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even now, as their stories are being dramatized in a movie and shown in theaters across the country, there is a campaign in Oklahoma — this time with legislation — to deter the history from being taught in schools.

The movement to suppress elements of American history extends well beyond Oklahoma. According to an analysis by The Washington Post, more than two dozen states have adopted laws that make it easier to remove books from school libraries and to prevent certain teaching on race, gender and sexuality

In 2023, PEN America, which defends freedom of speech, reported that book bans in U.S. public school classrooms and libraries had surged 33 percent over the previous school year, with more than 3,000 recorded removals; among them are classics by the Nobel laureate Toni Morrison (banned in 30 school districts) and Margaret Atwood (banned in 34). School curriculums are being revised to mask discomfiting truths — so much so that in Florida students will now be taught that some African Americans benefited from slavery because it gave them “skills.”

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.

Helen Toner, the director of strategy and foundational research grants for Center for Security and Emerging Technology at Georgetown, and Tasha McCauley, whose LinkedIn profile says she began work as an adjunct senior management scientist at Rand Corporation earlier this year. Toner has previously spoken at conferences for a philanthropic movement closely tied to AI safety. McCauley is also involved in the work.

Sutskever helped create AI software at the University of Toronto, called AlexNet, which classified objects in photographs with more accuracy than any previous software had achieved, laying much of the foundation for the field of computer vision and deep learning.

He recently shared a radically different vision for how AI might evolve in the near term. Within five to 10 years, there could be “data centers that are much smarter than people,” Sutskever said on a recent episode of the AI podcast “No Priors.” Not just in terms of memory or knowledge, but with a deeper insight and ability to learn faster than humans.

At the bare minimum, Sutskever added, it’s important to work on controlling superintelligence today. “Imprinting onto them a strong desire to be nice and kind to people — because those data centers,” he said, “they will be really quite powerful.”

OpenAI has a unique governing structure, which it adopted in 2019. It created a for-profit subsidiary that allowed investors a return on the money they invested into OpenAI, but capped how much they could get back, with the rest flowing back into the company’s nonprofit. The company’s structure also allows OpenAI’s nonprofit board to govern the activities of the for-profit entity, including the power to fire its chief executive.

As news of the circumstances around Altman’s ouster began to come out, Silicon Valley circles have turned to anger at OpenAI’s board.

“What happened at OpenAI today is a board coup that we have not seen the likes of since 1985 when the then-Apple board pushed out Steve Jobs,” Ron Conway, a longtime venture capitalist who was one of the attendees at OpenAI’s developer conference, said on X. “It is shocking, it is irresponsible, and it does not do right by Sam and Greg or all the builders in OpenAI.”

Biden has backed multiple actions, including a renewed assault weapons ban and universal background checks. But the president, whose fellow Democrats only narrowly control Congress, has cited the limits of executive action and urged lawmakers to act.Democrats need 10 Republican senators' support to pass any legislation.

This week the first of 21 funerals are scheduled in Uvalde.Residents of the shattered town urged Biden to "do something" about gun violence as he visited on Sunday to meet with families and first responders.

While school shootings are shocking, U.S. gun violence occurs regularly. Over the weekend, six people were shot and wounded in Chattanooga, Tennessee, while at least one person died and several were injured amid gunfire at an outdoor festival in Oklahoma City, local media reported.

With Mahinda Rajapaksa, the president, then at the peak of his powers, he did what many nationalist strongmen do: erect tributes to himself.

That’s now all gone. Sri Lanka is an international basket case whose foreign reserves — which once stood at over $6 billion under the Rajapaksas — have dwindled to almost nothing.

The collapse is partly a result of the loss of tourism during the pandemic, a problem made worse as war has kept away many of the Russians and Ukrainians who used to visit in large numbers. But the family’s economic mismanagement and denial of festering problems have also contributed mightily.

With food prices rising, electricity often cut and lifesaving medicines scarce, protesters have pushed Mr. Rajapaksa, 76, out of his latest position — prime minister — and are demanding that his brother Gotabaya, 72, give up the presidency.

Just outside the private residence of Mr. Rajapaksa, the Carlton House, they tied ropes to a gold-colored statue of his father, D.A. Rajapaksa. When they couldn’t drag it down, they dug under its feet until it collapsed. And around the corner from the family’s sprawling ancestral estate, they torched the museum memorializing the resting place of the patriarch and his wife.

“Whatever the politics, they shouldn’t have done this to their parents’ resting place.”

Before the economy crashed, she would sell 30 to 40 pots a day. That number has since dropped to about 20, as people have saved for other necessities. Most days in recent weeks, she has come back with half of her stack of 15 unsold.

During her grocery trips, she can buy only half of what she did in the past.

She was clear about who was to blame: the Rajapaksas.

“If you are investing in debt, you should really be looking at return — and quick return. You can’t do all your long-term, hard infrastructure projects on debt,” said Eran Wickramaratne, a former banker turned state minister of finance. “We completely overleveraged ourselves, and the returns are not there.”

