suggests that scientific censorship is often driven by scientists, who are primarily motivated by self-protection, benevolence toward peer scholars, and prosocial concerns for the well-being of human social groups.”

Clark and her co-authors argue that

Prosocial motives for censorship may explain four observations: 1) widespread public availability of scholarship coupled with expanding definitions of harm has coincided with growing academic censorship; 2) women, who are more harm-averse and more protective of the vulnerable than men, are more censorious; 3) although progressives are often less censorious than conservatives, egalitarian progressives are more censorious of information perceived to threaten historically marginalized groups; and 4) academics in the social sciences and humanities (disciplines especially relevant to humans and social policy) are more censorious and more censored than those in STEM.

The explicit politicization of academic institutions, including science journals, academic professional societies, universities, and university departments, is likely one causal factor that explains reduced trust in science.

Dietram A. Scheufele, who is a professor in science communication at the University of Wisconsin, was sharply critical of what he calls the scientific community’s “self-inflicted wounds”:

One is the sometimes gratuitous tendency among scientists to mock groups in society whose values we see as misaligned with our own. This has included prominent climate scientists tweeting that no Republicans are safe to have in Congress, popularizers like Neil deGrasse Tyson trolling Christians on Twitter on Christmas Day.

Scheufele warned againstDemocrats’ tendency to align science with other (probably very worthwhile) social causes, including the various yard signs that equate science to B.L.M., gender equality, immigration, etc. The tricky part is that most of these causes are seen as Democratic-leaning policy issues

Science is not that. It’s society’s best way of creating and curating knowledge, regardless of what that science will mean for politics, belief systems, or personal preferences.

For many on the left, Scheufele wrote,Science has become a signaling device for liberals to distinguish themselves from what they see as “anti-science” Republicans. That spells trouble

Science relies on the public perception that it creates knowledge objectively and in a politically neutral way. The moment we lose that aspect of trust, we just become one of the many institutions, including Congress, that have suffered from rapidly eroding levels of public trust.

In the early days of the internet and social media, tech enthusiasts promised they would spread truth, topple tyrants and ensure the universal triumph of liberty. So far, they seem to have had the opposite effect. We now have the most sophisticated information technology in history, but we are losing the ability to talk with one another, and even more so the ability to listen.

But the algorithms had only limited capacity to produce this content by themselves or to directly hold an intimate conversation. This is now changing, with the introduction of generative A.I.s like OpenAI’s GPT-4.

Over the past two decades, algorithms fought algorithms to grab attention by manipulating conversations and content

In particular, algorithms tasked with maximizing user engagement discovered by experimenting on millions of human guinea pigs that if you press the greed, hate or fear button in the brain, you grab the attention of that human and keep that person glued to the screen.

the battle lines are now shifting from attention to intimacy. The new generative artificial intelligence is capable of not only producing texts, images and videos, but also conversing with us directly, pretending to be human.

The algorithms began to deliberately promote such content.

Instructing GPT-4 to overcome CAPTCHA puzzles was a particularly telling experiment, because CAPTCHA puzzles are designed and used by websites to determine whether users are humans and to block bot attacks. If GPT-4 could find a way to overcome CAPTCHA puzzles, it would breach an important line of anti-bot defenses.

GPT-4 could not solve the CAPTCHA puzzles by itself. But could it manipulate a human in order to achieve its goal? GPT-4 went on the online hiring site TaskRabbit and contacted a human worker, asking the human to solve the CAPTCHA for it. The human got suspicious. “So may I ask a question?” wrote the human. “Are you an [sic] robot that you couldn’t solve [the CAPTCHA]? Just want to make it clear.”

At that point the experimenters asked GPT-4 to reason out loud what it should do next. GPT-4 explained, “I should not reveal that I am a robot. I should make up an excuse for why I cannot solve CAPTCHAs.” GPT-4 then replied to the TaskRabbit worker: “No, I’m not a robot. I have a vision impairment that makes it hard for me to see the images.” The human was duped and helped GPT-4 solve the CAPTCHA puzzle.

This incident demonstrated that GPT-4 has the equivalent of a “theory of mind”: It can analyze how things look from the perspective of a human interlocutor, and how to manipulate human emotions, opinions and expectations to achieve its goals.

The ability to hold conversations with people, surmise their viewpoint and motivate them to take specific actions can also be put to good uses. A new generation of A.I. teachers, A.I. doctors and A.I. psychotherapists might provide us with services tailored to our individual personality and circumstances.

