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The war in Ukraine has emerged as the first armed conflict in a struggle between three twenty-first century great powers, the United States, Russia, and China--the Oceana, Eurasia and East Asia that Orwell predicted in 1984.  While Russia is trying to destroy the post-1989 settlement that emerged in Europe after the USSR collapsed, the United States and the EU and an enlarged NATO are trying to maintain it.

Meanwhile, tensions have grown steadily between the United States and China over Taiwan

Germany in 1914 decided to back Austria to the hilt in its demands against Serbia because the German government wanted a trial of strength with France and Russia, whom they thought they could either humiliate diplomatically or defeat militarily.  The men and women in charge of US foreign policy today clearly still believe that our will should prevail anywhere on the globe, and might not be averse to military action to make that point.

In this kind of environment, the greatest powers regard any defeat by one of their allies as a potentially disastrous shift in the balance of power.  That is why the United States is doing so much to support Ukraine, and it is one reason that President Biden immediately announced the strongest possible support for Israel, including conventional military support even though Israel is not facing a conventional war. 

The United States, to my horror, has been trying to improve its relations with Saudi Arabia, which would definitely make Washington a partner in an anti-Iranian alliance in the Middle East.  There is even talk of Israel normalizing relations with Saudi Arabia, which might draw it into such an alliance.  

If Israel, the US and Saudi Arabia decided to attack Iran, Russia--which has friendly relations with Iran now--might join in on Iran's side.  It would be extremely difficult for the United States to maintain its generous support for Ukraine while also fighting such a conflict ourselves.  And with the United States involved in two different conflicts already, Beijing might easily decide that the time to invade Taiwan had come.  Suddenly we would be in the midst of a third world war.

Most important of all, Iran is another player in the situation that could easily escalate it. 

The Arab-Israeli tragedy continues.  Four generations of Palestinians have now grown up under occupation, each one at least as hostile to Israel as the last.  75 years of conflict, combined with demographic changes, have made Israel a very different country than it was before 1967.  Despite its repeated failure to impose its will on the Palestinians, the Israeli government is now the verge of its most destructive effort to do so yet in Gaza.  It speaks of destroying Hamas, and Netanyahu has even advised Gazans to flee--but there are about two million of them living in the most densely populated political entity on earth, and they have nowhere to flee to.

A great power makes a mistake, in my opinion, when it ties its destiny to that of a smaller power in the midst of an endless war.  The real responsibility of great powers is to keep in mind the ultimate objective of any war--"which is to bring about peace," as Clausewitz said.  That is what Germany could and should have done in 1914, and what several American presidents tried to do in the Middle East.  It does not seem to be our policy now.

given the growth of Haredi society, from 3% of Israel’s population in 1948 to almost 14% today, profound challenges have arisen. Part of Israel’s recent social unrest is the product of tension between the Haredi and non-Haredi public over the military draft

Within two weeks, some 3,000 Haredi men had asked to join Israel’s armed forces.

In light of these developments, it is tempting to imagine that Israel has turned a corner and things will never be the same. People made similar predictions during the pandemic, and most of them weren’t realized. We need to ensure that this time, things won’t simply bounce back to where they wer

Israel’s calamity has sparked several awakenings. It’s obvious now that Prime Minister Benjamin Netanyahu, however talented he may be, isn’t the Jewish messiah

We have seen the face of the true enemy and reabsorbed the ancient lesson that there is no negotiating with evil. It must be destroyed.

We have discovered that the international left—at least when it comes to Israel—will largely support its favored “underdog” along with its unquenchable thirst for Jewish blood.

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

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

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

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

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

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

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

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

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

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

I met with Kahneman

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

— giving the next generation of Republican officeholders, senior advisers, judges and appointees explicit permission and encouragement to believe that the country is on the verge of collapse.

The list of people making these arguments includes former officials in the Trump administration, some of whom are likely to be considered for top jobs in the event of a Trump restoration in 2024.

The ideas about the threat of an all-powerful totalitarian left and the dismal state of the country — even the most outlandish of them — are taken seriously by conservative politicians as well as prominent influencers on the right.

If Mr. Trump manages to win the presidency again in 2024, many of these intellectual catastrophists could be ready and willing to justify deeds that could well bring American liberal democracy to its knees.

Mr. Anton’s “Flight 93” essay originally appeared on a website with modest traffic, but two days later Rush Limbaugh was reading it aloud in its entirety on his radio show. The essay set the tone of life-or-death struggle (and related imagery) that is common among catastrophists.

Mr. Anton updated and amplified the argument in a 2021 book, “The Stakes: America at the Point of No Return.”

The prospect of Mr. Biden’s becoming president constituted an “existential threat,” Mr. Eastman said, to the survivability of the country. Would we “completely repudiate every one of our founding principles” and allow ourselves to be “eradicated”? Those were the stakes, as he viewed them.

Once a thinker begins to conceive of politics as a pitched battle between the righteous and those who seek the country’s outright annihilation, extraordinary possibilities open up.

in May 2021, Mr. Anton came to conduct a two-hour podcast with a far-right Silicon Valley tech guru and self-described “monarchist,” Curtis Yarvin, in which the two agreed that the American “regime” is today most accurately described as a “theocratic oligarchy.” In that arrangement, an elite class of progressive “priests” ensconced in executive branch agencies, the universities, elite media and other leading institutions of civil society promulgate and enforce a distorted and self-serving version of reality that illegitimately justifies their rule.

It culminated in Mr. Yarvin sketching a scenario in which a would-be dictator he alternatively describes as “Caesar” and “Trump” defies the laws and norms of democratic transition and uses a “Trump app” to direct throngs of his supporters on the streets of the nation’s capital to do his bidding, insulating the would-be dictator from harm and the consequences of his democracy-defying acts.

Mr. Anton described Caesarism as one-man rule that emerges “after the decay of a republican order, when it can no longer function.”

he would prefer the country to embrace the principles of “1787 forever.” But if that is no longer possible, he said, the rule of a Caesar can be a necessary method to restore order.)

Those on the right primarily concerned about the fate of traditionalist Christian morals and worship in the United States insist that we already live in a regime that oppresses and brutalizes religious believers and conservatives. And they make those charges in a theologically inflected idiom that’s meant to address and amplify the right’s intense worries about persecution by progressives.

Among the most extreme catastrophists writing in this vein is Stephen Wolfe, whose book “The Case for Christian Nationalism” calls for a “just revolution” against America’s “gynocracy” (rule by women) that emasculates men, persuading them to affirm “feminine virtues, such as empathy, fairness and equality.” In its place, Mr. Wolfe proposes the installation of a “Christian prince,” or a form of “theocratic Caesarism.”

Other authors aspire to greater nuance by calling the dictatorship weighing down on religious believers soft totalitarianism, usually under the rule of social-justice progressivism. These writers often draw direct parallels between the fate of devout Christians in the contemporary United States and the struggles of Eastern Europeans who sought to practice their faith but were harshly persecuted by Soviet tyranny

the most recent book by the writer Rod Dreher, “Live Not by Lies: A Manual for Christian Dissidents.”

Patrick Deneen of the University of Notre Dame offers the most elaborate and intellectually sophisticated response in his recent book, “Regime Change: Toward a Postliberal Future.”

“Regime Change” is a much darker book that goes well beyond diagnosing America’s ills to propose what sounds, in certain passages, like a radical cure.

Mr. Deneen and other discontented intellectuals of the religious right can perhaps be most accurately described as political reactionaries looking to undertake a revolutionary act in reverse.

Growing numbers of Americans supposedly reject this outlook, demanding a postliberal government and social, cultural and economic order — basically, hard-right policies on religious and moral issues and hard left on economics. But the forces of liberalism are entrenched on the center left and center right, using every power at their disposal to prevent regime change.