With their power consolidated, they announced broad tax cuts — rapidly undoing the work of aligning Sri Lanka’s spending more with its means — and made a disastrous decision to ban chemical fertilizers in hopes of turning the country toward organic farming.

At the airport, which for a time was used to store grain, the only outsiders are the crews of occasional cargo flights, or groups of curious villagers on tours to see the complex. The cricket stadium, where the scoreboard clock is stuck in some afternoon past, was at one point rented out as a wedding venue to produce some revenue. It has a capacity of 35,000, more than the town of Hambantota’s entire population, 25,000.

“But these megaprojects were meaningless,” he said. “This region still has elephants crossing the roads, and people are still cultivating paddy as a livelihood. So these projects were unnecessary.”

“They did a lot — they won the war, they built roads,” Ms. Niroshani said.

But what about economic hardship, Ms. Wijeyawickrama asked.

“In a few days it may be that we have nothing to eat.”

Irma Garcia, 46: Garcia spent 23 years at Robb Elementary, five of them as Mireles’s co-teacher. She liked to sing along to classic rock tunes and help her nephew, a college student, with his homework. Garcia was known as a steadfast optimist. She enjoyed barbecuing with her husband of 24 years, Joe; he died yesterday, of a heart attack.

he Bureau of Alcohol, Tobacco, Firearms and Explosives is also assisting on scene, the ATF Dallas Field Division said on Twitter. "What happened today in Tulsa is a senseless act of violence and hatred," Oklahoma Gov. Kevin Stitt wrote on Twitter. "I am grateful for the quick and brave actions of the Tulsa Police Department and other first responders who did their best to contain a terrible situation."

Debra Proctor was in another building on the hospital campus for a doctor's appointment when she heard police sirens ringing out. When she stepped outside, first responders were lined up everywhere, she told CNN. Proctor, who has been a registered nurse for more than four decades, said it was a "shocking" scene."Police were everywhere in the parking lot, up and down the surrounding blocks," Proctor said. "They were still arriving when I was leaving."Kalen Davis, a lifelong Tulsa resident, was waiting in traffic around 5 p.m. local time when she saw multiple police cars responding to the scene.

Police later received information that the shooter may have left a bomb in a residence in Muskogee, Oklahoma, Muskogee police said Wednesday night. The home was searched by a bomb squad and no explosives were found, CBS Tulsa affiliate KOTV reported, citing Muskogee Police. Surrounding homes were either evacuated or residents were told to shelter in place.Muskogee is located about 50 miles southeast of Tulsa.Tulsa police asked family and friends of the victims and survivors to go to Memorial High School, a block from the hospital campus, to wait to learn the fate of the people at the shooting scene, KOTV said.  

Hodges said she was in lockdown for just under two hours.Another employee wondered out loud, "What's going on with the world these days?" A witness observed, "I mean, it's a doctor's office, like, you can't go nowhere no more without something happening. I's just crazy."

who got the future most right? For the truth is that dystopia is now, not in some future date.

Science fiction provides us with a large sample of imagined discontinuities that might not occur if we only looked backwards.

Fahrenheit 451 (published in 1953 but set in 1999) describes an illiberal America where books are banned and the job of firemen is to burn them. (Though the novel is sometimes interpreted as a critique of McCarthyism, Bradbury’s real message was that the preference of ordinary people for the vacuous entertainment of TV and the willingness of religious minorities to demand censorship together posed a creeping threat to the book as a form for serious content.)

In a remarkable letter written in October 1949, Aldous Huxley — who had been Orwell’s French teacher at Eton — warned him that he was capturing his own present rather than the likely future. ‘The philosophy of the ruling minority in Nineteen Eighty-Four,’ Huxley wrote, ‘is a sadism which has been carried to its logical conclusion… Whether in actual fact the policy of the boot-on-the-face can go on indefinitely seems doubtful. My own belief is that the ruling oligarchy will find less arduous and wasteful ways of governing and of satisfying its lust for power, and these ways will resemble those which I described in Brave New World’. Huxley’s Brave New World (1932) is a very different dystopia. Citizens submit to a caste system, conditioned to be content with physical pleasure. Self-medication (‘soma’), constant entertainment (the ‘feelies’), regular holidays and ubiquitous sexual titillation are the basis for mass compliance. Censorship and propaganda play a part, but overt coercion is rarely visible. The West today seems more Huxley than Orwell: a world more of corporate distraction than state brutality.

