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BJP-associated Facebook groups also began to push the message that Hamas represented the same Muslim threat facing India in the troubled, majority-Muslim region of Kashmir and Palestinians were sweepingly branded as jihadis.

A turning point came in 1999 when India went to war with Pakistan and Israel proved willing to provide arms and ammunition. It was the beginning of a defence relationship that has grown exponentially. India buys about $2bn-worth of arms from Israel every year – its largest arms supplier after Russia – and accounts for 46% of Israel’s overall weapons exports.

it was the election of Modi that marked a fundamental sea change. While previous governments had kept their dealings with Israel largely quiet, due to concerns of alienating foreign allies and its own vast Muslim population, Modi’s Hindu nationalist BJP government had very different priorities.

ssa said: “The narrative they were pushing was clear: that India and Israel are these ancient civilisations that had been derailed by outsiders – which means Muslims – and their leaders have come together, like long-lost brothers, to fulfil their destiny.”

The ideological alignment between the two leaders was certainly more apparent than in the past. The BJP’s ideological forefathers, and its rank and file today, have long regarded Israel as a model for the religious nationalist state, referred to as the Hindu Rashtra, that the Hindu rightwing in India hope to establish.

While Modi was also the first Indian prime minister to visit Ramallah in Palestine, much of the focus of his government has been on strengthening ties with Israel, be it through defence, culture, agriculture and even film-making. This year, Gautam Adani, the Indian billionaire businessman seen to be close to Modi, paid $1.2bn to acquire the strategic Israeli port of Haifa.

Modi’s foreign policy has also overseen a transformation in ties with Arab Gulf countries including Saudi Arabia, the United Arab Emirates and Qatar, which has been of great financial benefit to India and laid the foundation for a groundbreaking India-Middle East economic trade corridor, running all the way to Europe, which was announced at the G20 forum for international economic cooperation this year but has yet to be built.

it’s also possible that population aging has something to do with it. There’s a pretty well-established literature linking youthful population bulges to elevated risk of conflict.

For example, Cincotta and Weber (2021) find that countries with a median age of 25 or less are much more likely to have revolutions:

Evidence from the 1990s reveals that countries where people aged fifteen to twenty-nine made up more than 40 percent of the adult population were twice as likely to suffer civil conflict.

Data collected from 1950 to 2000 found that countries where 35 percent or more of their adult populations comprised people aged fifteen to twenty-four were 150 percent more likely to experience an outbreak of civil conflict

, the young people crowd each other out, and this makes them mad. This effect is obviously exacerbated when the economy is stagnating. Also, simply having a lot of young men around without much to lose seems like a risk factor in and of itself.

Whether rich or poor, the countries in the Greater Middle East — I’ll throw Afghanistan and Pakistan into the mix, since they’ve also been a big locus of conflict — just don’t tend to experience much economic growth at all.

But the good news here, at least from a conflict-avoidance perspective, is that these countries are getting steadily older. There are a number of countries in the region where median age has already passed the 25-year mark:

how much things have changed

When Iran threw hundreds of thousands of soldiers against Iraq in “human wave” attacks in the 1980s, the median Iranian was just 17 years old; now, the median Iranian is in their early 30s.

Saudi Arabia got involved in the Yemen war, but was reluctant to send ground troops against the Houthis — possibly because the Houthis are formidable, but possibly because the Saudis have relatively few young people to send.

Hezbollah resides in a considerably older country than in 2006 when they attacked Israe

On the other hand, there are a number of other countries in the region that are still pretty young:

troublingly, Afghanistan, Yemen, Palestine, Iraq, and Pakistan are projected to still be below a median age of 25 a decade from now.

all of these countries are still aging at a steady clip — as are the countries that are already over 25. The fundamental reason is the big collapse in fertility rates in the Greater Middle East (and across the broader Muslim world) over the past few decades.

When Iran exploded in revolution and fought a titanic war against Iraq in the late 70s and 80s, its fertility was over 6; now it’s down to about 1.5

When the U.S. invaded Afghanistan in 2001, its fertility was over 7; now, it’s below 4

I don’t want to claim that “demography is destiny” here, and it’s all too easy to look at individual countries and tell just-so stories about how aging and fertility might have affected their conflict

The old Middle East, with massive crowds of angry young people thronging the streets, ready to explode into nationalist or sectarian or revolutionary violence, is steadily disappearing, being replaced by a more sedate, aging society. Given the horrific outcomes of the last few decades, it’s hard not to see that as a good thing.

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.