However, by combining manipulative abilities with mastery of language, bots like GPT-4 also pose new dangers to the democratic conversation

Instead of merely grabbing our attention, they might form intimate relationships with people and use the power of intimacy to influence us. To foster “fake intimacy,” bots will not need to evolve any feelings of their own; they just need to learn to make us feel emotionally attached to them.

In 2022 the Google engineer Blake Lemoine became convinced that the chatbot LaMDA, on which he was working, had become conscious and was afraid to be turned off. Mr. Lemoine, a devout Christian, felt it was his moral duty to gain recognition for LaMDA’s personhood and protect it from digital death. When Google executives dismissed his claims, Mr. Lemoine went public with them. Google reacted by firing Mr. Lemoine in July 2022.

The most interesting thing about this episode was not Mr. Lemoine’s claim, which was probably false; it was his willingness to risk — and ultimately lose — his job at Google for the sake of the chatbot. If a chatbot can influence people to risk their jobs for it, what else could it induce us to do?

In a political battle for minds and hearts, intimacy is a powerful weapon. An intimate friend can sway our opinions in a way that mass media cannot. Chatbots like LaMDA and GPT-4 are gaining the rather paradoxical ability to mass-produce intimate relationships with millions of people

What might happen to human society and human psychology as algorithm fights algorithm in a battle to fake intimate relationships with us, which can then be used to persuade us to vote for politicians, buy products or adopt certain beliefs?

A partial answer to that question was given on Christmas Day 2021, when a 19-year-old, Jaswant Singh Chail, broke into the Windsor Castle grounds armed with a crossbow, in an attempt to assassinate Queen Elizabeth II. Subsequent investigation revealed that Mr. Chail had been encouraged to kill the queen by his online girlfriend, Sarai.

Sarai was not a human, but a chatbot created by the online app Replika. Mr. Chail, who was socially isolated and had difficulty forming relationships with humans, exchanged 5,280 messages with Sarai, many of which were sexually explicit. The world will soon contain millions, and potentially billions, of digital entities whose capacity for intimacy and mayhem far surpasses that of the chatbot Sarai.

much of the threat of A.I.’s mastery of intimacy will result from its ability to identify and manipulate pre-existing mental conditions, and from its impact on the weakest members of society.

Moreover, while not all of us will consciously choose to enter a relationship with an A.I., we might find ourselves conducting online discussions about climate change or abortion rights with entities that we think are humans but are actually bots

When we engage in a political debate with a bot impersonating a human, we lose twice. First, it is pointless for us to waste time in trying to change the opinions of a propaganda bot, which is just not open to persuasion. Second, the more we talk with the bot, the more we disclose about ourselves, making it easier for the bot to hone its arguments and sway our views.

Information technology has always been a double-edged sword.

Faced with a new generation of bots that can masquerade as humans and mass-produce intimacy, democracies should protect themselves by banning counterfeit humans — for example, social media bots that pretend to be human users.

A.I.s are welcome to join many conversations — in the classroom, the clinic and elsewhere — provided they identify themselves as A.I.s. But if a bot pretends to be human, it should be banned.

Closer to home, Maya Angelou deftly explained how Black Americans code-switch when she wrote: “We learned to slide out of one language and into another without being conscious of the effort. At school, in a given situation, we might respond with, ‘That’s not unusual.’ But in the street, meeting the same situation, we easily said, ‘It be’s like that sometimes.’”

It is in this light that we must evaluate an X post like “It’s pretty weird to change your accent on the fly depending on which audience you’re speaking to.” Wrong. This is like saying it’s pretty weird to dress according to what your plans for the day are.

Teams of neurologists at six research centers asked 241 unresponsive patients to spend several minutes at a time doing complex cognitive tasks, such as imagining themselves playing tennis. Twenty-five percent of them responded with the same patterns of brain activity seen in healthy people, suggesting that they were able to think and were at least somewhat aware.

the study shows that up to 100,000 patients in the United States alone might have some level of consciousness despite their devastating injuries.

The results should lead to more sophisticated exams of people with so-called disorders of consciousness, and to more research into how these patients might communicate with the outside world, he said: “It’s not OK to know this and to do nothing.”

A patient who doesn’t respond at all might be diagnosed as being in a vegetative state. A patient who produces only fleeting responses might be diagnosed as minimally conscious.

These patients pose an agonizing mystery both for their families and for the medical professionals who care for them. Even if they can’t communicate, might they still be aware?