Yet none of these authors truly foresaw our networked world, which has combined the rising technological acceleration with a slackening of progress in other areas, such as nuclear energy, and a degeneration of governance. The real prophets are less known figures, like John Brunner, whose Stand on Zanzibar (1968) is set at a time — 2010 — when population pressure has caused social division and political extremism. Despite the threat of terrorism, US corporations are booming, thanks to a supercomputer. China is America’s new rival. Europe has united. Brunner envisaged affirmative action, genetic engineering, Viagra, Detroit’s collapse, satellite TV, in-flight video, gay marriage, laser printing, electric cars, the decriminalisation of marijuana and the decline of tobacco. There’s even a progressive president (albeit of the Africa state of Beninia, not America) named ‘Obomi’

With comparable prescience, William Gibson’s Neuromancer (1984) anticipates the world wide web and AI. Opening in the dystopian Japanese underworld of Chiba City, it imagines a global computer network in cyberspace called the ‘matrix’. Neal Stephenson’s Snow Crash (1992), which was especially popular among Facebook employees in the company’s early years, foresaw corporate overreach and virtual reality in an almost anarchic America. The state has withered away in California; everything has been privatised. Most people spend half their time in virtual reality, where their avatars have more fun than they themselves do in the real world. Meanwhile, flotillas of refugees approach via the Pacific. These cyberpunk Americas are much closer to the US in 2021 than the fascist dystopias of Lewis, Atwood or Roth.

Orwell and Huxley — have been outflanked when it comes to making sense of today’s totalitarian countries

Take China, which better resembles Yevgeny Zamyatin’s We: a book written in 1921, but suppressed by the Bolsheviks. It is set in a future ‘One State’ led by ‘the Benefactor’, where the ‘ciphers’ — who have numbers, not names, and wear standardised ‘unifs’ — are under constant surveillance. All apartments are made of glass, with curtains that can be drawn only when one is having state-licensed sex. Faced with insurrection, the omnipotent Benefactor orders the mass lobotomisation of ciphers, as the only way to preserve universal happiness is to abolish the imagination.

Chan Koonchung’s The Fat Years (2009) — which is banned in China. In this story, tap water is laced with drugs that render people docile, but at a cost. The month of February 2011 has been removed from public records and popular memory. This was when drastic emergency measures were introduced to stabilise the Chinese economy and assert China’s primacy in east Asia. Chan is one of a number of recent Chinese authors who have envisioned the decline of America, the corollary of China’s rise. The Fat Years is set in an imagined 2013, after a second western financial crisis makes China the world’s no. 1 economy.

Liu Cixin’s The Three-Body Problem (2006), a Chinese nanotechnology expert and a Beijing cop lead the global defence against an alien invasion that’s the fault of a misanthropic Chinese physicist.

I have some fond memories of my trips to the pre-collapse Soviet Union (I made four from 1983 to 1991). It was a weird and fascinating place. But it was also every inch the “evil empire” that President Ronald Reagan described, a place of fear and daily low-grade paranoia where any form of social attachment, whether religion or simple hobbies, was discouraged if it fell outside the control of the party-state.

the idea that anyone in Moscow would be stupid or deranged enough to want to reassemble the Soviet Union seemed to me a laughable fantasy. Even Putin himself—at least in public—often dismissed the idea.

I was wrong. I underestimated the power of Soviet imperial nostalgia. And so today, I grieve.

It was never designed, however, to function with one of its permanent members running amok as a nuclear-armed rogue state, and so today the front line of freedom is in Ukraine

I have lived through two eras, one an age of undeclared war between two ideological foes that threatened instant destruction, the next a time of increasing freedom and global integration. This second world was full of chaos, but it was also grounded in hope

I was convinced that everything I knew was more than likely destined to end in flames. Peace seemed impossible; war felt imminent.

Now I live in a new era, one in which the world order created in 1945 is collapsing.

The United Nations, as I once wrote, is a squalid and dysfunctional organization, but it is still one of the greatest achievements of humanity.

The Soviet collapse did not mean the end of war or of dictatorships, but after 1991, time seemed to be on the side of peace and democracy, if only we could summon the will and find the leadership to build on our heroic triumphs over Nazism and Communism.

But democracy is under attack everywhere, including here in the United States

I will celebrate the courage of Ukraine, the wisdom of NATO, and the steadfastness of the world’s democracies

But I also hear the quiet rustling of a shroud that is settling over the dreams—and perhaps, illusions—of a better world that for a moment seemed only inches from our grasp.

I do not know how this third era of my life will end, or if I will be alive to see it end. All I know is that I feel now as I did that night in Red Square, when I knew that democracy was in the fight of its life, that we might be facing a catastrophe, and that we must never waver.

I think that the age of the New Democrats, which was a very successful political project for the Democratic Party, has come to an end. The assumption of that politics, which began in earnest in the late 1980s and early 1990s, was that the Cold War had been settled, that democracy had prevailed, that the West was ascendant. But with China’s decision to take the route that they’ve gone on, with Russia now having waged this intense insurgency against the West, the assumption that that system is going to prevail in the world is now under question.

Rosenberg: Any honest assessment of the New Democrat project has to view it as wildly successful, because when I went to work for Clinton in 1992, Democrats had lost five out of the six previous presidential elections. And the central project of the New Democrats was to make the Democratic Party competitive at the presidential level again. Since then, we’ve won more votes in seven of eight presidential elections

I think that it’s birthing now for the United States a different era of politics, where we must be focused on two fundamental, existential questions. Can democracy prevail given the way that it’s being attacked from all sides? And can we prevent climate change from overwhelming the world that we know?