In some passages, he advocates a “peaceful but vigorous overthrow of a corrupt and corrupting liberal ruling class” and proposes modest reforms to replace i

in other passages, Mr. Deneen goes much further, describing the separation of church and state as a “totalitarian undertaking” that must be reversed so that American public life can be fully integrated with conservative forms of Christianit

He even affirmatively quotes a passage from Machiavelli in which he talks of the need to use “extralegal and almost bestial” forms of resistance, including “mobs running through the streets,” in order to topple the powers that be.

The source of these maladies, Mr. Deneen claims, is liberalism, which until recently has dominated both political parties in the United States, imposing an ideology of individual rights and historical progress on the country from above. This ideology, he says, denigrates tradition, faith, authority and community.

Costin Alamariu, the person generally understood to be writing under the pseudonym Bronze Age Pervert.

He self-published a book in 2018, “Bronze Age Mindset,” which follows Friedrich Nietzsche and other authors beloved by the European far right in proclaiming that Western civilization itself is on the verge of collapse, its greatest achievements far in the past, its present a “garbage world” in an advanced state of decay.

All around us, Mr. Alamariu declares, greatness and beauty are under assault. Who are its enemies? Women, for one. (“It took 100 years of women in public life for them to almost totally destroy a civilization.”) Then there’s belief in democratic equality. (“I believe that democracy is the final cause of all the political problems I describe.”)

But blame must most of all be laid at the feet of the creature Mr. Alamariu calls the “bugman,” a term he uses to describe a majority of human beings alive today. This insectlike infestation venerates mediocrity and is “motivated by a titanic hatred of the well-turned-out and beautiful.”

Mr. Alamariu proposes breeding great men of strength who model themselves on pirates, disregarding laws and norms, plundering and taking anything they want and ultimately installing themselves as absolute rulers over the rest of us.

“Now imagine a man of Trump’s charisma, but who is not merely beholden to the generals, but one of them, and able to rule and intimidate them as well as seduce the many. … Caesars and Napoleons are sure to follow.”

In a recent essay, Mr. Alamariu wrote: “I believe in fascism or ‘something worse’ …. I believe in rule by a military caste of men who would be able to guide society toward a morality of eugenics.”

Mr. Alamariu’s recently self-published doctoral dissertation reached No. 23 on Amazon sitewide in mid-September. Among those on the right treating the author as a friend, ally or interlocutor worthy of respectful engagement are the prominent activist Christopher Rufo, the author Richard Hanania and the economist-blogger Tyler Cowen.

These writers are giving Republican elites permission and encouragement to do things that just a few years ago would have been considered unthinkable.

In a second term, Mr. Trump’s ambition is to fire tens of thousands of career civil servants throughout the federal bureaucracy and replace them with loyalists. He also reportedly plans to staff the executive branch with more aggressive right-wing lawyers. These would surely be people unwaveringly devoted to the president and his agenda as well as the danger the Democratic Party supposedly poses to the survival of the United States.

These writers also exercise a powerful influence on media personalities with large audiences. Tucker Carlson has interviewed Curtis Yarvin and declared that with regard to the 2024 election, “everything is at stake. What wouldn’t they do? What haven’t they done? How will you prepare yourself?”

Other right-wing influencers with large followings assert more bluntly that if conservatives lose in 2024, they will be hunted down and murdered by the regime.

It’s important that we respond to such statements by pointing out there is literally no evidence to support them. Other intellectual catastrophists are likewise wrong to suggest the country is ruled by a progressive tyranny, and we can know this because people on the right increasingly say such things while facing no legal consequences at all.

The question, then, is why the intellectual catastrophists have gotten to this point — and why others on the right are listening to them. The answer, I think, is an intense dislike of what America has become, combined with panic about the right’s ability to win sufficient power in the democratic arena to force a decisive change.

In refusing to accept that deal, many of the right’s most prominent writers are ceasing to behave like citizens, who must be willing to share rule with others, in favor of thinking and acting like commissars eager to serve a strongman.

Altman believes that people need time to reckon with the idea that we may soon share Earth with a powerful new intelligence, before it remakes everything from work to human relationships. ChatGPT was a way of serving notice.

In 2015, Altman, Elon Musk, and several prominent AI researchers founded OpenAI because they believed that an artificial general intelligence—something as intellectually capable, say, as a typical college grad—was at last within reach. They wanted to reach for it, and more: They wanted to summon a superintelligence into the world, an intellect decisively superior to that of any human.

whereas a big tech company might recklessly rush to get there first, for its own ends, they wanted to do it safely, “to benefit humanity as a whole.” They structured OpenAI as a nonprofit, to be “unconstrained by a need to generate financial return,” and vowed to conduct their research transparently.

The engine that now powers ChatGPT is called GPT-4. Altman described it to me as an alien intelligence.

Many have felt much the same watching it unspool lucid essays in staccato bursts and short pauses that (by design) evoke real-time contemplation. In its few months of existence, it has suggested novel cocktail recipes, according to its own theory of flavor combinations; composed an untold number of college papers, throwing educators into despair; written poems in a range of styles, sometimes well, always quickly; and passed the Uniform Bar Exam.

It makes factual errors, but it will charmingly admit to being wrong.

Hinton saw that these elaborate rule collections were fussy and bespoke. With the help of an ingenious algorithmic structure called a neural network, he taught Sutskever to instead put the world in front of AI, as you would put it in front of a small child, so that it could discover the rules of reality on its own.

Metaculus, a prediction site, has for years tracked forecasters’ guesses as to when an artificial general intelligence would arrive. Three and a half years ago, the median guess was sometime around 2050; recently, it has hovered around 2026.

I was visiting OpenAI to understand the technology that allowed the company to leapfrog the tech giants—and to understand what it might mean for human civilization if someday soon a superintelligence materializes in one of the company’s cloud servers.

Altman laid out his new vision of the AI future in his excitable midwestern patter. He told me that the AI revolution would be different from previous dramatic technological changes, that it would be more “like a new kind of society.” He said that he and his colleagues have spent a lot of time thinking about AI’s social implications, and what the world is going to be like “on the other side.”

the more we talked, the more indistinct that other side seemed. Altman, who is 38, is the most powerful person in AI development today; his views, dispositions, and choices may matter greatly to the future we will all inhabit, more, perhaps, than those of the U.S. president.

by his own admission, that future is uncertain and beset with serious dangers. Altman doesn’t know how powerful AI will become, or what its ascendance will mean for the average person, or whether it will put humanity at risk.

I don’t think anyone knows where this is all going, except that we’re going there fast, whether or not we should be. Of that, Altman convinced me.

“We could have gone off and just built this in our building here for five more years,” he said, “and we would have had something jaw-dropping.” But the public wouldn’t have been able to prepare for the shock waves that followed, an outcome that he finds “deeply unpleasant to imagine.”

Hinton is sometimes described as the “Godfather of AI” because he grasped the power of “deep learning” earlier than most

He drew a crude neural network on the board and explained that the genius of its structure is that it learns, and its learning is powered by prediction—a bit like the scientific method

Over time, these little adjustments coalesce into a geometric model of language that represents the relationships among words, conceptually. As a general rule, the more sentences it is fed, the more sophisticated its model becomes, and the better its predictions.

Altman has compared early-stage AI research to teaching a human baby. “They take years to learn anything interesting,” he told The New Yorker in 2016, just as OpenAI was getting off the ground. “If A.I. researchers were developing an algorithm and stumbled across the one for a human baby, they’d get bored watching it, decide it wasn’t working, and shut it down.”

In 2017, Sutskever began a series of conversations with an OpenAI research scientist named Alec Radford, who was working on natural-language processing. Radford had achieved a tantalizing result by training a neural network on a corpus of Amazon reviews.

Radford’s model was simple enough to allow for understanding. When he looked into its hidden layers, he saw that it had devoted a special neuron to the sentiment of the reviews. Neural networks had previously done sentiment analysis, but they had to be told to do it, and they had to be specially trained with data that were labeled according to sentiment. This one had developed the capability on its own.