Nor can a university with a commitment to academic freedom prohibit all calls for political violence. That would require it to punish, say, students who express support for the invasion of Gaza knowing that it must result in the deaths of thousands of civilians. Thus Gay was correct in saying that students’ political slogans are not punishable by Harvard’s rules on harassment and bullying unless they cross over into intimidation, personal threats, or direct incitement of violence.

Gay was correct yet again in replying to Stefanik’s insistent demand, “What action has been taken against students who are harassing Jews on campus?” by noting that no action can be taken until an investigation has been completed. Harvard should not mete out summary justice like the Queen of Hearts in “Alice in Wonderland”: Sentence first, verdict afterward.

The real problem with Gay’s testimony was that she could not clearly and credibly invoke those principles because they either have never been explicitly adopted by Harvard or they have been flagrantly flouted in the past (as Stefanik was quick to point out)

Harvard has persecuted scholars who said there are two sexes, or who signed an amicus brief taking the conservative side in a Supreme Court deliberation. It has retracted acceptances from students who were outed by jealous peers for having used racist trash talk on social media when they were teens. Harvard’s subzero FIRE rating reveals many other punishments of politically incorrect peccadillos.

Institutional neutrality. A university does not need a foreign policy, and it does not need to issue pronouncements on the controversies and events of the day. It is a forum for debate, not a protagonist in debates. When a university takes a public stand, it either puts words in the mouths of faculty and students who can speak for themselves or unfairly pits them against their own employer.

In the wake of this debacle, the natural defense mechanism of a modern university is to expand the category of forbidden speech to include antisemitism (and as night follows day, Islamophobia). Bad idea

Deplorable speech should be refuted, not criminalized. Outlawing hate speech would only result in students calling anything they didn’t want to hear “hate speech.” Even the apparent no-brainer of prohibiting calls for genocide would backfire. Trans activists would say that opponents of transgender women in women’s sports were advocating genocide, and Palestinian activists would use the ban to keep Israeli officials from speaking on campus.

For universities to have a leg to stand on when they try to stand on principle, they must embark on a long-term plan to undo the damage they have inflicted on themselves. This requires five commitments.

Free speech. Universities should adopt a clear and conspicuous policy on academic freedom. It might start with the First Amendment, which binds public universities and which has been refined over the decades with carefully justified exceptions.

Since universities are institutions with a mission of research and education, they are also entitled to controls on speech that are necessary to fulfill that mission. These include standards of quality and relevance: You can’t teach anything you want at Harvard, just like you can’t publish anything you want in The Boston Globe. And it includes an environment conducive to learning.

So for the president of Harvard to suddenly come out as a born-again free-speech absolutist, disapproving of what genocidaires say but defending to the death their right to say it, struck onlookers as disingenuous or worse.

The events of this autumn also show that university pronouncements are an invitation to rancor and distraction. Inevitably there will be constituencies who feel a statement is too strong, too weak, too late, or wrongheaded.

Nonviolence.

Universities should not indulge acts of vandalism, trespassing, and extortion. Free speech does not include a heckler’s veto, which blocks the speech of others. These goon tactics also violate the deepest value of a university, which is that opinions are advanced by reason and persuasion, not by force

Viewpoint diversity. Universities have become intellectual and political monocultures. Seventy-seven percent of the professors in Harvard’s Faculty of Arts and Sciences describe themselves as liberal, and fewer than 3 percent as conservative. Many university programs have been monopolized by extreme ideologies, such as the conspiracy theory that the world’s problems are the deliberate designs of a white heterosexual male colonialist oppressor class.

Vast regions in the landscape of ideas are no-go zones, and dissenting ideas are greeted with incomprehension, outrage, and censorship.

The entrenchment of dogma is a hazard of policies that hire and promote on the say-so of faculty backed by peer evaluations. Though intended to protect departments from outside interference, the policies can devolve into a network of like-minded cronies conferring prestige on each other. Universities should incentivize departments to diversify their ideologies, and they should find ways of opening up their programs to sanity checks from the world outside.

Disempowering DEI. Many of the assaults on academic freedom (not to mention common sense) come from a burgeoning bureaucracy that calls itself diversity, equity, and inclusion while enforcing a uniformity of opinion, a hierarchy of victim groups, and the exclusion of freethinkers. Often hastily appointed by deans as expiation for some gaffe or outrage, these officers stealthily implement policies that were never approved in faculty deliberations or by university leaders willing to take responsibility for them.