I want to try to write a book and to take the perspective of having been part of the beginning of the last big shift in American politics, the emergence of the New Democrats, and start imagining what’s going to come next for the center left in the United States and around the world.

Simon Rosenberg:

We’ve also seen three Democratic presidents that have served [since then]—Clinton, Barack Obama, and Joe Biden have also made the country materially better during their presidencies.

what’s the main lesson you take from his emergence?

Rosenberg: Yeah, it’s obviously disappointing. The emergence of what I call “Greater MAGA” has been a dark period in our history.

You have to recognize just how central to that is this narrative of the white tribe rallying around itself, and the sense of grievance, the sense of loss, the sense of decline. That’s what MAGA is. That’s all it is

We know from history, we know from other countries, when countries go into sectarian or tribal warfare, it can destroy a country, pull it apart. And Trump has created a domestic argument here that could potentially destroy the U.S. Look at Marjorie Taylor Greene this week—advocating for the country to split into two, red and blue.

Part of the reason I’m taking a step back from NDN is that I don’t think that we have yet figured out how to talk to the American people about the nature of the conflict we’re in right now, with rising authoritarianism around the world, the weakening of democratic institutions here and in other places.

My hope is that because Biden won’t be able to legislate very much for the next two years, he’ll spend his time talking to the American people and the West about the necessity of winning this conflict.

Rosenberg: The threat is still here. Look, I think [Florida Governor] Ron DeSantis is even more MAGA than Trump. This idea that in 2024, Republicans are going to end up with a moderate, center-right candidate and distance themselves from the insanity of the Trump years, that’s just fantasy talk.

DeSantis has decided to double down on extremism and on MAGA. We will learn in the next year and a half about how it all plays out. But I think he misread the room; he’s misread the moment in history. He needed to become an anti-Trump; instead, he became more Trump than Trump

In this last election, there were really two elections. There was a bluer election inside the battlegrounds, and there was a redder election outside the battlegrounds. We actually gained ground in seven battleground states: Arizona, Colorado, Georgia, Michigan, Minnesota, New Hampshire, and Pennsylvania. It’s an extraordinary achievement given high inflation, a low Biden approval rating, traditional midterm dynamics. My view is, that happened because the fear of MAGA has created a supercharged grass roots; our candidates are raising unprecedented amounts of money; we have more labor to work in these races than we’ve ever had before. And where we have these muscular campaigns, we were able to control the information environment. And also push turnout up through the roof.

But outside the battlegrounds, we fell back in New York and California, and in Florida and Texas, the four biggest states in the country. And the admonition to us is that we are still not competitive enough in the national daily discourse;

Republicans, because of this incredible noise machine that they built, are still far louder than we are. Democrats have to become obsessive about being more competitive in the daily political discourse in the country.

We have to build more media institutions. Republicans use ideological media to advance their politics in a way that we’ve never done. And we’re going to have to match that to some degree.

The second piece is that average Democratic activists have to recognize that they need to become information warriors daily

I think the way we have to think of the war room now, it’s 4 million proud patriots getting up every day, spending a little bit of their day putting good information into our daily discourse to try to crowd out the poisonous information and right-wing propaganda. There’s a lot that average citizens can do in this.

The key is to defeat MAGA in such a definitive and declarative way that Republicans move on to a different kind of politics and become something more like a traditional center-right political party.

We must stick together as a party because what will cause far-right political parties to succeed is when the prodemocracy coalition splits, and we can’t allow that to happen. As much as sometimes we want to have interfamily battles, those are self-indulgent at this point.

I don’t think that this emerging criticism is entirely wrong, but it’s only half right. The goal should be to expand, not to reposition. There are four areas that I think we have to bear down on in the next two years for a potential Democratic expansion: young voters, Latinos, Never-MAGA or -Trumpers, and young women, post-Dobbs.

The No. 1 job is we just need more young people voting, period. It’s more registration, more communications, targeting them more in our campaigns. In the Democratic Party, young people are still at the kids’ table; they have to become the center of our politics now.

I think that we’re favored in the presidential election. For us to win next year, the economy has to be good. And we have to look like we’ve been successful in Ukraine. Those two things are going to be paramount in him being able to say, “I’ve been a good president, and I may be a little bit old, but I still got 90 miles an hour on my fastball, and I’m able to get the job done right versus they’re still a little bit too crazy.”

What the Republicans should be worried about is we’ve had three consecutive elections where the battleground states have rejected MAGA. And so, if the Republicans present themselves as MAGA again, which looks almost inevitable, it’s going to be hard for them to win a presidential election in 2024 given that the battleground has muscle memory about MAGA and has voted now three times against it.

The western world kept a buzz going for twelve years, and that’s an accomplishment. It must also be said that the 1990s weren’t squandered, because even in the dark years they were fun. They weren’t complicated.

the 1990s make great nostalgia bait: simpler politics, plus great music, plus cool fashion cues. And maybe we can create another halcyon bubble again one day!

