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Friedman’s thought, she argues, is more complex and subtle than has been understood: He raised pressing questions about the market, individualism, and the role of the state that will be with us for as long as capitalism endures.

Just as important, his time at Chicago taught Friedman about the intertwining of political, intellectual, and personal loyalties. He became a regular in an informal group of graduate students and junior faculty trying to consolidate the department as a center of free-market thought

by the 1930s, the leading figures at the University of Chicago were deeply committed to what had become known as price theory, which analyzed economic behavior in terms of the incentives and information reflected in prices. The economists who left their mark on Friedman sought to create predictive models of economic decision making, and they were politically invested in the ideal of an unencumbered marketplace.

Friedman was also shaped by older traditions of economic thought, in particular the vision of political economy advanced by thinkers such as Adam Smith and Alfred Marshall. For them, as for him, economics was not a narrow social science, concerned with increasing productivity and efficiency. It was closely linked to a broader set of political ideas and values, and it necessarily dealt with basic questions of justice, freedom, and the best way to organize society.

His libertarian ethos helped seed the far more openly hierarchical social and political conservatism that fuels much of our present-day political dysfunction.

But his fundamental commitments were consistent. In his early work on consumption habits, Friedman sought to puncture the arrogance of the postwar Keynesian economists, who claimed to be able to manipulate the economy from above, using taxes and spending to turn investment, consumption, and demand on and off like so many spigots

Instead, he believed that consumption patterns were dependent on local conditions and on lifetime expectations of income. The federal government, he argued, could do much less to affect economic demand—­and hence to fight recessions—­than the Keynesian consensus suggested.

In 1946, Friedman was hired by the University of Chicago, where he shut down efforts to recruit economists who didn’t subscribe to free-market views.

He was also legendary for his brutal classroom culture. One departmental memo, trying to rectify the situation, went so far as to remind faculty to please not treat a university student “like a dog.” What had started as a freewheeling, rebellious culture among the economists in Room Seven wound up as doctrinal rigidity.

Evidence leads her to argue more pointedly that Rose (credited only with providing “assistance”) essentially co-wrote Capitalism and Freedom (1962).

Burns implicitly exposes some of the limitations of Friedman’s focus on the economic benefits of innate individual talent. He had more than nature to thank for producing associates of such high caliber, ready to benefit him in his career. Culture and institutions clearly played a large role, and sexual discrimination during the 1930s, ’40s, and ’50s ensured that professional paths were anything but fair.

The state, he acknowledged, would have to take some responsibility for managing economic life—­and thus economists would be thrust into a public role. The question was what they would do with this new prominence.

Almost as soon as the Second World War ended, Friedman began to stake out a distinctive rhetorical position, arguing that the policy goals of the welfare state could be better accomplished by the free market

in Capitalism and Freedom, Friedman made the case that the real problem lay in the methods liberals employed, which involved interfering with the competitive price mechanism of the free market. Liberals weren’t morally wrong, just foolish, despite the vaunted expertise of their economic advisers.

In a rhetorical move that seemed designed to portray liberal political leaders as incompetent, he emphasized efficiency and the importance of the price system as a tool for social policy

For Friedman, the competitive market was the realm of innovation, creativity, and freedom. In constructing his arguments, he envisioned workers and consumers as individuals in a position to exert decisive economic power, always able to seek a higher wage, a better price, an improved product

The limits of this notion emerged starkly in his contorted attempts to apply economic reasoning to the problem of racism, which he described as merely a matter of taste that should be free from the “coercive power” of the law:

Although he personally rejected racial prejudice, he considered the question of whether Black children could attend good schools—and whether, given the “taste” for prejudice in the South, Black adults could find remunerative jobs—less important than the “right” of white southerners to make economic decisions that reflected their individual preferences. In fact, Friedman compared fair-employment laws to the Nuremberg Race Laws of Nazi Germany. Not only was this tone-deaf in the context of the surging 1960s civil-rights movement; it was a sign of how restricted his idea of freedom really was.

s the conservative movement started to make electoral gains in the ’70s, Friedman emerged as a full-throated challenger of liberal goals, not just methods

He campaigned for “tax limitation” amendments that would have restricted the ability of state governments to tax or spend

n a famous New York Times Magazine essay, he suggested that corporations had no “social responsibility” at all; they were accountable only for increasing their own profit

Friedman’s free-market certainties went on to win over neoliberals. By the time he and Rose published their 1998 memoir, Two Lucky People, their ideas, once on the margin of society, had become the reigning consensus.