An infamous example is the freshman training sessions that terrify students with warnings of all the ways they can be racist (such as asking, “Where are you from?”). Another is the mandatory diversity statements for job applicants, which purge the next generation of scholars of anyone who isn’t a woke ideologue or a skilled liar. And since overt bigotry is in fact rare in elite universities, bureaucrats whose job depends on rooting out instances of it are incentivized to hone their Rorschach skills to discern ever-more-subtle forms of “systemic” or “implicit” bias.

Universities should stanch the flood of DEI officials, expose their policies to the light of day, and repeal the ones that cannot be publicly justified.

A fivefold way of free speech, institutional neutrality, nonviolence, viewpoint diversity, and DEI disempowerment will not be a quick fix for universities. But it’s necessary to reverse their tanking credibility and better than the alternatives of firing the coach or deepening the hole they have dug for themselves.

(A study of sixty-seven civil wars published in the Journal of Peace Studies in 2021 found no evidence that ceasefires and prisoner releases led to sustainable peace agreements.)

Because of Israel’s deep alliance with this country, its wars run on a timer: When will the U.S. conclude that its interests, and Israel’s, require that hostilities end? After the atrocities of October 7th, the Israel Defense Forces launched an unprecedented retaliation and, because of the predictable killing and immiseration of innocents which followed, effectively shortened the time that the Biden Administration and European allies were likely to offer unqualified support.

there is no way for the I.D.F. to fight what amounts to a war of attrition without killing many more noncombatants

In any event, Israel cannot “destroy” or “eliminate” Hamas anytime soon. With international diplomatic support, however, it might be able to disarm, suppress, and further delegitimatize the group

Doing so would require the committed help of those powerful Arab states, such as Egypt and Saudi Arabia, whose leaders fear and despise the Islamist ideology that Hamas espouses.

Durable Israeli security cannot be achieved without Palestinian sovereignty. The alternative to re-starting the difficult work toward a sustainable deal is violence with no end in sight. ♦

“The main purpose is to send a clear message to the West that future seizures of oil tankers will be met with a response in kind,” said Sina Azodi, an Iran analyst at the Atlantic Council in Washington.

Iranian news media said the two vessels had an estimated combined capacity to carry 1.8 million barrels of oil and that their cargo was now in Iran’s possession.

Iran has a history of the retaliatory seizing of oil tankers in the Persian Gulf and the Strait of Hormuz in response to ships carrying its oil being stopped or confiscated. But the incident on Friday marked the first time in months that a foreign-flagged vessel was targeted by Iran.

The shadow war between Iran and Israel has also played out in the waters of the Persian Gulf, with the West accusing Iran of a drone attack on an Israeli-affiliated tanker that killed two European crew members in 2021. Iran denied it had a role in the attack

The system is designed to help students get along with one another, said Dee Mostofi, a Stanford spokeswoman. “The process aims to promote a climate of respect, helping build understanding that much speech is protected while also offering resources and support to students who believe they have experienced harm based on a protected identity,” she said.

The Stanford faculty’s effort is part of broader pushback against bias-reporting systems around the country. About half of college campuses have one—more than twice as many as five years ago—according to a 2022 survey by Speech First, a conservative nonprofit.

Prof. Santiago said he is wary that anonymous complaints could be exaggerated or used to attack someone. He helped collect 77 faculty signatures to petition the school to investigate free speech and academic freedom on campus, the first step to getting rid of the anonymous-reporting system. 

The system defaults to anonymous reporting and most students file that way. They use an online form to describe how the bias was demonstrated, which triggers an inquiry within 48 hours. Both parties are contacted.

Participation in the inquiry is voluntary. But it may not feel that way to accused students, said Juan Santiago, a professor of mechanical engineering who favors getting rid of the system.

“If you’re an 18-year-old freshman and you get contacted by an administrator and told you’ve been accused of some transgression, what are you going to do?” Prof. Santiago said. “They may not call that punitive but that can be very stressful.”

At Stanford, students can report a “Protected Identity Harm Incident,” which is defined as conduct targeting an individual or group on the basis of characteristics including race or sexual orientation. The system is meant to “build and maintain a better, safer, and more respectful campus community,” according to the school’s website.

Senior Christian Sanchez, executive vice president of the Associated Students of Stanford University, the student-government group, said the system is necessary and important. Mr. Sanchez, who describes himself as Chicano, said he has bristled in the past when another student has addressed him as “G,” short for gangster.

He has let it roll off his back, he said, but less thick-skinned students should have a path for redress.

he reports are stored in a platform operated by a third party called Maxient, a Charlottesville, Va.-based company that has contracts with 1,300 schools—mostly colleges and universities in the U.S

Only Maxient and a small number of people within the student affairs office have access to the records, said Ms. Mostofi. She declined to say how long they are stored.