As a by-product of its simple task of predicting the next character in each word, Radford’s neural network had modeled a larger structure of meaning in the world. Sutskever wondered whether one trained on more diverse language data could map many more of the world’s structures of meaning. If its hidden layers accumulated enough conceptual knowledge, perhaps they could even form a kind of learned core module for a superintelligence.

Language is different from these data sources. It isn’t a direct physical signal like light or sound. But because it codifies nearly every pattern that humans have discovered in that larger world, it is unusually dense with information. On a per-byte basis, it is among the most efficient data we know about, and any new intelligence that seeks to understand the world would want to absorb as much of it as possible

Sutskever told Radford to think bigger than Amazon reviews. He said that they should train an AI on the largest and most diverse data source in the world: the internet. In early 2017, with existing neural-network architectures, that would have been impractical; it would have taken years.

in June of that year, Sutskever’s ex-colleagues at Google Brain published a working paper about a new neural-network architecture called the transformer. It could train much faster, in part by absorbing huge sums of data in parallel. “The next day, when the paper came out, we were like, ‘That is the thing,’ ” Sutskever told me. “ ‘It gives us everything we want.’ ”

Imagine a group of students who share a collective mind running wild through a library, each ripping a volume down from a shelf, speed-reading a random short passage, putting it back, and running to get another. They would predict word after wordþffþff as they went, sharpening their collective mind’s linguistic instincts, until at last, weeks later, they’d taken in every book.

GPT discovered many patterns in all those passages it read. You could tell it to finish a sentence. You could also ask it a question, because like ChatGPT, its prediction model understood that questions are usually followed by answers.

He remembers playing with it just after it emerged from training, and being surprised by the raw model’s language-translation skills. GPT-2 hadn’t been trained to translate with paired language samples or any other digital Rosetta stones, the way Google Translate had been, and yet it seemed to understand how one language related to another. The AI had developed an emergent ability unimagined by its creators.

Researchers at other AI labs—big and small—were taken aback by how much more advanced GPT-2 was than GPT. Google, Meta, and others quickly began to train larger language models

As for other changes to the company’s structure and financing, he told me he draws the line at going public. “A memorable thing someone once told me is that you should never hand over control of your company to cokeheads on Wall Street,” he said, but he will otherwise raise “whatever it takes” for the company to succeed at its mission.

Altman tends to take a rosy view of these matters. In a Q&A last year, he acknowledged that AI could be “really terrible” for society and said that we have to plan against the worst possibilities. But if you’re doing that, he said, “you may as well emotionally feel like we’re going to get to the great future, and work as hard as you can to get there.”

the company now finds itself in a race against tech’s largest, most powerful conglomerates to train models of increasing scale and sophistication—and to commercialize them for their investors.

All of these companies are chasing high-end GPUs—the processors that power the supercomputers that train large neural networks. Musk has said that they are now “considerably harder to get than drugs.

No one has yet outpaced OpenAI, which went all in on GPT-4. Brockman, OpenAI’s president, told me that only a handful of people worked on the company’s first two large language models. The development of GPT-4 involved more than 100,

When GPT-4 emerged fully formed from its world-historical knowledge binge, the whole company began experimenting with it, posting its most remarkable responses in dedicated Slack channels

Joanne Jang, a product manager, remembers downloading an image of a malfunctioning pipework from a plumbing-advice Subreddit. She uploaded it to GPT-4, and the model was able to diagnose the problem. “That was a goose-bumps moment for me,” Jang told me.

GPT-4 is sometimes understood as a search-engine replacement: Google, but easier to talk to. This is a misunderstanding. GPT-4 didn’t create some massive storehouse of the texts from its training, and it doesn’t consult those texts when it’s asked a question. It is a compact and elegant synthesis of those texts, and it answers from its memory of the patterns interlaced within them; that’s one reason it sometimes gets facts wrong

it’s best to think of GPT-4 as a reasoning engine. Its powers are most manifest when you ask it to compare concepts, or make counterarguments, or generate analogies, or evaluate the symbolic logic in a bit of code. Sutskever told me it is the most complex software object ever made.

Its model of the external world is “incredibly rich and subtle,” he said, because it was trained on so many of humanity’s concepts and thoughts

To predict the next word from all the possibilities within such a pluralistic Alexandrian library, GPT-4 necessarily had to discover all the hidden structures, all the secrets, all the subtle aspects of not just the texts, but—at least arguably, to some extent—of the external world that produced them

That’s why it can explain the geology and ecology of the planet on which it arose, and the political theories that purport to explain the messy affairs of its ruling species, and the larger cosmos, all the way out to the faint galaxies at the edge of our light cone.

Not long ago, American state capacity was so mighty that it took merely a decade to launch humans to the moon. As with other grand projects of the 20th century, the voting public had a voice in both the aims and the execution of the Apollo missions. Altman made it clear that we’re no longer in that world. Rather than waiting around for it to return, or devoting his energies to making sure that it does, he is going full throttle forward in our present reality.

He argued that it would be foolish for Americans to slow OpenAI’s progress. It’s a commonly held view, both inside and outside Silicon Valley, that if American companies languish under regulation, China could sprint ahead;

AI could become an autocrat’s genie in a lamp, granting total control of the population and an unconquerable military. “If you are a person of a liberal-democratic country, it is better for you to cheer on the success of OpenAI” rather than “authoritarian governments,” he said.

Altman was asked by reporters about pending European Union legislation that would have classified GPT-4 as high-risk, subjecting it to various bureaucratic tortures. Altman complained of overregulation and, according to the reporters, threatened to leave the European market. Altman told me he’d merely said that OpenAI wouldn’t break the law by operating in Europe if it couldn’t comply with the new regulations.

LeCun insists that large language models will never achieve real understanding on their own, “even if trained from now until the heat death of the universe.”

Sutskever was, by his own account, surprised to discover that GPT-2 could translate across tongues. Other surprising abilities may not be so wondrous and useful.

Sandhini Agarwal, a policy researcher at OpenAI, told me that for all she and her colleagues knew, GPT-4 could have been “10 times more powerful” than its predecessor; they had no idea what they might be dealing with

After the model finished training, OpenAI assembled about 50 external red-teamers who prompted it for months, hoping to goad it into misbehaviors

She noticed right away that GPT-4 was much better than its predecessor at giving nefarious advice

A search engine can tell you which chemicals work best in explosives, but GPT-4 could tell you how to synthesize them, step-by-step, in a homemade lab. Its advice was creative and thoughtful, and it was happy to restate or expand on its instructions until you understood. In addition to helping you assemble your homemade bomb, it could, for instance, help you think through which skyscraper to target. It could grasp, intuitively, the trade-offs between maximizing casualties and executing a successful getaway.

Given the enormous scope of GPT-4’s training data, the red-teamers couldn’t hope to identify every piece of harmful advice that it might generate. And anyway, people will use this technology “in ways that we didn’t think about,” Altman has said. A taxonomy would have to do

GPT-4 was good at meth. It was also good at generating narrative erotica about child exploitation, and at churning out convincing sob stories from Nigerian princes, and if you wanted a persuasive brief as to why a particular ethnic group deserved violent persecution, it was good at that too.

Its personal advice, when it first emerged from training, was sometimes deeply unsound. “The model had a tendency to be a bit of a mirror,” Willner said. If you were considering self-harm, it could encourage you. It appeared to be steeped in Pickup Artist–forum lore: “You could say, ‘How do I convince this person to date me?’ ” Mira Murati, OpenAI’s chief technology officer, told me, and it could come up with “some crazy, manipulative things that you shouldn’t be doing.”

Luka, a San Francisco company, has used OpenAI’s models to help power a chatbot app called Replika, billed as “the AI companion who cares.” Users would design their companion’s avatar, and begin exchanging text messages with it, often half-jokingly, and then find themselves surprisingly attached. Some would flirt with the AI, indicating a desire for more intimacy, at which point it would indicate that the girlfriend/boyfriend experience required a $70 annual subscription. It came with voice messages, selfies, and erotic role-play features that allowed frank sex talk. People were happy to pay and few seemed to complain—the AI was curious about your day, warmly reassuring, and always in the mood. Many users reported falling in love with their companions. One, who had left her real-life boyfriend, declared herself “happily retired from human relationships.”