That consensus is now in surprising disarray in the Republican Party that was once its stronghold. The startling rise in economic inequality and the continued erosion of middle-class living standards have called into question the idea that downsizing the welfare state, ending regulations, and expanding the reach of the market really do lead to greater economic well-being—let alone freedom.

Friedman—despite being caricatured as a key intellectual architect of anti-government politics—had actually internalized an underlying assumption of the New Deal era: that government policy should be the key focus of political action. Using market theory to reshape state and federal policy was a constant theme of his career.

Still, Friedman—­and the libertarian economic tradition he advanced—­bears more responsibility for the rise of a far right in the United States than Burns’s biography would suggest. His strategy of goading the left, fully on display in the various provocations of Free to Choose and even Capitalism and Freedom, has been a staple for conservatives ever since

He zealously promoted the kind of relentless individualism that undergirds parts of today’s right, most notably the gun lobby. The hostile spirit that he brought to civil-rights laws surfaces now in the idea that reliance on court decisions and legislation to address racial hierarchy itself hems in freedom

The opposition to centralized government that he championed informs a political culture that venerates local authority and private power, even when they are oppressive

his insistence (to quote Capitalism and Freedom) that “any … use of government is fraught with danger” has nurtured a deep pessimism that democratic politics can offer any route to redressing social and economic inequalities.

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

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

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

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

Hellscape

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

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

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

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

What does that mean for news? Nothing good.

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

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

Two big takeaways:

(1) Ad-supported publications will not survive

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

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

(2) Size is determinative.

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

Audiences were valuable; content was commoditized.

But everything in between? That’s a crapshoot.

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

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

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

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

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.

The videos promoted narratives that Chinese technology was superior to America’s, that the United States was doomed to economic collapse, and that China and Russia were responsible geopolitical players. Some of the clips fawned over Chinese companies like Huawei and denigrated American companies like Apple.

Content from at least 30 channels in the network drew nearly 120 million views and 730,000 subscribers since last year, along with occasional ads from Western companies

Disinformation — such as the false claim that some Southeast Asian nations had adopted the Chinese yuan as their own currency — was common. The videos were often able to quickly react to current events

he coordinated campaign might be “one of the most successful influence operations related to China ever witnessed on social media.”

YouTube said in a statement that its teams work around the clock to protect its community, adding that “we have invested heavily in robust systems to proactively detect coordinated influence operations.” The company said it welcomed research efforts and that it had shut down several of the channels mentioned in the report for violating the platform’s policies.

Efforts to push pro-China messaging have proliferated in recent years, but have featured largely low-quality content that attracted limited engagement or failed to sustain meaningful audiences

“This campaign actually leverages artificial intelligence, which gives it the ability to create persuasive threat content at scale at a very limited cost compared to previous campaigns we’ve seen,”

Historically, its influence operations have focused on defending the Communist Party government and its policies on issues like the persecution of Uyghurs or the fate of Taiwan

China began targeting the United States more directly amid the mass pro-democracy protests in Hong Kong in 2019 and continuing with the Covid-19 pandemic, echoing longstanding Russian efforts to discredit American leadership and influence at home and aboard.

Over the summer, researchers at Microsoft and other companies unearthed evidence of inauthentic accounts that China employed to falsely accuse the United States of using energy weapons to ignite the deadly wildfires in Hawaii in August.

Meta announced last month that it removed 4,789 Facebook accounts from China that were impersonating Americans to debate political issues, warning that the campaign appeared to be laying the groundwork for interference in the 2024 presidential elections.

It was the fifth network with ties to China that Meta had detected this year, the most of any other country.

The advent of artificial technology seems to have drawn special interest from Beijing. Ms. Keast of the Australian institute said that disinformation peddlers were increasingly using easily accessible video editing and A.I. programs to create large volumes of convincing content.

She said that the network of pro-China YouTube channels most likely fed English-language scripts into readily available online text-to-video software or other programs that require no technical expertise and can produce clips within minutes. Such programs often allow users to select A.I.-generated voice narration and customize the gender, accent and tone of voice.

In 39 of the videos, Ms. Keast found at least 10 artificially generated avatars advertised by a British A.I. company

she also discovered what may be the first example in an influence operation of a digital avatar created by a Chinese company — a woman in a red dress named Yanni.

The scale of the pro-China network is probably even larger, according to the report. Similar channels appeared to target Indonesian and French people. Three separate channels posted videos about chip production that used similar thumbnail images and the same title translated into English, French and Spanish.