The generation that came of age in the 1990s, now well into middle age, have a lot of happy memories of a sort that may never be possible to have again. At the moment any possibility of collective joy seems about as realistic as a Miss America contestant trying to wish world peace into existence

n the 1990s we still had the future, a place that you could travel to, that would be cool when you got there, like Australia or the South Pole. Right now we merely have a future, and a murky one at that, and it’s probably more like Kenosha, Wisconsin than Sydney.

I remember doing a book tour and ending up on a local AM radio station’s podium at the grand opening of Mall of America in Bloomington, Minnesota on 11 August 1992. It was full of Americans in alpha consumption mode, eating ice cream, faces beaming, walking around in unselfconscious bliss. The local radio jock said to me, “You must think all of this is pretty silly”. He motioned towards the crowd and then to a rollercoaster directly beside us that came screeching at our heads every 95 seconds.

But I said, “No. In a century people are going to look back on right now as a sort of magic era, a charmed time of peace and prosperity and freedom from fear, as something that can never happen again, no matter how much they wish it would”.

On Thursday, rescuers said they had found engine components, part of a wing and other “important debris” as they searched the mountainside in a rural part of the Guangxi region for a fourth day.

Mr. Zhang, who was born in 1963, was one of China’s most experienced pilots,

A day earlier, the workers had found a black box, believed to be the cockpit voice recorder, which could provide investigators with crucial details. Officials said it was damaged but that its memory unit was relatively intact. The plane’s second black box, which records flight data, has yet to be recovered.

Their past performance was “very good,” Sun Shiying, the chairman of China Eastern Airlines’ Yunnan branch, said on Wednesday. When reached by phone, an airline representative declined to answer further questions about the crew.

At the main crash site, a state broadcaster showed the workers digging with shovels around a large piece of wreckage that the reporter described as a wing, which bore part of the China Eastern logo and was perched on a steep, barren slope fringed by dense thickets of now-flattened bamboo. Heavy rains had left the roads slick and inundated the earth with muddy pools.

Over his career as a commercial pilot with China Yunnan, which later merged with China Eastern, Mr. Zhang flew four different models of aircraft and accumulated 31,769 hours of flight experience.

The airline commonly paired young pilots with older pilots, and Mr. Zhang had mentored more than 100, CAAC News said. Mr. Yang was one of them.

Experts said that investigating the crash, which involved a sudden dive from cruising altitude in good weather, would require a close look at both the aircraft and the pilots, including the possibility that the plane was deliberately brought down. But they stressed that the cause was far from determined.

“Certainly an intentional downing is always a part of any investigation, and especially with this particular flight profile,” said Hassan Shahidi, chief executive of the Flight Safety Foundation, a nonprofit organization created after World War II to promote aviation safety. But he cautioned that it was “premature to jump onto any possibilities.”

“If the captain were intending to commit suicide, they’d have to overcome the other flight crew members,” Mr. Marks said.

he started receiving death threats. People said they wished he and his family had been killed by drug lords, told him that “sooner or later your punishment will arrive” and proposed that he be nailed into a coffin or run over by a cement roller.

Mr. Moreno, who grew up in Colombia, began working as a researcher in a computer science and robotics lab in Paris in 1983; the career that followed involved creating a start-up, meeting the Dalai Lama and being named a knight of the Légion d’Honneur. His work has won several awards and spanned many fields — automotive, medical, nuclear, military, even home goods.

Many of the recent threats have been directed at scientists studying Covid-19. In a survey of 321 such scientists who had given media interviews, the journal Nature found that 22 percent had received threats of physical or sexual violence and 15 percent had received death threats

Last year, an Austrian doctor who was a vocal supporter of vaccines and a repeated target of threats died by suicide.

increasingly, even professors and researchers without much of a public persona have faced intimidation from extremists and conspiracy theorists.

Around 2010, he started thinking about how technology could help create sustainable cities. Eventually, he refined his ideas about “human smart cities” and “living cities” into his 2016 proposal for 15-minute cities.

The idea owes much to its many predecessors: “neighborhood units” and “garden cities” in the early 1900s, the community-focused urban planning pioneered by the activist Jane Jacobs in the 1960s, even support for “new urbanism” and walkable cities in the 1990s. So-called low-traffic neighborhoods, or LTNs, have been set up in several British cities over the past few decades.

Critics of 15-minute cities have been outspoken, arguing that a concept developed in Europe may not translate well to highly segregated American cities. A Harvard economist wrote in a blog post for the London School of Economics and Political Science in 2021 that the concept was a “dead end” that would exacerbate “enormous inequalities in cities” by subdividing without connecting them.

Jordan Peterson, a Canadian psychologist with four million Twitter followers, suggested that 15-minute cities were “perhaps the worst imaginable perversion” of the idea of walkable neighborhoods. He linked to a post about the “Great Reset,” an economic recovery plan proposed by the World Economic Forum that has spawned hordes of rumors about a pandemic-fueled plot to destroy capitalism.