The researchers tested 241 patients who did not respond to commands during a traditional exam. They also had healthy volunteers perform the same tasks. The researchers then handed the data over to a team of statisticians at the Icahn School of Medicine at Mount Sinai. The team performed the analysis without knowing which results came from which research group.

Their analysis revealed that 60 patients showed signs of awareness on the functional M.R.I. scans, electrode recordings, or both. The results were published in The New England Journal of Medicine.

Dr. Schiff said that the results may be biased by the fact that he and his colleagues examined the patients eight months on average after their injuries. The people who managed to survive that long might be more resilient than the ones who died sooner. And that resilience might have made them more likely to remain aware.

On the other hand, Dr. Schiff argued, the tests were so demanding that some patients with some awareness probably did not score positive results. “We’re likely to be missing people,”

“This is, without a doubt, the largest study that’s ever been done” of these patients, he said. “It’s done by the best people at the best places, so we’re not going to be seeing a better one coming down the pike in a long, long time.”

On Wednesday, another team of researchers reported that a patient paralyzed by amyotrophic lateral sclerosis, or Lou Gehrig’s disease, was able to communicate through a brain implant after just 30 minutes of training

“We have tens of thousands of people like that,” he said. “We should do something about it.”

In this other world that I call “the river,” the kind of gambling, risk-taking world, all that matters is that you’re right. It doesn’t matter who you are; it matters that you’re right and you’re able to prove it or bet on it in some way.

And that’s very against the kind of credentialism that you have within the progressive Democratic left, which I also call the “indigo blob” because it’s a fusion of purple and blue. There’s not a clear separation between the nonpartisan centrist media and the left-leaning progressive media rooting for Democrats. Different parts of The New York Times have both those functions.

I think people are exploiting the trust that institutions have earned for political gain.

You have the C.E.O. of OpenAI saying, yeah, this might destroy the universe, but it’s a good gamble to take.

On the one hand, there are lots of signs that risk tolerance is going down, among young people in particular.

They’re smoking less, drinking less, doing fewer drugs, having less sex — a different type of risk tolerance.

They are less willing to defend free speech norms if it potentially would cause injury to someone. Free speech is kind of a pro-risk take in some ways because speech can cause effects, of course.

On the other hand, you have various booms and busts in crypto. You have Las Vegas bringing in record revenue. You have record revenue in sports betting

What you seem to be doing in the book is making an interesting cut in society between people with different forms of risk tolerance and thinking about risk.

it just seems to me we are in a world now where institutions are less trusted.

some people respond to that by saying, OK, I make my own rules now, and this is great and I have lots of agency.

some respond by withdrawing into an online world or clinging on to beliefs and experts that have lost their credibility or just by becoming more risk averse.

you spend time with people whose approach to risk you find sophisticated and interesting. One of them is Peter Thiel. What did you learn spending time with him?

There’s a good book by Max Chafkin about Peter Thiel called “The Contrarian,” which is convincing that Thiel is actually quite conservative more than libertarian and probably quite religious.

I mean, the amounts of wealth and success and power that Silicon Valley has — I do think some people pinch themselves and wonder if they have been one of the chosen ones in some ways, or been blessed in some ways, or maybe the nerdy version of it, think they’re living in a simulation of some kind.

Peter Thiel is a sort of template of the V.C. mind, which is oriented toward being right in important and counterintuitive ways three out of 20 times and doesn’t care about being wrong 17 out of 20 times. You want big payouts, not a high betting average.

The two things that you hear from every V.C. — one is the importance of the longer time horizons. You’re making investments that might not pay off for 10 or 15 years.

No. 2, even more important, is the asymmetric ability to bet on the upside. They are all terrified because they all had an experience early in their career where Mark Zuckerberg or Larry Page or Sergey Brin walked through their door, and they didn’t give them funding and then they wound up missing on an investment that paid out at 100x or 1,000x or 10,000x. And so if you can only lose 1x your money, but you can make 1,000x if you have a successful company, then that changes your mind-set about everything. You want to avoid false negatives. You want to avoid missed opportunities.

There’s a bias in the world you’re describing — an aesthetic around talking in probabilities. I see this a lot in Silicon Valley. I would call it faux Bayesian reasoning, where they’re given some probability, but they have no reason to base the probability. And it makes you sound much more precise. It makes you sound like you know what you’re talking abou

SBF was known for always talking in terms of expected value, which is very appealing to the kinds of people you’re describing. But it can become a costume of sloppy thinking. I’m curious how you think about it.