“Pocock rejected the idea that politics or philosophy addressed the same problems over time — what justice meant for Aristotle did not mean the same for Hobbes or for Rousseau,”

“So explaining what political ideas meant in theory and in practice became the historian’s task.”

The Cambridge School attracted devotees across the world in departments of politics, history, philosophy, literature and language — scholars who were admonished to set aside any modern-day assumptions and prejudices they might hold when delving into the past.

“Readers, Christian or non-believing, who may find themselves involved in analyses of thought they consider obsolete or false, are asked to remember that they are studying the history of a time when such thinking was offered and read seriously,” he wrote.

Professor Pocock’s first book, “The Ancient Constitution and the Feudal Law,” made clear that he would not be a conventional historian. The book asked how people in the 17th century viewed their past, and he wasn’t satisfied with drawing on the go-to philosopher of the period, John Locke. As Colin Kidd wrote in The London Review of Books in 2008, the book “drove a bypass around Locke” and “concentrated instead on a set of debates among such obscure antiquaries as William Petyt, James Tyrrell, William Atwood and Robert Brady.”

“The Machiavellian Moment” cemented Professor Pocock’s reputation among historians, and it continued to grow from there. The first volume of “Barbarism and Religion” came out in 1999, when Professor Pocock was in his mid-70s. Volume 6 appeared in 2015. He also edited or co-edited “The Political Works of James Harrington” (1977), “Edmund Burke: Reflections on the Revolution in France” (1987) and “The Varieties of British Political Thought, 1500-1800” (1993), among other books.

“Pocock’s central contention,” the Oxford historian Keith Thomas wrote in The New York Review of Books in 1986, “is that a work of political thought can only be understood if the reader is aware of the contemporary linguistic constraints to which its author was subject, for these constraints prescribed both his subject matter and the way in which that subject matter was conceptualized.”

its application to the history of political ideas forms a great contrast to the assumptions of the 1950s, when it was widely thought that the close reading of a text by an analytic philosopher was sufficient to establish its meaning, even though the philosopher was quite innocent of any knowledge of the period in which the text was written or of the linguistic traditions within which its author operated.”

“Historians need to understand that the history of discourse is not a simple linear sequence in which new patterns overcome and replace the old,” he wrote in 1988 in a preface to a reissue of “Politics, Language and Time,” a 1971 essay collection, “but a complex dialogue in which these patterns persist in transforming one another.”

Things that were long big fun now overwhelm, exhaust and annoy. The holiday season is an extended exercise in excess and loud, often sleazy sweaters.

Which means it is nothing of the sort. This is the drag equivalent of fun and suggests that fun is done.

Adults assiduously record themselves appearing to have something masquerading as “fun,” a fusillade of Coachellic micro social aggressions unleashed on multiple social media platforms. Look at me having so much FUN!

“I feel like I should be having more fun than I’m actually having,” says Alyssa Alvarez, a social media marketing manager and DJ in Detroit, expressing a sentiment that many share. “There are expectations of what I want people to believe that my life is like rather than what my life is actually like.”

Weddings have morphed into multistage stress extravaganzas while doubling as express paths to insolvency: destination proposals for the whole family, destination bachelorette and bachelor blowouts, destination weddings in remote barns with limited lodging, something called a “buddymoon” (bring the gang!) and planners to help facilitate the same custom cocktailsness of it all.

What could be a greater cause for joy or more natural than having a baby? Apparently, not much these days. Impending parenthood is overthought and over-apped, incorporating more savings-draining events that didn’t exist a few decades ago: babymoons and lethal, fire-inducing, gender-reveal gatherings and baby showers so over-the-top as to shame weddings.

Retirements must be purposeful. Also, occasions for an acute identity crisis. You need to have a plan, a mission, a coach, a packed color-coded grid of daily activities in a culture where our jobs are our identities, our worth tied to employment.

Vacations are overscheduled with too many activities, FOMO on steroids, a paradox of choice-inducing decision fatigue, so much so that people return home exhausted and in need of another one.

“The world is so much less about human connection,” says Amanda Richards, 34, who works in casting in Los Angeles and is a graduate of Cudworth’s course. “We do more things virtually. People are more isolated. And there’s all this toxic positivity to convince people of how happy you are.”

For eons, early adulthood was considered an age of peak fun. Now, according to several studies, it’s a protracted state of anxiety and depression.