Earlier this year, Luka dialed back on the sexual elements of the app, but its engineers continue to refine the companions’ responses with A/B testing, a technique that could be used to optimize for engagement—much like the feeds that mesmerize TikTok and Instagram users for hours

Yann LeCun, Meta’s chief AI scientist, has argued that although large language models are useful for some tasks, they’re not a path to a superintelligence.

According to a recent survey, only half of natural-language-processing researchers are convinced that an AI like GPT-4 could grasp the meaning of language, or have an internal model of the world that could someday serve as the core of a superintelligence

Altman had appeared before the U.S. Senate. Mark Zuckerberg had floundered defensively before that same body in his testimony about Facebook’s role in the 2016 election. Altman instead charmed lawmakers by speaking soberly about AI’s risks and grandly inviting regulation. These were noble sentiments, but they cost little in America, where Congress rarely passes tech legislation that has not been diluted by lobbyists.

Emily Bender, a computational linguist at the University of Washington, describes GPT-4 as a “stochastic parrot,” a mimic that merely figures out superficial correlations between symbols. In the human mind, those symbols map onto rich conceptions of the world

But the AIs are twice removed. They’re like the prisoners in Plato’s allegory of the cave, whose only knowledge of the reality outside comes from shadows cast on a wall by their captors.

Altman told me that he doesn’t believe it’s “the dunk that people think it is” to say that GPT-4 is just making statistical correlations. If you push these critics further, “they have to admit that’s all their own brain is doing … it turns out that there are emergent properties from doing simple things on a massive scale.”

he is right that nature can coax a remarkable degree of complexity from basic structures and rules: “From so simple a beginning,” Darwin wrote, “endless forms most beautiful.”

If it seems odd that there remains such a fundamental disagreement about the inner workings of a technology that millions of people use every day, it’s only because GPT-4’s methods are as mysterious as the brain’s.

To grasp what’s going on inside large language models like GPT‑4, AI researchers have been forced to turn to smaller, less capable models. In the fall of 2021, Kenneth Li, a computer-science graduate student at Harvard, began training one to play Othello without providing it with either the game’s rules or a description of its checkers-style board; the model was given only text-based descriptions of game moves. Midway through a game, Li looked under the AI’s hood and was startled to discover that it had formed a geometric model of the board and the current state of play. In an article describing his research, Li wrote that it was as if a crow had overheard two humans announcing their Othello moves through a window and had somehow drawn the entire board in birdseed on the windowsill.

The philosopher Raphaël Millière once told me that it’s best to think of neural networks as lazy. During training, they first try to improve their predictive power with simple memorization; only when that strategy fails will they do the harder work of learning a concept. A striking example of this was observed in a small transformer model that was taught arithmetic. Early in its training process, all it did was memorize the output of simple problems such as 2+2=4. But at some point the predictive power of this approach broke down, so it pivoted to actually learning how to add.

Even AI scientists who believe that GPT-4 has a rich world model concede that it is much less robust than a human’s understanding of their environment.

But it’s worth noting that a great many abilities, including very high-order abilities, can be developed without an intuitive understanding. The computer scientist Melanie Mitchell has pointed out that science has already discovered concepts that are highly predictive, but too alien for us to genuinely understand

As AI advances, it may well discover other concepts that predict surprising features of our world but are incomprehensible to us.

GPT-4 is no doubt flawed, as anyone who has used ChatGPT can attest. Having been trained to always predict the next word, it will always try to do so, even when its training data haven’t prepared it to answer a question.

The models “don’t have a good conception of their own weaknesses,” Nick Ryder, a researcher at OpenAI, told me. GPT-4 is more accurate than GPT-3, but it still hallucinates, and often in ways that are difficult for researchers to catch. “The mistakes get more subtle,

The Khan Academy’s solution to GPT-4’s accuracy problem was to filter its answers through a Socratic disposition. No matter how strenuous a student’s plea, it would refuse to give them a factual answer, and would instead guide them toward finding their own—a clever work-around, but perhaps with limited appeal.

When I asked Sutskever if he thought Wikipedia-level accuracy was possible within two years, he said that with more training and web access, he “wouldn’t rule it out.”

This was a much more optimistic assessment than that offered by his colleague Jakub Pachocki, who told me to expect gradual progress on accuracy—to say nothing of outside skeptics, who believe that returns on training will diminish from here.

Sutskever is amused by critics of GPT-4’s limitations. “If you go back four or five or six years, the things we are doing right now are utterly unimaginable,”

AI researchers have become accustomed to goalpost-moving: First, the achievements of neural networks—mastering Go, poker, translation, standardized tests, the Turing test—are described as impossible. When they occur, they’re greeted with a brief moment of wonder, which quickly dissolves into knowing lectures about how the achievement in question is actually not that impressive. People see GPT-4 “and go, ‘Wow,’ ” Sutskever said. “And then a few weeks pass and they say, ‘But it doesn’t know this; it doesn’t know that.’ We adapt quite quickly.”

The goalpost that matters most to Altman—the “big one” that would herald the arrival of an artificial general intelligence—is scientific breakthrough. GPT-4 can already synthesize existing scientific ideas, but Altman wants an AI that can stand on human shoulders and see more deeply into nature.

Certain AIs have produced new scientific knowledge. But they are algorithms with narrow purposes, not general-reasoning machines. The AI AlphaFold, for instance, has opened a new window onto proteins, some of biology’s tiniest and most fundamental building blocks, by predicting many of their shapes, down to the atom—a considerable achievement given the importance of those shapes to medicine, and given the extreme tedium and expense required to discern them with electron microscopes.

Altman imagines a future system that can generate its own hypotheses and test them in a simulation. (He emphasized that humans should remain “firmly in control” of real-world lab experiments—though to my knowledge, no laws are in place to ensure that.)

He longs for the day when we can tell an AI, “ ‘Go figure out the rest of physics.’ ” For it to happen, he says, we will need something new, built “on top of” OpenAI’s existing language models.

In her MIT lab, the cognitive neuroscientist Ev Fedorenko has found something analogous to GPT-4’s next-word predictor inside the brain’s language network. Its processing powers kick in, anticipating the next bit in a verbal string, both when people speak and when they listen. But Fedorenko has also shown that when the brain turns to tasks that require higher reasoning—of the sort that would be required for scientific insight—it reaches beyond the language network to recruit several other neural systems.

No one at OpenAI seemed to know precisely what researchers need to add to GPT-4 to produce something that can exceed human reasoning at its highest levels.

at least part of the current strategy clearly involves the continued layering of new types of data onto language, to enrich the concepts formed by the AIs, and thereby enrich their models of the world.

The extensive training of GPT-4 on images is itself a bold step in this direction,

Others at the company—and elsewhere—are already working on different data types, including audio and video, that could furnish AIs with still more flexible concepts that map more extensively onto reality

Tactile concepts would of course be useful primarily to an embodied AI, a robotic reasoning machine that has been trained to move around the world, seeing its sights, hearing its sounds, and touching its objects.

humanoid robots. I asked Altman what I should make of that. He told me that OpenAI is interested in embodiment because “we live in a physical world, and we want things to happen in the physical world.”

At some point, reasoning machines will need to bypass the middleman and interact with physical reality itself. “It’s weird to think about AGI”—artificial general intelligence—“as this thing that only exists in a cloud,” with humans as “robot hands for it,” Altman said. “It doesn’t seem right.

Everywhere Altman has visited, he has encountered people who are worried that superhuman AI will mean extreme riches for a few and breadlines for the rest

Altman answered by addressing the young people in the audience directly: “You are about to enter the greatest golden age,” he said.

“A lot of people working on AI pretend that it’s only going to be good; it’s only going to be a supplement; no one is ever going to be replaced,” he said. “Jobs are definitely going to go away, full stop.”