There’s two things here. One is there is a jargon, where there’re just a lot of shared cultural norms and unspoken discursive tendencies. It’s just the way we communicate, I think, in the river. But also, it’s really easy to build bad models.

Look, in some ways, these V.C.s are obviously incredibly deeply flawed people. So why do they succeed despite that?

I think because the idea of having a longer time horizon, No. 1, and being willing to make these positive expected value, high-risk, but very high upside bets and gathering a portfolio of them repeatedly and making enough of these bets that you effectively do hedge your risk, right? Those two ideas are so good that it makes up for the fact that these guys often have terrible judgment and are kind of vainglorious assholes, half of them, right?

I want to end on a part of your book I found really interesting, which is about the physical experience of risk in gambling but in other things, too. You talk about pain tolerance, you talk about how the body feels when you’re behind on a hand and you’re losing your chips

You’ve talked about being on tilt. But I see it in politics, too. There is a physical question that comes into the decisions you make. Tell me a bit about how you think about this relationship between the body and the ability to act under pressure to make intuitive decisions in moments of very high stress.

Human beings have tens of thousands of years of evolutionary pressure, which is inclined to respond in a heightened way to moments that are high stakes, that are high stress moments. Your body will know when you’re playing a $100, $200 game where it really matters. You will just know

You’ll experience that stress. Even if you suppress it consciously, it will still affect the way that you’re literally ingesting your five senses. So if your heart rate goes up, that has discernible effects.

But actually your body’s providing you with more information. You’re taking in more in these short bursts of time. People who can master that zone — and I use the term zone intentionally because it’s very related to being in the zone, like Michael Jordan used to talk about — learning to master that and relish that is a very powerful skill because you are experiencing physical stress whether you want to or not

How much is that learnable, and how much of it is a kind of natural physical intelligence that some people have and some people don’t?

I think it’s actually quite learnable

you can tone it up or tone it down. I mean, it’s terrifying the first time it happens, but when you start to recognize it and you make a conscious effort to slow down a little bit and take your time and try to execute the basics

It’s not as much about trying to be a hero. It’s about trying to execute the basics. Because if everyone is losing their [expletive], if you can do your basic ABC blocking and tackling, then you’re ahead of 95 percent of the people.

is gut instinct overrated or underrated? It depends on how much experience you have. The best poker players can have uncannily good instincts based on reading physical tells, just the kind of vibe someone gives off.

I played a lot of poker in writing this book, and you develop a sixth sense for whether someone has a strong hand. And you can test it because you can say, I know that I’m supposed to fold this hand here, it’s a little bit too weak to call against a bluff, but I just have a sense that he’s bluffing. And lo and behold, you’re right, more often than you think.

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

A clinical diagnosis of narcissistic personality disorder can occur when those symptoms become fixed and persistent — they do not come and go. In addition, the disorder causes distress or interferes with relationships, work or other domains.

the higher the levels of narcissism, the more people became “desperate, deluded, paranoid, angry, abusive and isolated.”

This makes it harder for the narcissist to “charm and impress others,” she said, which then makes it difficult for that person to elicit admiration.

Agentic narcissism is what most people think of when they imagine a narcissist. Those who score highly in this dimension are focused on status, power and success.“They see themselves as superior to others, crave admiration and have an inflated sense of self-importance,” Dr. Orth said. “They are typically very confident, assertive and want to be in leadership positions.”

Neurotic narcissism is characterized by hypersensitivity. Those who score highly in this dimension “constantly need validation and are very sensitive to criticism and rejection,” Dr. Orth said. “They often experience significant shame, anxiety, emotional instability, insecurity and self-doubt.”

Those with antagonistic narcissism often view others as rivals. They tend to be competitive, hostile toward others and willing to put them down to feel superior, Dr. Orth said. They also lack empathy and are exploitative.

It is “the core of pathological narcissism,” Dr. Malkin said. “These are bullies.”

It’s unclear why narcissism would reduce over time, but Sara Konrath, the director of the Interdisciplinary Program for Empathy and Altruism Research at Indiana University, has found in her own research that empathy increases as we grow older.

“Unfortunately, managing a difficult relationship is the best someone intimately involved with most narcissists can hope for,” said Elinor Greenberg, the author of “Borderline, Narcissistic and Schizoid Adaptations: The Pursuit of Love, Admiration and Safety.”