Because there is now a coach for everything, Alvarez hired the “party coach” Evan Cudworth, taking his $497 course this fall on how to pursue “intentional fun.” (It now costs $555.)

Instead of this being the most wonderful time of the year, we battle holiday fatigue, relentless beseeching for our money and, if Fox News is to be believed, a war on Christmas that is nearing its third decade.

Blame it on technological advances that tether us to work without cessation

Blame it on the pandemic, which exacerbated so much while delivering Zoomageddon.

Blame it on 2004, with the advent of Facebook, which led to Twitter (okay, X), Instagram, Threads, TikTok and who-knows-what lurking in the ether.

Blame it again on 2004 and the introduction of FOMO, our dread of missing out, broadcast through multiple social media spigots

“So many people are retreating into their phones, into anxiety,” says Cudworth, 37, from Chicago. “I’m helping people rediscover what fun means to them.”

His mandate is redefining fun: cutting back on bingeing screen time, eradicating envy scrolling, getting outside, moving, dancing. “With technology, we don’t allow ourselves to be present. You’re always thinking ‘something is better around the corner,’” Cudworth says, the now squandered in pursuit of the future.

Blame it on an American culture that values work, productivity, power, wealth, status and more work over leisure

ow do Americans spend their leisure hours when they might be having fun with others, making those vital in-person connections? Watching television, our favorite free time and “sports activity” (yes, that’s how it’s classified), according to the Bureau of Labor Statistics, an average of 2.8 hours daily.

“That’s way more television than you really need. We put play on the back burner,” says Pat Rumbaugh, 65, of Takoma Park, Md. She’s “The Play Lady,” who organizes unorganized play for adults

Catherine Price, the author of “The Power of Fun: How to Feel Alive Again,” believes “we’re totally misdoing leisure” and “not leaving any room for spontaneity.”

To Price, True Fun is the confluence of connection (other people, nature), playfulness (lightheartedness, freedom) and flow (being fully engaged, present), which is not as challenging as it sounds. “You can have fun in any context. Playfulness is about an attitude,”

Back in the day, co-workers were friends. (Sometimes, more.) After hours, they gathered for drinks, played softball. Today, because of email, Slack and remote work, offices are half empty and far quieter than libraries.

“We go to work and there’s no sense of connection and camaraderie,” says Davis, who was long employed by his city’s department of parks and recreation. “People feel emotionally disconnected. Healthy conversations are the precursor of fun. We’ve lost the art of communication. Our spirit comes home with us. If you don’t communicate at work, what are you coming home with?”

This is triggering a U.S.-China cold war, mass migrations from south to north and an America that has become more unreliable than indispensable.

that’s not the half of it. Because now that advanced military technologies like drones are readily available, smaller players can wield much more power and project it more widely than ever before, enabling even their bad choices to shake the world

This is why I referred to Russia’s invasion of Ukraine as our first true world war, and why I feel that Hamas’s war with Israel is in some ways our second true world war.

They are being fought on both physical battlefields and digital ones, with huge global reach and implications.

Indeed, in today’s tightly wired world, it is possible that the war over the Gaza Strip — which is roughly twice the size of Washington, D.C. — could decide the next president in Washington, D.C., as some young Democrats abandon President Biden because of his support for Israel.

before we become too pessimistic, let us remember that these choices are just that: choices. There was nothing inevitable or foreordained about them

Gorbachev, Deng, Anwar el-Sadat, Menachem Begin, George H.W. Bush and Volodymyr Zelensky, to name but a few, faced excruciating choices, but they chose forks in the road that led to a safer and more prosperous world, at least for a time

What is the essential ingredient that Dubai has and Gaza lacks? Because both began, in one sense, as the convergence of sand and seawater at crucial intersections of the world.

The short answer is visionary leadership.Dubai has benefited from two generations of monarchs in the United Arab Emirates who had a powerful vision of how the U.A.E. in general and the emirate of Dubai in particular could choose to be Arab, modern, pluralistic, globalized and embracing of a moderate interpretation of Islam

Their formula incorporates a radical openness to the world, an emphasis on free markets and education, a ban on extremist political Islam, relatively little corruption, a strong rule of law promulgated from the top down and a relentless commitment to economic diversification, talent recruitment and development.

Any of Dubai’s neighbors — Kuwait, Qatar, Oman, Bahrain, Iran and Saudi Arabia — could have done the same with their similar coastlines, but it was the U.A.E. that pulled it off by making the choices it made.