A member of Britain’s Parliament said that 15-minute cities were “an international socialist concept” that would “cost us our personal freedoms.” QAnon supporters said the derailment of a train carrying hazardous chemicals in Ohio was an intentional move meant to push rural residents into 15-minute cities.

“Conspiracy-mongers have built a complete story: climate denialism, Covid-19, anti-vax, 5G controlling the brains of citizens, and the 15-minute city for introducing a perimeter for day-to-day life,” Mr. Moreno said. “This storytelling is totally insane, totally irrational for us, but it makes sense for them.”

The multipronged conspiracy theory quickly became “turbocharged” after the Oxford protest, said Jennie King, head of climate research and policy at the Institute for Strategic Dialogue, a think tank that studies online platforms.

“You have this snowball effect of a policy, which in principle was only going to affect a small urban population, getting extrapolated and becoming this crucible where far-right groups, industry-sponsored lobbying groups, conspiracist movements, anti-lockdown groups and more saw an opportunity to insert their worldview into the mainstream and to piggyback on the news cycle,”

The vitriol currently directed at Mr. Moreno and researchers like him mirrors “the broader erosion of trust in experts and institutions,”

Modern conspiracy theorists and extremists turn the people they disagree with into scapegoats for a vast array of societal ills, blaming them personally for causing the high cost of living or various health crises and creating an “us-versus-them” environment, she said.

“I am not a politician, I am not a candidate for anything — as a researcher, my duty is to explore and deepen my ideas with scientific methodology,” he said. “It is totally unbelievable that we could receive a death threat just for working as scientists.”

Mr. Khamenei’s ruling philosophy has been shaped and reinforced by three notable authoritarian collapses: The 1979 fall of Iran’s monarchy, the 1991 dissolution of the Soviet Union and the Arab uprisings of 2011. His takeaway from each of these events has been to never compromise under pressure and never compromise on principles.

The Iranian regime’s repressive capacity — at least on paper — remains formidable. Ayatollah Khamenei is commander in chief of 190,000 armed members of the Islamic Revolutionary Guard Corps, who oversee tens of thousands of Basij militants tasked with instilling public fear and morality.

Iran’s nonideological conscription army, whose active forces are an estimated 350,000, is unlikely to take part in mass repression

Until now, the political and financial interests of Ayatollah Khamenei and the Revolutionary Guards have been intertwined. But persistent protests and chants of “Death to Khamenei” might change that

The sociologist Charles Kurzman wrote in his seminal book, “The Unthinkable Revolution in Iran,” that the paradox of revolutionary movements is that they are not viable until they attract a critical mass of supporters but that to attract a critical mass of supporters, they must be perceived as viable.

If the organizing principle that united Iran’s disparate opposition forces in 1979 was anti-imperialism, the organizing principles of today’s socioeconomically and ethnically diverse movement are pluralism and patriotism.

The faces of this movement are not ideologues or intellectuals but athletes, musicians and ordinary people, especially women and ethnic minorities, who have shown uncommon courage. Their slogans are patriotic and progressive — “We will not leave Iran, we will reclaim Iran,” and “Women, life, freedom.”

The demands of the current movement are brilliantly distilled in Shervin Hajipour’s song “Baraye,” or “For,” which has become the anthem of the protests and articulates a “yearning for a normal life” rather than the “forced paradise” of a religious police state.

Abbas Amanat, a historian of Iran, observed that one of the keys to Iran’s civilizational longevity, which dates to the Persian Empire of 2,500 years ago, is the power of its culture to co-opt its military invaders. “For nearly two millenniums, Persian political culture and, in a broader sense, a repository of Persian civilizational tools successfully managed to convert Turkic, Arab and Mongolian conquerors,” he told me. “Persian language, myth, historical memories and timekeeping endured. Iranians persuaded invaders to appreciate a Persian high culture of poetry, food, painting, wine, music, festivals and etiquette.”

When Ayatollah Khomeini acquired power in 1979, he led a cultural revolution that sought to replace Iranian patriotism with a purely Islamic identity. Ayatollah Khamenei continues that tradition, but he is one of the few remaining true believers. While the Islamic Republic sought to subdue Iranian culture, it is Iranian culture and patriotism that are threatening to undo the Islamic Republic.

Four decades of the Islamic Republic’s hard power will ultimately be defeated by two millenniums of Iranian cultural soft power. The question is no longer about whether this will happen but when.

Our minds are asymmetric judges, applying harsher moral judgment to present and future transgressions than past ones. It is as if the past becomes blurry. We even tend to blame the victim of a past event more than we blame the victim of a future one.

Third, our minds struggle with the negative emotions that our country’s complicated past gives rise to.

Research shows we are drawn to a sentimental form of history—nostalgia—which leads us to feel more loved, more protected, and even more competent in our ability to start and maintain relationships.