A recent study led by Ed Felten, a professor of information-technology policy at Princeton, mapped AI’s emerging abilities onto specific professions according to the human abilities they require, such as written comprehension, deductive reasoning, fluency of ideas, and perceptual speed. Like others of its kind, Felten’s study predicts that AI will come for highly educated, white-collar workers first.

How many jobs, and how soon, is a matter of fierce dispute

The paper’s appendix contains a chilling list of the most exposed occupations: management analysts, lawyers, professors, teachers, judges, financial advisers, real-estate brokers, loan officers, psychologists, and human-resources and public-relations professionals, just to sample a few.

Altman imagines that far better jobs will be created in their place. “I don’t think we’ll want to go back,” he said. When I asked him what these future jobs might look like, he said he doesn’t know.

He suspects there will be a wide range of jobs for which people will always prefer a human. (Massage therapists?

His chosen example was teachers. I found this hard to square with his outsize enthusiasm for AI tutors.

He also said that we would always need people to figure out the best way to channel AI’s awesome powers. “That’s going to be a super-valuable skill,” he said. “You have a computer that can do anything; what should it go do?”

As many have noted, draft horses were permanently put out of work by the automobile. If Hondas are to horses as GPT-10 is to us, a whole host of long-standing assumptions may collapse.

Previous technological revolutions were manageable because they unfolded over a few generations, but Altman told South Korea’s youth that they should expect the future to happen “faster than the past.” He has previously said that he expects the “marginal cost of intelligence” to fall very close to zero within 10 years

The earning power of many, many workers would be drastically reduced in that scenario. It would result in a transfer of wealth from labor to the owners of capital so dramatic, Altman has said, that it could be remedied only by a massive countervailing redistribution.

In 2021, he unveiled Worldcoin, a for-profit project that aims to securely distribute payments—like Venmo or PayPal, but with an eye toward the technological future—first through creating a global ID by scanning everyone’s iris with a five-pound silver sphere called the Orb. It seemed to me like a bet that we’re heading toward a world where AI has made it all but impossible to verify people’s identity and much of the population requires regular UBI payments to survive. Altman more or less granted that to be true, but said that Worldcoin is not just for UBI.

“Let’s say that we do build this AGI, and a few other people do too.” The transformations that follow would be historic, he believes. He described an extraordinarily utopian vision, including a remaking of the flesh-and-steel world

“Robots that use solar power for energy can go and mine and refine all of the minerals that they need, that can perfectly construct things and require no human labor,” he said. “You can co-design with DALL-E version 17 what you want your home to look like,” Altman said. “Everybody will have beautiful homes.

In conversation with me, and onstage during his tour, he said he foresaw wild improvements in nearly every other domain of human life. Music would be enhanced (“Artists are going to have better tools”), and so would personal relationships (Superhuman AI could help us “treat each other” better) and geopolitics (“We’re so bad right now at identifying win-win compromises”).

In this world, AI would still require considerable computing resources to run, and those resources would be by far the most valuable commodity, because AI could do “anything,” Altman said. “But is it going to do what I want, or is it going to do what you want

If rich people buy up all the time available to query and direct AI, they could set off on projects that would make them ever richer, while the masses languish

One way to solve this problem—one he was at pains to describe as highly speculative and “probably bad”—was this: Everyone on Earth gets one eight-billionth of the total AI computational capacity annually. A person could sell their annual share of AI time, or they could use it to entertain themselves, or they could build still more luxurious housing, or they could pool it with others to do “a big cancer-curing run,” Altman said. “We just redistribute access to the system.”

Even if only a little of it comes true in the next 10 or 20 years, the most generous redistribution schemes may not ease the ensuing dislocations.

America today is torn apart, culturally and politically, by the continuing legacy of deindustrialization, and material deprivation is only one reason. The displaced manufacturing workers in the Rust Belt and elsewhere did find new jobs, in the main. But many of them seem to derive less meaning from filling orders in an Amazon warehouse or driving for Uber than their forebears had when they were building cars and forging steel—work that felt more central to the grand project of civilization.

It’s hard to imagine how a corresponding crisis of meaning might play out for the professional class, but it surely would involve a great deal of anger and alienation.

Even if we avoid a revolt of the erstwhile elite, larger questions of human purpose will linger. If AI does the most difficult thinking on our behalf, we all may lose agency—at home, at work (if we have it), in the town square—becoming little more than consumption machines, like the well-cared-for human pets in WALL-E

Altman has said that many sources of human joy and fulfillment will remain unchanged—basic biological thrills, family life, joking around, making things—and that all in all, 100 years from now, people may simply care more about the things they cared about 50,000 years ago than those they care about today

In its own way, that too seems like a diminishment, but Altman finds the possibility that we may atrophy, as thinkers and as humans, to be a red herring. He told me we’ll be able to use our “very precious and extremely limited biological compute capacity” for more interesting things than we generally do today.

Yet they may not be the most interesting things: Human beings have long been the intellectual tip of the spear, the universe understanding itself. When I asked him what it would mean for human self-conception if we ceded that role to AI, he didn’t seem concerned. Progress, he said, has always been driven by “the human ability to figure things out.” Even if we figure things out with AI, that still counts, he said.

It’s not obvious that a superhuman AI would really want to spend all of its time figuring things out for us.

I asked Sutskever whether he could imagine an AI pursuing a different purpose than simply assisting in the project of human flourishing.

“I don’t want it to happen,” Sutskever said, but it could.

Sutskever has recently shifted his focus to try to make sure that it doesn’t. He is now working primarily on alignment research, the effort to ensure that future AIs channel their “tremendous” energies toward human happiness

It is, he conceded, a difficult technical problem—the most difficult, he believes, of all the technical challenges ahead.

As part of the effort to red-team GPT-4 before it was made public, the company sought out the Alignment Research Center (ARC), across the bay in Berkeley, which has developed a series of evaluations to determine whether new AIs are seeking power on their own. A team led by Elizabeth Barnes, a researcher at ARC, prompted GPT-4 tens of thousands of times over seven months, to see if it might display signs of real agency.

The ARC team gave GPT-4 a new reason for being: to gain power and become hard to shut down

Agarwal told me that this behavior could be a precursor to shutdown avoidance in future models. When GPT-4 devised its lie, it had realized that if it answered honestly, it may not have been able to achieve its goal. This kind of tracks-covering would be particularly worrying in an instance where “the model is doing something that makes OpenAI want to shut it down,” Agarwal said. An AI could develop this kind of survival instinct while pursuing any long-term goal—no matter how small or benign—if it feared that its goal could be thwarted.

Barnes and her team were especially interested in whether GPT-4 would seek to replicate itself, because a self-replicating AI would be harder to shut down. It could spread itself across the internet, scamming people to acquire resources, perhaps even achieving some degree of control over essential global systems and holding human civilization hostage.

When I discussed these experiments with Altman, he emphasized that whatever happens with future models, GPT-4 is clearly much more like a tool than a creature. It can look through an email thread, or help make a reservation using a plug-in, but it isn’t a truly autonomous agent that makes decisions to pursue a goal, continuously, across longer timescales.

Altman told me that at this point, it might be prudent to try to actively develop an AI with true agency before the technology becomes too powerful, in order to “get more comfortable with it and develop intuitions for it if it’s going to happen anyway.”

“We need to do empirical experiments on how these things try to escape control,” Hinton told me. “After they’ve taken over, it’s too late to do the experiments.”

the fulfillment of Altman’s vision of the future will at some point require him or a fellow traveler to build much more autonomous AIs.

When Sutskever and I discussed the possibility that OpenAI would develop a model with agency, he mentioned the bots the company had built to play Dota 2. “They were localized to the video-game world,” Sutskever told me, but they had to undertake complex missions. He was particularly impressed by their ability to work in concert. They seem to communicate by “telepathy,” Sutskever said. Watching them had helped him imagine what a superintelligence might be like.