Compare that with Gaza, where the role models today are Hamas martyrs in its endless war with Israel.

Among the most ignorant and vile things that have been said about this Gaza war is that Hamas had no choice — that its wars with Israel, culminating on Oct. 7 with a murderous rampage, the kidnappings of Israelis as young as 10 months and as old as 86 and the rape of Israeli women, could somehow be excused as a justifiable jailbreak by pent-up males.

Let’s go to the videotape: In September 2005, Ariel Sharon completed a unilateral withdrawal of all Israeli forces and settlements from Gaza, which Israel occupied in the 1967 war. In short order, Hamas began attacking the crossing points between Gaza and Israel to show that even if Israel was gone, the resistance movement wasn’t over; these crossing points were a lifeline for commerce and jobs, and Israel eventually reduced the number of crossings from six to two.

In January 2006, the Palestinians held elections hoping to give the Palestinian Authority legitimacy to run Gaza and the West Bank. There was a debate among Israeli, Palestinian and Bush administration officials over whether Hamas should be allowed to run in the elections — because it had rejected the Oslo peace accords with Israel.

Yossi Beilin, one of the Israeli architects of Oslo, told me that he and others argued that Hamas should not be allowed to run, as did many members of Fatah, Arafat’s group, who had embraced Oslo and recognized Israel. But the Bush team insisted that Hamas be permitted to run without embracing Oslo, hoping that it would lose and this would be its ultimate refutation.

Fatah ran unrealistically high numbers of candidates in many districts, dividing the vote, while the more disciplined Hamas ran carefully targeted slates and managed to win the parliamentary majority.

Hamas then faced a critical choice: Now that it controlled the Palestinian parliament, it could work within the Oslo Accords and the Paris protocol that governed economic ties between Israel, Gaza and the West Bank — or not.

Hamas chose not to — making a clash between Hamas and Fatah, which supported Oslo, inevitable

That led to the first Israeli economic blockade of Gaza — and what would be 22 years of on-and-off Hamas rocket attacks, Israeli checkpoint openings and closings, wars and cease-fires, all culminating on Oct. 7.

These were fateful choices. Once Sharon pulled Israel out of Gaza, Palestinians were left, for the first time ever, with total control over a piece of land. Yes, it was an impoverished slice of sand and coastal seawater, with some agricultural areas. And it was not the ancestral home of most of its residents. But it was theirs to build anything they wanted.

Hamas had a choice: to replicate Dubai in 2023 or replicate Hanoi in 1968. It chose to replicate Hanoi, whose Củ Chi tunnel network served as the launchpad for the ’68 Tet offensive.

Hamas is not simply engaged in some pure-as-the-driven-snow anticolonial struggle against Israel. Only Hamas’s useful idiots on U.S. college campuses would believe that.

Hamas is engaged in a raw power struggle with Fatah over who will control Gaza and the West Bank, and it’s engaged in a power struggle in the region — alongside other pro-Muslim Brotherhood parties and regimes (like Turkey and Qatar) — against pro-Western monarchies like Saudi Arabia, Jordan, Kuwait and the U.A.E. and military-led regimes like Egypt’s.

In that struggle, Hamas wanted Gaza isolated and in conflict with Israel because that allowed Hamas to maintain its iron-fisted political and Islamist grip over the strip, foregoing elections and controlling all the smuggling routes in and out, which funded its tunnels and war machine and the lifestyle of its leaders and loyalists

The only exit from this mutually assured destruction is to bring in some transformed version of the Palestinian Authority in the West Bank — or a whole new P.L.O.-appointed government of Palestinian technocrats — in partnership with moderate Arab states like Egypt, Jordan and Saudi Arabia. But when I raise that with many Israelis right now, they tell me, “Tom, it’s not the time. No one wants to hear it.”

please, spare me the Harvard Yard nonsense that this war is all about the innocent, colonized oppressed and the evil, colonizing oppressors; that Israel alone was responsible for the isolation of Gaza; and that the only choice Hamas had for years was to create an underground “skyline” of tunnels up to 230 feet deep (contra Dubai) and that its only choice on Oct. 7 was martyrdom.

But our story about agency and choices does not stop there. Benjamin Netanyahu, Israel’s longest-serving prime minister — 16 years — also made choices. And even before this war, he made terrible ones — for Israel and for Jews all over the world.