A dashboard maintained by the school lists a few incidents students have reported using the anonymous system, including the removal of an Israeli flag and a racial slur written on a whiteboard hanging on a dorm-room door.

At the University of California, which includes 10 campuses, the reporting system collected 457 acts of “intolerance or hate” during the 2021-22 school year. Of those, 296 were defined as offensive speech. The UC said those incidents include “gestures, taunts, mockery, unwanted jokes or teasing, and derogatory or disparaging comments of a biased nature.”

Free-speech advocacy organizations including the Goldwater Institute, the Foundation for Individual Rights and Expression and Alumni Free Speech Alliance have advocated against bias-reporting mechanisms.

After Speech First challenged bias-response systems at the University of Texas, the University of Michigan and the University of Central Florida, all three schools changed or disbanded their systems.

Stanford Business School professor Ivan Marinovic said the bias-reporting system reminded him of the way citizens were encouraged to inform on one another by governments in the Soviet Union, East Germany and China. 

“It ignores the whole history,” he said. “You’re basically going to be reporting people who you find offensive, right? According to your own ideology.”

it is easy to forget how much we have in common as people. I can’t think of any major nation after the United States with more of a Protestant work ethic and naturally capitalist population than China.

These days, it is extremely difficult for a visiting columnist to get anyone — a senior official or a Starbucks barista — to speak on the record. It was not that way a decade ago.

The Communist Party’s hold is also a product of all the hard work and savings of the Chinese people, which have enabled the party and the state to build world-class infrastructure and public goods that make life for China’s middle and lower classes steadily better.

Beijing and Shanghai, in particular, have become very livable cities, with the air pollution largely erased and lots of new, walkable green spaces.

some 900 cities and towns in China are now served by high-speed rail, which makes travel to even remote communities incredibly cheap, easy and comfortable

Just when trust has become more important than ever between the U.S. and China, it also has become scarcer than ever. Bad trend.

China’s stability is a product of both an increasingly pervasive police state and a government that has steadily raised standards of living. It’s a regime that takes both absolute control and relentless nation-building seriously.

For an American to fly from New York’s Kennedy Airport into Beijing Capital International Airport today is to fly from an overcrowded bus terminal to a Disney-like Tomorrowland.

China got an early jump on A.I. in two realms — facial recognition technology and health records — because there are virtually no privacy restrictions on the government’s ability to build huge data sets for machine learning algorithms to find patterns.

“ChatGPT is prompting some people to ask if the U.S. is rising again, like in the 1990s,”

“I understand your feeling: You have been in the first place for a century, and now China is rising, and we have the potential to become the first — and that is not easy for you,” Hu said to me. But “you should not try to stop China’s development. You can’t contain China in the end. We are quite smart. And very diligent. We work very hard. And we have 1.4 billion people.”

Before the Trump presidency, he added: “We never thought China-U.S. relations would ever become so bad. Now we gradually accept the situation, and most Chinese people think there is no hope for better relations. We think the relationship will be worse and worse and hope that war will not break out between our two countries.”

A lot of people hesitated when I asked. Indeed, many would answer with some version of “I’m not sure, I just know that it’s THEIR fault.”

t was repeated conversations like these that got me started asking American, Chinese and Taiwanese investors, analysts and officials a question that has been nagging at me for a while: What exactly are America and China fighting about?

the real answer is so much deeper and more complex than just the usual one-word response — “Taiwan” — or the usual three-word response — “autocracy versus democracy.”

Let me try to peel back the layers. The erosion in U.S.-China relations is a result of something old and obvious — a traditional great-power rivalry between an incumbent power (us) and a rising power (China) — but with lots of new twists

One of the twists, though, is that this standard-issue great-power rivalry is occurring between nations that have become as economically intertwined as the strands of a DNA molecule. As a result, neither China nor America has ever had a rival quite like the other.

in modern times, China, like America, has never had to deal with a true economic and military peer with which it was also totally intertwined through trade and investment.

Another new twist, and a reason it’s hard to define exactly what we’re fighting about, has a lot to do with how this elusive issue of trust and the absence of it have suddenly assumed much greater importance in international affairs.