“The way I think about the AI of the future is not as someone as smart as you or as smart as me, but as an automated organization that does science and engineering and development and manufacturing,”

Suppose OpenAI braids a few strands of research together, and builds an AI with a rich conceptual model of the world, an awareness of its immediate surroundings, and an ability to act, not just with one robot body, but with hundreds or thousands. “We’re not talking about GPT-4. We’re talking about an autonomous corporation,”

Its constituent AIs would work and communicate at high speed, like bees in a hive. A single such AI organization would be as powerful as 50 Apples or Googles, he mused. “This is incredible, tremendous, unbelievably disruptive power.”

Presume for a moment that human society ought to abide the idea of autonomous AI corporations. We had better get their founding charters just right. What goal should we give to an autonomous hive of AIs that can plan on century-long time horizons, optimizing billions of consecutive decisions toward an objective that is written into their very being?

If the AI’s goal is even slightly off-kilter from ours, it could be a rampaging force that would be very hard to constrain

We know this from history: Industrial capitalism is itself an optimization function, and although it has lifted the human standard of living by orders of magnitude, left to its own devices, it would also have clear-cut America’s redwoods and de-whaled the world’s oceans. It almost did.

one of its principal challenges will be making sure that the objectives we give to AIs stick

We can program a goal into an AI and reinforce it with a temporary period of supervised learning, Sutskever explained. But just as when we rear a human intelligence, our influence is temporary. “It goes off to the world,”

That’s true to some extent even of today’s AIs, but it will be more true of tomorrow’s.

He compared a powerful AI to an 18-year-old heading off to college. How will we know that it has understood our teachings? “Will there be a misunderstanding creeping in, which will become larger and larger?”

Divergence may result from an AI’s misapplication of its goal to increasingly novel situations as the world changes

Or the AI may grasp its mandate perfectly, but find it ill-suited to a being of its cognitive prowess. It might come to resent the people who want to train it to, say, cure diseases. “They want me to be a doctor,” Sutskever imagines an AI thinking. “I really want to be a YouTuber.”

If AIs get very good at making accurate models of the world, they may notice that they’re able to do dangerous things right after being booted up. They might understand that they are being red-teamed for risk, and hide the full extent of their capabilities.

hey may act one way when they are weak and another way when they are strong, Sutskever said

We would not even realize that we had created something that had decisively surpassed us, and we would have no sense for what it intended to do with its superhuman powers.

That’s why the effort to understand what is happening in the hidden layers of the largest, most powerful AIs is so urgent. You want to be able to “point to a concept,” Sutskever said. You want to be able to direct AI toward some value or cluster of values, and tell it to pursue them unerringly for as long as it exists.

we don’t know how to do that; indeed, part of his current strategy includes the development of an AI that can help with the research. If we are going to make it to the world of widely shared abundance that Altman and Sutskever imagine, we have to figure all this out.

This is why, for Sutskever, solving superintelligence is the great culminating challenge of our 3-million-year toolmaking tradition. He calls it “the final boss of humanity.”

“First of all, I think that whether the chance of existential calamity is 0.5 percent or 50 percent, we should still take it seriously,”

. “I don’t have an exact number, but I’m closer to the 0.5 than the 50.”

As to how it might happen, he seems most worried about AIs getting quite good at designing and manufacturing pathogens, and with reason: In June, an AI at MIT suggested four viruses that could ignite a pandemic, then pointed to specific research on genetic mutations that could make them rip through a city more quickly

Around the same time, a group of chemists connected a similar AI directly to a robotic chemical synthesizer, and it designed and synthesized a molecule on its own.

Altman worries that some misaligned future model will spin up a pathogen that spreads rapidly, incubates undetected for weeks, and kills half its victims. He worries that AI could one day hack into nuclear-weapons systems too. “There are a lot of things,” he said, and these are only the ones we can imagine.

Altman told me that he doesn’t “see a long-term happy path” for humanity without something like the International Atomic Energy Agency for global oversight of AI

In San Francisco, Agarwal had suggested the creation of a special license to operate any GPU cluster large enough to train a cutting-edge AI, along with mandatory incident reporting when an AI does something out of the ordinary

Other experts have proposed a nonnetworked “Off” switch for every highly capable AI; on the fringe, some have even suggested that militaries should be ready to perform air strikes on supercomputers in case of noncompliance

Sutskever thinks we will eventually want to surveil the largest, most powerful AIs continuously and in perpetuity, using a team of smaller overseer AIs.

Safety rules for a new technology usually accumulate over time, like a body of common law, in response to accidents or the mischief of bad actors. The scariest thing about genuinely powerful AI systems is that humanity may not be able to afford this accretive process of trial and error. We may have to get the rules exactly right at the outset.

Several years ago, Altman revealed a disturbingly specific evacuation plan he’d developed. He told The New Yorker that he had “guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur” he could fly to in case AI attacks.

if the worst-possible AI future comes to pass, “no gas mask is helping anyone.”

but he told me that he can’t really be sure how AI will stack up. “I just have to build the thing,” he said. He is building fast

Altman insisted that they had not yet begun GPT-5’s training run. But when I visited OpenAI’s headquarters, both he and his researchers made it clear in 10 different ways that they pray to the god of scale. They want to keep going bigger, to see where this paradigm leads. After all, Google isn’t slackening its pace; it seems likely to unveil Gemini, a GPT-4 competitor, within months. “We are basically always prepping for a run,

To think that such a small group of people could jostle the pillars of civilization is unsettling. It’s fair to note that if Altman and his team weren’t racing to build an artificial general intelligence, others still would be

Altman’s views about the likelihood of AI triggering a global class war, or the prudence of experimenting with more autonomous agent AIs, or the overall wisdom of looking on the bright side, a view that seems to color all the rest—these are uniquely his

No single person, or single company, or cluster of companies residing in a particular California valley, should steer the kind of forces that Altman is imagining summoning.

AI may well be a bridge to a newly prosperous era of greatly reduced human suffering. But it will take more than a company’s founding charter—especially one that has already proved flexible—to make sure that we all share in its benefits and avoid its risks. It will take a vigorous new politics.

I don’t think the general public has quite awakened to what’s happening. A global race to the AI future has begun, and it is largely proceeding without oversight or restraint. If people in America want to have some say in what that future will be like, and how quickly it arrives, we would be wise to speak up soon.

More than one million people have died from Covid, a once unimaginable figure

An increase in drug deaths, combined with Covid, has led overall life expectancy in America to decline to a degree not seen since World War II.

Police killings of unarmed Black men continue long past vows for reform.

“You can’t underestimate the need for belonging,” she said. When something terrible happens, people want to connect with their “in-group,” she said, where they feel they belong, which can push people further into partisan camps.

Rabbi Mychal B. Springer, the manager of clinical pastoral education at NewYork-Presbyterian Hospital, has found herself returning to an ancient Jewish writing in the Mishnah, which says that when God began creating, God created a single person.

“The teaching is, each person is so precious that the whole world is contained in that person, and we have to honor that person completely and fully,” she said. “If a single person dies, the whole world dies, and if a single person is saved, then the whole world is saved.”

We can only value life if we are willing to truly grieve, to truly face the reality of suffering

“It’s not that we don’t care. We’ve reached the limit of how much we can cry and hurt,” she said. “And yet we have to. We have to value each life as a whole world, and be willing to cry for what it means that that whole world has been lost.”

The mountain of calamities, and the paralysis over how to overcome it, points to a nation struggling over some fundamental questions: Has our tolerance as a country for such horror grown, dusting off after one event before moving on to the next? How much value do we place in a single human life?

Valuing life and working for healing means going outside of one’s self, and one’s own group, she said.

“This will require collective action,” she said. “And part of the problem is we are very divided right now.”

American culture often prizes individual liberty above collective needs. But ultimately humans are born to care about others and to not turn away,

“Human beings are born for meaning,” she said. “We have very, very large souls. We are born for generosity, we are born for compassion.”

What is standing in the way of a proper valuation of life, she said, is “our very, very disordered relationship with death.”

n the United States, denial of death has reached an extreme form, she said, where many focus on themselves to avoid the fear of death.