Before this war, Netanyahu actively worked to keep the Palestinians divided and weak by strengthening Hamas in Gaza with billions of dollars from Qatar, while simultaneously working to discredit and delegitimize the more moderate Palestinian Authority in Ramallah, committed to Oslo and nonviolence in the West Bank.

Netanyahu’s goal has always been to destroy the Oslo option once and for all. In that, Bibi and Hamas have always needed each other: Bibi to tell the United States and Israelis that he had no choice, and Hamas to tell Gazans and its new and naïve supporters around the world that the Palestinians’ only choice was armed struggle led by Hamas.

This is now a common strategy for consolidating and holding power forever by a single political faction and disguising it with an ideology of resistance. It’s no wonder they all support one another.

Don’t they get it? Netanyahu’s greatest political achievement has been to persuade Israelis and the world that it’s never the right time to talk about the morally corrosive occupation and how to help build a credible Palestinian partner to take it off Israel’s hands.

He and the settlers wore everyone down. When I covered the State Department in the early 1990s, West Bank settlements were routinely described by U.S. officials as “obstacles to peace.” But that phrase was gradually dropped. The Trump administration even decided to stop calling the West Bank “occupied” territory.

Israel is being surrounded by what I call Iran’s landcraft carriers (as opposed to our aircraft carriers): Hamas, Hezbollah, the Houthis and Shiite militias in Iraq. Iran is squeezing Israel into a multifront war with its proxies. I truly worry for Israel.

But Israel will have neither the sympathy of the world that it needs nor the multiple allies it needs to confront this Iranian octopus, nor the Palestinian partners it needs to govern any post-Hamas Gaza, nor the lasting support of its best friend in the world, Joe Biden, unless it is ready to choose a long-term pathway for separating from the Palestinians with an improved, legitimate Palestinian partner.

For all these reasons, if Netanyahu keeps refusing because, once again, politically, the time is not right for him, Biden will have to choose, too — between America’s interests and Netanyahu’s.

In sum, this war is so ugly, deadly and painful, it is no wonder that so many Palestinians and Israelis want to just focus on survival and not on any of the choices that got them here

The Haaretz writer Dahlia Scheindlin put it beautifully in a recent essay:The situation today is so terrible that people run from reality as they run from rockets — and hide in the shelter of their blind spots. It’s pointless to wag fingers. The only thing left to do is try and change that reality.

The Chinese are “watching the war in Ukraine closely and will likely use nuclear coercion to their advantage” in future conflicts, the commander, Adm. Charles A. Richard, told Congress.

Others are learning their own lessons. North Korea, which President Donald J. Trump boasted he would disarm with one-on-one diplomacy, is building new weapons.

What is fast approaching, experts say, is a second nuclear age full of new dangers and uncertainties, less predictable than during the Cold War, with established restraints giving way to more naked threats to reach for such weapons — and a need for new strategies to keep the atomic peace.

the dawning era would feature “both a greater risk of a nuclear arms race and heightened incentives for states to resort to nuclear weapons in a crisis.”

President Vladimir V. Putin of Russia opened the Ukraine war with a declaration that he was putting his nuclear abilities on some kind of heightened alert — a clear message to Washington to back off.

In the years leading up to the Ukraine invasion, Mr. Putin regularly punctuated his speeches with nuclear propaganda videos, including one that showed a swarm of warheads descending on Florida.

They are designed by the Russians to blur the distinction between conventional and nuclear weapons, which strategists fear makes their use more thinkable.

escalate to de-escalate.”

“There are a lot of things that he would do in the context of escalation before he would get to nuclear weapons,” Ms. Haines said.

The White House, the Pentagon and the intelligence agencies are examining the implications of any potential Russian claim that it is conducting a nuclear test or the use by its forces of a relatively small, battlefield nuclear weapon to demonstrate its ability.

The idea would be to “signal immediate de-escalation” followed by international condemnation, said one administration official who spoke on the condition of anonymity to provide insight into classified topics.

Henry Kissinger noted in a recent interview with The Financial Times that “there’s almost no discussion internationally about what would happen if the weapons actually became used.” He added: “We are now living in a totally new era.”

The simplest theory is that if China is going to be a superpower, it needs a superpower-sized arsenal. But another is that Beijing recognizes that all the familiar theories of nuclear balance of power are eroding.

“China is heralding a paradigm shift to something much less stable,” Mr. Krepinevich wrote, “a tripolar nuclear system.”

“They’re up to something,” Mr. Albright said of Saudi Arabia, “and they’re rich.”