Nostalgia is often tied to the identities that we care most deeply about, such as our family or national identity. And, nostalgia is big business—in fashion, advertising, music and tourism, among other things.

Second, our minds tend to overplay sweet memories that favor our ancestors from the past.

Our minds resist the paradoxes that characterize our country’s past. It’s so much less psychologically painful to pick one path than to grapple with both ideas at the same time.

Fourth, our minds want to pick either a beautiful or a brutal narrative.

Contradictions, though, pocket our history, beginning with forefathers who had an extraordinary vision of equality, and simultaneously enslaved other humans

When we learn about historical atrocities, particularly ones that expose our limited knowledge, contradict the narratives we believe, or implicate our own ancestors, we might experience shame, guilt, disbelief or anger. In response, we have a natural desire to pull away from the new knowledge and perhaps even refute it, rather than try to better understand it.

Tools to useWhile the past is in the past, we can address the psychological challenge, however formidable, in the present. We have tools that will help, and I anticipate (and hope) that our debates will take on more psychological nuance as we shift from arguments over whether to explore our history more fully to how to do it.

For example, research shows the importance of returning to our values again and again as a way of inoculating us from setbacks

The daily arguments over curfews or messy rooms or study habits can cause us to shut down (“Do whatever you want”) or double down (“I’m your parent and you’ll do what I say”). Instead, it’s helpful to remind ourselves and our children that a parent has three jobs—to teach them, to protect them and to love them. Just doing that can ground us, and enable us to stay engaged, resilient and calm.

Similarly, when we confront a historical event, it can help to reflect on questions like, “Which American ideals do you most value?” and, “How do you hope others see your country?

You can even write out your responses, share them with others, and reread what you have written. Think of it as a values booster shot

Say, for instance, that you deeply value freedom. Keeping this value in your thoughts can help you notice the ways in which this country has delivered on the promise of freedom in important ways. But it also enables you to consider the disheartening realizations when those freedoms are not upheld.

esearch by Wendy Smith and others shows that we are capable of embracing paradox, rather than rejecting it. It doesn’t always come naturally. But we simply need to give ourselves permission to allow multiple truths to coexist.

In a paradox mind-set, we allow both of these things to be true. When both are true, we can challenge our either/or assumptions, and be more creative in finding solutions.

When you spot the paradox, allow both things to be true and observe if your mind shifts from solving the unsolvable puzzle (reconciling how can both of these things be true) to more deeply processing the knowledge that you may otherwise have pushed away. This is the greater resilience and creativity that comes with a paradox mind-set.

We simply need to accept that the formidable challenge will require us to be intentional in our approach.

In doing so, we become what I call “gritty patriots.” Psychologist Angela Duckworth defines grit as “passion and perseverance in pursuit of a meaningful, long-term goal.” Love of country is not something we are entitled to; it is something we work toward, with grit.

The 2024 election will not be the usual battle between parties, platforms and policies. It is a battle between those who fundamentally respect and abide by the ground rules of democracy and those who do not.

To underline his case most forcefully, Mr. Biden didn’t need to use his own words. He could rely on the words of his opponent: revenge, retribution, fight like hell, terminate the Constitution, suckers and losers, vermin, poisoning the blood of our country, dictator on Day 1, American carnage. There is no subtext here; it’s all text. As Mr. Biden put it, “We all know who Donald Trump is.”

And yet, apparently, we need to keep reminding ourselves. Otherwise, we fall into the trap of normalization that Mr. Trump laid from the start.

Today he can call for the execution of the chairman of the Joint Chiefs of Staff, or tell the Biden administration to “rot in hell,” or promote a video claiming he is literally a gift from God, and it gets less attention in both mainstream and social media than Mr. Biden tripping over a sandbag.

How did we end up here? Mr. Biden offered one compelling explanation: complacency. “We’ve been blessed so long with a strong, stable democracy, it’s easy to forget why so many before us risked their lives and strengthened democracy,

In that sense, democracy is like vaccines. Few people today have firsthand memories of the horrors of diseases that were rampant before vaccines largely eradicated them, which makes it easier for vaccine hesitancy to take root

Similarly, when a country has no history of living under a dictatorship, it can be easier to lose sight of what it means to live in a representative democracy, and to be caught flat-footed when a real authoritarian comes knocking.

The ordinary fixes—the kind that draw on people’s will, and require eating less and moving more—rarely have a large or lasting effect. Indeed, America itself has suffered through a long, maddening history of failed attempts to change its habits on a national scale: a yo-yo diet of well-intentioned treatments, policies, and other social interventions that only ever lead us back to where we started

Through it all, obesity rates keep going up; the diabetes epidemic keeps worsening.

The most recent miracle, for Barb as well as for the nation, has come in the form of injectable drugs. In early 2021, the Danish pharmaceutical company Novo Nordisk published a clinical trial showing remarkable results for semaglutide, now sold under the trade names Wegovy and Ozempic.