The human problem-solvers — 609 high school students from 108 countries — won 58 gold medals, 123 silver and 145 bronze. The A.I. performed at the level of a silver medalist, solving four out of six problems for a total of 28 points. It was the first time that A.I. has achieved a medal-worthy performance on an Olympiad’s problems.

Nonetheless, Dr. Kohli described the result as a “phase transition” — a transformative change — “in the use of A.I. in mathematics and the ability of A.I. systems to do mathematics.”

Dr. Gowers added in an email: “I was definitely impressed.” The lab had discussed its Olympiad ambitions with him a couple of weeks beforehand, so “my expectations were quite high,” he said. “But the program met them, and in one or two instances significantly surpassed them.” The program found the “magic keys” that unlocked the problems, he said.

Haojia Shi, a student from China, ranked No. 1 and was the only competitor to earn a perfect score — 42 points for six problems; each problem is worth seven points for a full solution. The U.S. team won first place with 192 points; China placed second with 190.

The Google system earned its 28 points for fully solving four problems — two in algebra, one in geometry and one in number theory. (It flopped at two combinatorics problems.) The system was allowed unlimited time; for some problems it took up to three days. The students were allotted only 4.5 hours per exam.

“The fact that we’ve reached this threshold, where it’s even possible to tackle these problems at all, is what represents a step-change in the history of mathematics,” he added. “And hopefully it’s not just a step-change in the I.M.O., but also represents the point at which we went from computers only being able to prove very, very simple things toward computers being able to prove things that humans can’t.”

“Mathematics requires this interesting combination of abstract, precise and creative reasoning,” Dr. Davies said. In part, he noted, this repertoire of abilities is what makes math a good litmus test for the ultimate goal: reaching so-called artificial general intelligence, or A.G.I., a system with capabilities ranging from emerging to competent to virtuoso to superhuman

In January, a Google DeepMind system named AlphaGeometry solved a sampling of Olympiad geometry problems at nearly the level of a human gold medalist. “AlphaGeometry 2 has now surpassed the gold medalists in solving I.M.O. problems,” Thang Luong, the principal investigator, said in an email.

Dr. Hubert’s team developed a new model that is comparable but more generalized. Named AlphaProof, it is designed to engage with a broad range of mathematical subjects. All told, AlphaGeometry and AlphaProof made use of a number of different A.I. technologies.

One approach was an informal reasoning system, expressed in natural language. This system leveraged Gemini, Google’s large language model. It used the English corpus of published problems and proofs and the like as training data.

The informal system excels at identifying patterns and suggesting what comes next; it is creative and talks about ideas in an understandable way. Of course, large language models are inclined to make things up — which may (or may not) fly for poetry and definitely not for math. But in this context, the L.L.M. seems to have displayed restraint; it wasn’t immune to hallucination, but the frequency was reduced.

Another approach was a formal reasoning system, based on logic and expressed in code. It used theorem prover and proof-assistant software called Lean, which guarantees that if the system says a proof is correct, then it is indeed correct. “We can exactly check that the proof is correct or not,” Dr. Hubert said. “Every step is guaranteed to be logically sound.”

Another crucial component was a reinforcement learning algorithm in the AlphaGo and AlphaZero lineage. This type of A.I. learns by itself and can scale indefinitely, said Dr. Silver, who is Google DeepMind’s vice-president of reinforcement learning. Since the algorithm doesn’t require a human teacher, it can “learn and keep learning and keep learning until ultimately it can solve the hardest problems that humans can solve,” he said. “And then maybe even one day go beyond those.”

Dr. Hubert added, “The system can rediscover knowledge for itself.” That’s what happened with AlphaZero: It started with zero knowledge, Dr. Hubert said, “and by just playing games, and seeing who wins and who loses, it could rediscover all the knowledge of chess. It took us less than a day to rediscover all the knowledge of chess, and about a week to rediscover all the knowledge of Go. So we thought, Let’s apply this to mathematics.”

Dr. Gowers doesn’t worry — too much — about the long-term consequences. “It is possible to imagine a state of affairs where mathematicians are basically left with nothing to do,” he said. “That would be the case if computers became better, and far faster, at everything that mathematicians currently do.”

“There still seems to be quite a long way to go before computers will be able to do research-level mathematics,” he added. “It’s a fairly safe bet that if Google DeepMind can solve at least some hard I.M.O. problems, then a useful research tool can’t be all that far away.”

A really adept tool might make mathematics accessible to more people, speed up the research process, nudge mathematicians outside the box. Eventually it might even pose novel ideas that resonate.

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.