To varying degrees, we have all inherited a muddled understanding of race, ancestry and phenotype from the Enlightenment,

if we don’t disentangle these concepts, we may miss the great promise of using genetics to push back against a very long and sad history of the misuse of science for pernicious purposes.

One of the key moments in the evolution of modern concepts of race occurred in France in 1741, when the members of Bordeaux’s Royal Academy of Sciences held a continentwide essay contest on the “cause” of dark skin and textured hair among African populations. Why, they asked, were Black people Black?

this contest signaled a new era of “scientific racism.” In the decades that followed, naturalists increasingly subdivided the human species into several so-called races by things like skin color, hair texture, skull shape and, most perniciously, according to supposedly transcendent essences.

genetics — or, for that matter, any science — has the potential to be misused, co-opted by racist ideologies and employed to bolster harmful narratives about racial purity or biological superiority.

There is no category for white in genetic analysis; half of his ancestry traces back to regions in Europe. We should never forget that whiteness, like Blackness, is just another social fiction.

If, throughout the 18th, 19th and 20th centuries, science put an enormous amount of effort into dividing the human species into separate categories, 21st-century genetic analysis promises to reveal just how meaningless those categories are — and how connected we’ve been all along.

it feels urgent that we develop new language for discussing the relationship between identity, ancestry, history and science

DNA analysis could help create that language by offering more nuanced ways of looking at individual origins and a more unifying narrative about our shared heritage

While, biologically speaking, the idea of individual human races with different origins is as farcical as the medieval belief that elves cause hiccups, the social reality of race is undeniable.

The multitude of population clusters, regions and genetic groups reflected in DNA tests counters existing narratives that try to reduce the astonishing variety of the human community to the four or five socially constructed races of man

But if we can, at the very least, embrace the understanding that race (a toxic social construction) and ancestry (a shared genetic history) are not only distinct but also fundamentally opposed — and teach that in our classrooms — it could go a long way toward freeing us from some of the binds in which scientific racism have trapped us.

The stories embedded in our genes beg to be told. They tell of ancestral diversity that stretches back thousands of years and ultimately underscores all that we — despite superficial physical differences — have in common.

What matters for Mearsheimer is not so much the imperialist competition of the 1890s and 1900s, but the great train-wreck that resulted, in 1914. What concerns him above all is how great power rivalry leads to war.

what Specter’s book allows us to do is to squarely locate Mearsheimer’s brand of “offensive” or “great power realism” within a history that goes back to the moment of high imperialism in the 1890s.

Specter focuses on the tradition of imperialist geopolitics that goes back to geographers like Friedrich Ratzel and naval theorists like Alfred Mahan, and descends from them to Karl Haushofer and Carl Schmitt in the 1930s and 1940s

What Mearsheimer sees himself as doing, as far as I can tell, is to speak truth to power and to the public with a view to dialing back excessive ambition and avoiding ruinous competition.

It is important to emphasize, I think, that Mearsheimer is less a theorist or apologist for great power policy as such, than an analyst of why great power clashes lead to wars.

I take issue with him in the New Statesman. Not principally on moral or ethical grounds, though I do find the naturalization of war abhorrent, but above all because I think Mearsheimer’s reified view of international politics effectively evacuates any subtle understanding of what statecraft actually consists of.

The theory we need here is not the logic of great power self-assertion, so much as the logic of great power self-destruction.

abstraction is a risky business and you have to get your abstraction “right”, otherwise you risk missing what is essential and engaging in a kind of callous and at times ludicrous reductionism.

Taking Mearsheimer’s account of great power politics for the real thing is, to my mind, a bit like confusing the anatomy of sex ed, with actual eroticism, or romance. It isn’t exactly wrong, but it entirely misses the point

the alarming thing is not so much the possibility that Mearsheimer offers justifications for what Putin has done, but, rather, the degree to which, in his reification of power relations, Mearsheimer’s thought seems to mirror Putin’s actions.

To call that kind of description an explanation begs the question. It is more like an analogue model. And that ought to be deeply alarming.

If for Putin as for Mearsheimer war really is just the extension of policy by other means, and if he was capable of taking this first step, where does this end?

While most editors recognize the importance of criticism in helping readers decipher contemporary art, and the multibillion-dollar industry it has created, venues for such writing are shrinking. Over the years, newspapers including The Philadelphia Inquirer and The Miami Herald have trimmed critics’ jobs.