Patients in the study who’d had injections of the drug lost, on average, close to 15 percent of their body weight—more than had ever been achieved with any other drug in a study of that size. Wadden knew immediately that this would be “an incredible revolution in the treatment of obesity.”

Many more drugs are now racing through development: survodutide, pemvidutide, retatrutide. (Among specialists, that last one has produced the most excitement: An early trial found an average weight loss of 24 percent in one group of participants.

In the United States, an estimated 189 million adults are classified as having obesity or being overweight

The drugs don’t work for everyone. Their major side effects—nausea, vomiting, and diarrhea—can be too intense for many patients. Others don’t end up losing any weight

For the time being, just 25 percent of private insurers offer the relevant coverage, and the cost of treatment—about $1,000 a month—has been prohibitive for many Americans.

The drugs have already been approved not just for people with diabetes or obesity, but for anyone who has a BMI of more than 27 and an associated health condition, such as high blood pressure or cholesterol. By those criteria, more than 140 million American adults already qualify

if this story goes the way it’s gone for other “risk factor” drugs such as statins and antihypertensives, then the threshold for prescriptions will be lowered over time, inching further toward the weight range we now describe as “normal.”

How you view that prospect will depend on your attitudes about obesity, and your tolerance for risk

The first GLP-1 drug to receive FDA approval, exenatide, has been used as a diabetes treatment for more than 20 years. No long-term harms have been identified—but then again, that drug’s long-term effects have been studied carefully only across a span of seven years

the data so far look very good. “These are now being used, literally, in hundreds of thousands of people across the world,” she told me, and although some studies have suggested that GLP-1 drugs may cause inflammation of the pancreas, or even tumor growth, these concerns have not borne out.

adolescents are injecting newer versions of these drugs, and may continue to do so every week for 50 years or more. What might happen over all that time?

“All of us, in the back of our minds, always wonder, Will something show up?  ” Although no serious problems have yet emerged, she said, “you wonder, and you worry.”

in light of what we’ve been through, it’s hard to see what other choices still remain. For 40 years, we’ve tried to curb the spread of obesity and its related ailments, and for 40 years, we’ve failed. We don’t know how to fix the problem. We don’t even understand what’s really causing it. Now, again, we have a new approach. This time around, the fix had better work.

The fen-phen revolution arrived at a crucial turning point for Wadden’s field, and indeed for his career. By then he’d spent almost 15 years at the leading edge of research into dietary interventions, seeing how much weight a person might lose through careful cutting of their calories.

But that sort of diet science—and the diet culture that it helped support—had lately come into a state of ruin. Americans were fatter than they’d ever been, and they were giving up on losing weight. According to one industry group, the total number of dieters in the country declined by more than 25 percent from 1986 to 1991.

Rejecting diet culture became something of a feminist cause. “A growing number of women are joining in an anti-diet movement,” The New York Times reported in 1992. “They are forming support groups and ceasing to diet with a resolve similar to that of secretaries who 20 years ago stopped getting coffee for their bosses.

Now Wadden and other obesity researchers were reaching a consensus that behavioral interventions might produce in the very best scenario an average lasting weight loss of just 5 to 10 percent

National surveys completed in 1994 showed that the adult obesity rate had surged by more than half since 1980, while the proportion of children classified as overweight had doubled. The need for weight control in America had never seemed so great, even as the chances of achieving it were never perceived to be so small.

Wadden wasn’t terribly concerned, because no one in his study had reported any heart symptoms. But ultrasounds revealed that nearly one-third of them had some degree of leakage in their heart valves. His “cure for obesity” was in fact a source of harm.

In December 1994, the Times ran an editorial on what was understood to be a pivotal discovery: A genetic basis for obesity had finally been found. Researchers at Rockefeller University were investigating a molecule, later named leptin, that gets secreted from fat cells and travels to the brain, and that causes feelings of satiety. Lab mice with mutations in the leptin gene—importantly, a gene also found in humans—overeat until they’re three times the size of other mice. “The finding holds out the dazzling hope,”

In April 1996, the doctors recommended yes: Dexfenfluramine was approved—and became an instant blockbuster. Patients received prescriptions by the hundreds of thousands every month. Sketchy wellness clinics—call toll-free, 1-888-4FEN-FEN—helped meet demand. Then, as now, experts voiced concerns about access. Then, as now, they worried that people who didn’t really need the drugs were lining up to take them. By the end of the year, sales of “fen” alone had surpassed $300 million.

It was nothing less than an awakening, for doctors and their patients alike. Now a patient could be treated for excess weight in the same way they might be treated for diabetes or hypertension—with a drug they’d have to take for the rest of their life.

the article heralded a “new understanding of obesity as a chronic disease rather than a failure of willpower.”

News had just come out that, at the Mayo Clinic in Minnesota, two dozen women taking fen-phen—including six who were, like Barb, in their 30s—had developed cardiac conditions. A few had needed surgery, and on the operating table, doctors discovered that their heart valves were covered with a waxy plaque.