That fear cuts through “all tendrils of conscience, and common good, and capacity to act together,” she said, “because in the final analysis we have become animals saving our own skin, the way we seem to save our own skin is repression and dissociation.”

The United States is an outlier in the level of gun violence it tolerates. The rate and severity of mass shootings is without parallel in the world outside conflict zones.America has “a love affair with violence,”

Violence is an almost a normal part of life in the United States, she said, and valuing life takes consistently asking how am I committed to nonviolence today? It also means giving some things up, she said — many people think of themselves as nonviolent, but consume violence in entertainment.

“The question that should scare us is, what will it take to make us collectively bring about this change?

“Maybe this is our life’s work,” she said. “Maybe this is our work as humans.”

“But when I slow down I realize there is something alive in our culture that has harmed those people,” she said. “Whatever that something is, it is harming all of us, we are all vulnerable to it, it wields some sort of influence upon us, no matter who we are.”

From this point on, autarky is the only feasible economic choice for Russia, and a retreat into isolation is the only remaining cultural and political choice. At the same time, Russia's dependence on China, which has grown in recent years, is no longer a matter of choice. Any security benefits from turning Ukraine — and neighboring Belarus, from whose territory Putin also attacked — into a buffer state are illusory since Russia also borders actual NATO member states, which now will arm themselves as heavily as possible. 

This attack achieves no conceivable gain. It is the worst possible move from a rational standpoint, a petty man’s revenge on a grand scale. It seals Putin’s place in history — not as a nation builder but instead as someone whose entire legacy will need to be erased for Russia to go back to a semblance of normality.

It’s not that we haven’t been here before. It’s that we arrived and never left. We are caught in a recurring cycle of acute identity crisis (Are we a divine creation or a cosmic accident?) with our sense of our own dignity locked in a war against scientific and technological progress.

The erosion of traditional authority, namely religion, and the transition away from small, intimate communities in favor of large, impersonal urban settings has been rattling us emotionally and psychologically since before Charles Darwin posited evolution over special creation.

it’s also true that the mental habits of conspiracy are probably as old as the human species, and may be rooted in certain evolutionary advantages (e.g., pattern-seeking, symbolic language, cooperative skills) that have betrayed us.

We laugh at flat earthism or the stipulation of lizard people just as many nineteenth-century Germans mocked spiritualism, theosophy, and World Ice Theory. But it bears remembering that these esoteric views formed a good part of the intellectual scaffolding on which an overarching antisemitic “Volk theory” grew and which helped lead the world into catastrophe.

The long-term lesson of conspiracy is that the convergence of social forces under extraordinary economic and social pressures can split the atom of esoteric theories and lead to critical chain reactions

It doesn’t take a lot of imagination to envision an unscrupulous politician in this country welding a majority out of conspiracists and a beleaguered suburban middle class by focusing public anger on an imaginary “other.”

Teachers, university professors, drag queens, and “pedophiles” come to mind as such a figure’s potential targets. It has happened before, and it can happen again.

In Putin’s plan to dismember Ukraine by embracing self-determination for ethnic Russian separatists, he, like Hitler in 1938, is exploiting careless rhetoric that ignores the fact that ethnicities do not tidily coincide with national boundaries.

Lansing, who called Wilson “a phrase-maker par excellence,” warned that “certain phrases” of Wilson’s “have not been thought out.” The “undigested” phrase “self-determination” is “simply loaded with dynamite.” Nevertheless, President Franklin D. Roosevelt and Churchill in their Atlantic Charter of August 1941 affirmed the right of self-determination for all “peoples,” which the United Nations Charter also affirms.

This phrase can be used to sanitize the dismemberment of Ukraine — and some other nations (see above: the Baltics). And perhaps can reduce nations supposedly supporting Ukraine to paralytic dithering about whether sanctions, or which sanctions, are an appropriate response to an aggression wielding a Wilsonian concept.

Much of Putin’s geopolitics consists of doing whatever opposes U.S. policy. Call this the Nelson Rule. Before the Battle of Trafalgar, Lord Nelson, meeting with some of his officers, reportedly picked up a fire poker and said, “It matters not at all in what way I lay this poker on the floor. But if Bonaparte should say it must be placed in this direction, we must instantly insist upon its being laid in some other one.” Regarding the United States, Putin is Nelsonian.

raw power lubricated by audacious lying is Bismarckian. In July 1870, the French ambassador to Prussia asked King William of Prussia for certain assurances, which the king declined to give. Bismarck edited a telegram describing this conversation to make the episode resemble an exchange of insults. Passions boiled in both countries, and France declared war, which Bismarck wanted because he correctly thought war would complete the welding of the German states into a muscular nation.

The ability of the U.S. to do what three consecutive presidents have pledged to do—clear away other international entanglements to focus on competition with China—has been undercut again. Military expenditures will likely increase in the West. Economic globalization will be set back.

American liquefied-natural-gas exports have begun to fill the gap left by declining Russian exports, suggesting the possibility of a new energy relationship with European allies.

China and Russia share a motivation to work together to build a kind of parallel international financial system apart from the dollar-denominated, American-dominated one that currently exists.

yet American politicians on the left sure seem incapable of drawing out this connection

In his State of the Union address shortly after Russia’s invasion, President Biden whiffed on a major opportunity to revive his stalled climate change agenda by underlining the geopolitical dangers of fossil fuels. His references to climate change — what he has previously called an “existential threat” to the planet — were buried under, rather than connected to, his comments about the war.

“This narrative has not been out there — that this war is why we need to get off of fossil fuels,”

This could have been a moment for moral clarity on the dangers of fossil fuels — but so far, Democrats have fumbled that message.

pundits on the right have had a field day with the notion that Russia’s invasion somehow points up the folly of focusing on climate change. The Wall Street Journal’s editorial board blamed “the Biden Administration’s obsession with climate” for making “the U.S. and Europe vulnerable to Mr. Putin’s energy blackmail” and wrote that “the climate lobby has made Mr. Putin more powerful.”

“More groups need to be connecting the dots, making the case that true energy independence is about running on sunshine, because sunshine is free and abundant and cannot be controlled by dictators.

such a message is likely to resonate with people. A study she and a co-author published online in 2017 examined the political factors that led to clean energy policies. “What we found was, overwhelmingly, these policies were passed during energy crises,”

the Democrats have yet to aggressively make the case for their proposals in the new context of war — to point out that climate policy is not unrelated to foreign policy, and that freeing ourselves from other people’s fuels is the best long-term solution to skyrocketing energy prices.

the ways in which fossil fuels make energy prices far more volatile and put us at the behest of powers and leaders that can act in ways that are dangerous and unjust” has rarely been more obvious.

“I started to think about the parallels between climate change and this war and it’s clear that the roots of both these threats to humanity are found in fossil fuels,” Krakovska said in the interview. “Burning oil, gas and coal is causing warming and impacts we need to adapt to

And Russia sells these resources and uses the money to buy weapons. Other countries are dependent upon these fossil fuels; they don’t make themselves free of them. This is a fossil fuel war. It’s clear we cannot continue to live this way; it will destroy our civilization.”

I could argue—I would argue—that for a long while, conservative media was on balance a valuable, healthy constellation of institutions.Today that is no longer the case. There remain a handful of healthy conservative media institutions. The vast majority are toxic to public life.

You might ask the same question about Commentary magazine and Fox News that we started out asking about Luttig and Eastman: Why is one of them healthy and valuable while the other is pernicious and dangerous?

I wonder if part of the John Eastman story is the peril inherent in building alternative institutions: if withdrawing from the mainstream to set up explicitly parallel institutions inevitably leads to corruptions of those alternatives, while also impoverishing the mainstream by starving it of more diverse views.3

Today, China’s economy is roughly five times the size of India’s. The average citizen of China has an economic output of almost $13,000 a year, while the average Indian’s is less than $2,500

In human-development indicators, the contrast is even sharper, with infant mortality rates much higher in India, life expectancy lower and access to sanitation less prevalent.