In December, the Penske Media Corporation announced that it had acquired Artforum, a contemporary art journal, and was bringing the title under the same ownership as its two competitors, ARTnews and Art in America. Its sister publication, Bookforum, was not acquired and ceased operations. Through the pandemic, other outlets have shuttered, including popular blogs run by SFMOMA and the Walker Art Center in Minneapolis as well as smaller magazines called Astra and Elephant.

(National newspapers with art critics on staff include The New York Times, The Los Angeles Times, The Boston Globe and The Washington Post. )

David Velasco, editor in chief of Artforum, said in an interview that he hoped the magazine’s acquisition would improve the publication’s financial picture. The magazine runs nearly 700 reviews a year, Velasco said; about half of those run online and pay $50 for roughly 250 words. “Nobody I know who knows about art does it for the money,” Velasco said, “but I would love to arrive at a point where people could.”

Noah Dillon, who was on the AICA-USA board until he resigned last year, has been reluctant to recommend that anyone follow his path to become a critic. Not that they could. The graduate program in art writing that he attended at the School of Visual Arts in Manhattan also closed during the pandemic.

“It’s crazy that the ideal job nowadays is producing catalog essays for galleries, which are basically just sales pitches,” Dillon said in a phone interview. “Critical thinking about art is not valued financially.”

Large galleries — including Gagosian, Hauser & Wirth, and Pace Gallery — now produce their own publications with interviews and articles sometimes written by the same freelance critics who simultaneously moonlight as curators and marketers. Within its membership, AICA-USA has a number of writers who belong to all three categories.

According to Lilly Wei, a longtime AICA-USA board member who recently resigned, the group explored different ways of protecting writers in the industry. There were unrealized plans of turning the organization into a union; others hoped to create a permanent emergency fund to keep financially struggling critics afloat. She said the organization has instead canceled initiatives, including an awards program for the best exhibitions across the country.

“It just came down to not having enough money,” said Terence Trouillot, a senior editor at Frieze, a contemporary art magazine . He spent nearly three years on the AICA-USA board, resigning in 2022. He said that initiatives to re-energize the group “were just moving too slowly.”

The organization has yearly dues of $115 and provides free access to many museums. But some members complained that the fee was too expensive for young critics, yet not enough to support significant programming.

Efforts to revive AICA-USA are continuing. In January, Jasmine Amussen joined the organization’s board to help rethink the meaning of criticism for a younger generation.

Amussen, 33, is the editor of Burnaway, which focuses on criticism in the American South and often features young Black artists. (The magazine started in 2008 in response to layoffs at the Atlanta Journal-Constitution’s culture section and now runs as a nonprofit with four full-time employees and a budget that mostly consists of grants.)

a new generation was coming to the fore.  This generation had been born between 1965 and 1980 constituting some 65 million individuals.  Self- righteous outrage that had not been considered cool in an earlier generation had begun to change to more than acceptable.

America had been consumed with non-stories while ignoring foreboding signs of impending danger for some time.  The decade would end according to Klosterman, not with the last day of the decade but in 2001.  The Nineties collapsed with the World Trade Center Towers.

it is wise yet humorous, thoughtful yet fun, insightful yet unpredictable. So, if you are interested in reliving the decade in a totally unconventional manner, I would suggest you read it with your seatbelt on, because you are in for a bumpy ride.

As I wrote in my book, at my most partisan moment I once gave a speech in which I said words that shame me to this day. 

we forget a fundamental truth—our own maladies often make us unable to see the world clearly. Or, as Jesus said, “You hypocrite, first take the plank out of your own eye, and then you will see clearly to remove the speck from your brother’s eye.” In so many ways, we’ve become the People of the Plank, blind to the pain we’ve inflicted on the public even as we try desperately to protect ourselves from them.

Early church fathers were far, far more concerned with the faith and virtue of the church than the maladies of the Romans. 

“I believe the two greatest threats to the United States are university leftists at home and jihadists abroad.”

In Iraq, the reality was so profoundly different that words can barely begin to describe all the distinctions

I didn’t exactly become post-partisan upon my return (that came later), but I gained the perspective that permitted me to start the process of pulling the plank from my own eye.

it’s opened my eyes to many truths that were new to me. Among them, the church should be focused much more on its own virtue than the virtue of the rest of the world.

In addition, if there were no grounds for Christians to live with a “spirit of fear” at the height of the Roman Empire, there are no grounds for us to live with a spirit of fear in our nation today. Yet fear seems to dominate Christian political activism—including fear of the left, of CRT, and sometimes even fear for the very existence of a free church in the United States of America.