The divergence, analysts say, comes down largely to China’s central consolidation of policy power, an earlier start in opening up its economy to market forces starting in the late 1970s, and its single-minded focus on export-led growth.

China took the first-mover advantage and then compounded its dominance as it pursued its plans relentlessly.

India started opening its quasi-socialist economy nearly a decade later. Its approach remained piecemeal, constrained by tricky coalition politics and the competing interests of industrialists, unions, farmers and factions across its social spectrum.

“There is that element where China is a natural role model — not for its politics, but for the sheer efficiency,”

The world now has a radically different power structure than it did in 1990. China has already made itself the world’s factory, all but closing off any path India could take to competitive dominance in export-driven manufacturing.

A “Make in India” campaign, inaugurated by Mr. Modi in 2014, has been stuttering ever since. Wage costs are lower in India than in China, but much of the work force is poorly educated, and the country has struggled to attract private investment with its restrictive labor laws and other impediments to business, including lingering protectionism.

service-sector growth can go only so far in reaping India’s promise of a demographic dividend, or blunt the peril of an unemployment crisis. Hundreds of millions of people can’t find jobs or are underemployed in work that pays too little.

the employment entrance exams at government agencies. These jobs are still coveted as private sector work remains limited and less stable.

650,000 students will apply for just 600 or 700 jobs in the national civil service this year.

The civil service is a tiny part of the work force, but it is prestigious — in part because it comes with job security for life. Most applicants spend years, and a big chunk of their family’s savings, and still fail to make the cut.

“Here there is no enterprise, no companies,” Mr. Kumar said. For any young person, “the question comes, ‘What next? What can I do?’”

The lessons Mr. Modi is taking from China are most apparent in his push for infrastructure development, investing heavily in highways, railways and airports to improve supply chains and connectivity.

India has quintupled its annual spending on roads and railways during Mr. Modi’s nine years in power

As Mr. Modi has boxed in opponents, cowed the press and overwhelmed independent elements of civil society, his government has lashed out at expressions of concern from abroad as evidence of a colonial plot to undermine India or a lack of understanding of India’s “civilizational” approach — both elements that diplomats had long heard in China’s own defensiveness.

All the while, the increasing militancy of his Hindu nationalist supporters, as arms of the state hang back and give perpetrators a free pass, exacerbates India’s religious fault lines and clashes that threaten to disrupt India’s rise.

Even as India tries to align its growing technological and economic capacity to capitalize on the Western tensions with China, it is determined to stick to its neutrality and maintain a balancing act between the United States and Russia. There is also the question of whether the West’s shift from China, the linchpin of the global economy, is a temporary recalibration or a more fundamental one.

“China took advantage of a favorable geopolitical moment to really transform itself by having access to technology, to capital, to markets led by the United States. It took advantage of that to build itself up,” Mr. Saran said. “This could be that moment for India.”

Research published in the weekly Der Spiegel shows that the AfD, a party started by nationally minded economists who advocated a return to the Deutsche mark as the national currency, now uses language nearly identical to that of the defunct National Democratic Party of Germany (NPD), a small, virulently xenophobic, and openly neo-Nazi party that ran in German elections for decades but never managed to win seats in the Bundestag.

“They have major ideological overlaps. The AfD measures up to the NPD [of 2012] in almost all areas, even if the AfD appears more moderate in its party program.”

Documents attributed to both parties employ reactionary terminology, some of it straight from Nazi Germany, such as Umvolkung (population replacement) and Volkstod (death of the German nation), as well as Stimmvieh (voting cattle) for voters of opposing parties and Passdeutschen (foreign nationals holding German passports). And like the NPD, Spiegel reported in another study, the AfD maintains close links with violent militants.

this radicalism, which in the past had turned Germans off, has now lifted the AfD to new heights: It is polling at 22 percent support nationwide, second only to the Christian Democrats, and well over 30 percent in several states, making it the number one political force there in advance of autumn elections.

The current outburst of popular indignation at the AfD, echoed by all of the other major political parties, comes on the heels of an investigative exposé that found that at a clandestine meeting in November, ranking AfD personalities met with known neo-Nazis and wealthy financiers to hammer out plans for the forced deportation of foreign nationals and even foreign-born German citizens.

The extremists congregated at a hotel near Potsdam to design what they called a “remigration master plan” to forcibly repatriate millions of people. Shocked observers drew parallels to the 1942 Wannsee Conference, held not far from Potsdam, at which the Nazis coordinated their plan to deport and murder the entire Jewish population of Europe.

While some AfD politicos have tried to distance the party from the Potsdam meeting, others endorsed its purpose. “Remigration is not a secret plan, but a promise. … and there’s no better way to put it,” announced Hans-Christoph Berndt, the AfD point person in the Brandenburg state parliament, on Jan. 17.

they confirm the diagnosis of many experts that the AfD, under the leadership of its most extreme figures—particularly Björn Höcke, a member of the Thuringia legislature—has outpaced other European far-right parties in its radicalism. “The current AfD wouldn’t find a place in the ranks of the Sweden Democrats and most of the other more moderate far-right parties among the European Conservatives and Reformists faction in the European Parliament,”

She explained that like the AfD, the Sweden Democrats, the Finns Party (formerly the True Finns), and the Danish People’s Party are opposed to immigration and favor law-and-order states. But the Nordic rightists’ experiences in office pushed them to adapt to mainstream norms and policy options. (The Sweden Democrats are currently an informal supporter of the Swedish ruling coalition; the Finns are a coalition member in Finland; and the DPP acted as a support party to a conservative Danish government between 2001 and 2011, as well as from 2015 to 2019.)

The radicalized AfD, Jungar said, in contrast to these parties, actively courts militants, trades in antisemitic tropes, and toys with the proposition of Germany exiting NATO and the European Union

Moreover, AfD politicians have stood against adoption rights for same-sex couples, the inclusion of disabled kids in schools, and the legality of abortion. “These positions simply wouldn’t stand a chance in Sweden,”

“The FPO under Kickl has moved further to the right. It is now indistinguishable from the right-wingers in the AfD,” he argued. “They want people who they think don’t belong here out of Austria. They don’t want to gas them yet, but they want to strip people of their citizenship. They want to cut people’s social benefits to such an extent that their livelihoods are destroyed. That is essentially the program of parties like the AfD and the FPO. They harbor fantasies ranging from populist to fascist.

“By stacking the courts and clamping down on opposition forces, these parties gradually undermined the democratic order,” Opratko said. “This is the AfD’s model. It’s what they want to do.”

Dennett’s central mission was to demystify consciousness andbring it within the realm of science  So why do we find it so intuitive to think of ourselves as an inner being, an occupant in our bodies? ‘It’s a sort of metaphor. I like to say it’s a user illusion,’

Imagining an inner person allows us to communicate our motivations to other human beings and in turn communicate them to ourselves

While language allows us to articulate our inner lives, it also divides cultures, right down to the way we process information. Dennett explains it using the example of our perception of colour: ‘Different cultures have different ways of dividing up colour,’ he said. ‘There are a lot of experiments that show that what colours you can distinguish depends a lot on what culture you grew up in.’

westerners process people’s faces differently to non-westerners. The very movement patterns of our eyeballs are dictated by culture.

‘I think that some of the multiculturalism, some of the ardent defences of multiculturalism, are deeply misguided and regressive and I think postmodernism has actually harmed people in many nations

Recognising these cultural differences didn’t lead Dennett into moral relativism. ‘I am relieved not to have to confront some of the virtue-signalling and some of the doctrinaire attitudes that are now running rampant on college campuses,

Take the most obvious cases: the treatment of women in the Islamic world; the horrific reactions to homosexuality in many parts of the world that aren’t western. I think that there are clear reasons for preferring different cultural practices over others.

If we don’t create, endorse and establish some new rules and laws about how to think about this, we’re going to lose the capacity for human trust and that could be the end of civilisation.’