This is a byproduct of our new technological ecosystem in which more and more devices and services that we both use and trade are driven by microchips and software, and connected through data centers in the cloud and high-speed internet

so many more things became “dual use.” That is, technologies that can easily be converted from civilian tools to military weapons, or vice versa.

no one country or company can own the whole supply chain. You need the best from everywhere, and that supply chain is so tightly intertwined that each company has to trust the others intimately.

when we install the ability to sense, digitize, connect, process, learn, share and act into more and more things — from your GPS-enabled phone to your car to your toaster to your favorite app — they all become dual use, either weapons or tools depending on who controls the software running them and who owns the data that they spin off.

As long as most of what China sold us was shallow goods, we did not care as much about its political system — doubly so because it seemed for a while as if China was slowly but steadily becoming more and more integrated with the world and slightly more open and transparent every year. So, it was both easy and convenient to set aside some of our worries about the dark sides of its political system.

when you want to sell us ‘deep goods’ — goods that are dual use and will go deep into our homes, bedrooms, industries, chatbots and urban infrastructure — we don’t have enough trust to buy them. So, we are going to ban Huawei and instead pay more to buy our 5G telecom systems from Scandinavian companies we do trust: Ericsson and Nokia.”

as we’ve seen in Ukraine, a smartphone can be used by Grandma to call the grandkids or to call a Ukrainian rocket-launching unit and give it the GPS coordinates of a Russian tank in her backyard.

So today, the country or countries that can make the fastest, most powerful and most energy efficient microchips can make the biggest A.I. computers and dominate in economics and military affairs.

As more and more products and services became digitized and electrified, the microchips that powered everything became the new oil. What crude oil was to powering 19th- and 20th-century economies, microchips are for powering 21st-century economies.

When you ask them what is the secret that enables TSMC to make 90 percent of the world’s most advanced logic chips — while China, which speaks the same language and shares the same recent cultural history, makes zero — their answer is simple: “trust.”

TSMC is a semiconductor foundry, meaning it takes the designs of the most advanced computer companies in the world — Apple, Qualcomm, Nvidia, AMD and others — and turns the designs into chips that perform different processing functions

TSMC makes two solemn oaths to its customers: TSMC will never compete against them by designing its own chips and it will never share the designs of one of its customers with another.

“Our business is to serve multiple competitive clients,” Kevin Zhang, senior vice president for business development at TSMC, explained to me. “We are committed not to compete with any of them, and internally our people who serve customer A will never leak their information to customer C.”

But by working with so many trusted partners, TSMC leverages the partners’ steadily more complex designs to make itself better — and the better it gets, the more advanced designs it can master for its customers. This not only requires incredibly tight collaboration between TSMC and its customers, but also between TSMC and its roughly 1,000 critical local and global suppliers.

As the physics of chip making gets more and more extreme, “the investment from customers is getting bigger and bigger, so they have to work with us more closely to make sure they harvest as much [computing power] as they can. They have to trust you.”

China also has a foundry, Semiconductor Manufacturing International Corporation, which is partly state-owned. But guess what? Because no global chip designers trust SMIC with their most advanced designs, it is at least a decade behind TSMC.

It’s for these reasons that the erosion in U.S.-China relations goes beyond our increasingly sharp disagreements over Taiwan. It is rooted in the fact that just when trust, and its absence, became much bigger factors in international affairs and commerce, China changed its trajectory. It made itself a less trusted partner right when the most important technology for the 21st century — semiconductors — required unprecedented degrees of trust to manufacture and more and more devices and services became deep and dual use.

when American trade officials said: “Hey, you need to live up to your W.T.O. commitments to restrict state-funding of industries,” China basically said: “Why should we live by your interpretation of the rules? We are now big enough to make our own interpretations. We’re too big; you’re too late.”

Combined with China’s failure to come clean on what it knew about the origins of Covid-19, its crackdown on democratic freedoms in Hong Kong and on the Uyghur Muslim minority in Xinjiang, its aggressive moves to lay claim to the South China Sea, its increasing saber rattling toward Taiwan, its cozying up to Vladimir Putin (despite his savaging of Ukraine), Xi’s moves toward making himself president for life, his kneecapping of China’s own tech entrepreneurs, his tighter restrictions on speech and the occasional abduction of a leading Chinese businessman — all of these added up to one very big thing: Whatever trust that China had built up with the West since the late 1970s evaporated at the exact moment in history when trust, and shared values, became more important than ever in a world of deep, dual-use products driven by software, connectivity and microchips.

it started to matter a lot more to Western nations generally and the United States in particular that this rising power — which we were now selling to or buying from all sorts of dual-use digital devices or apps — was authoritarian.

eijing, for its part, argues that as China became a stronger global competitor to America — in deep goods like Huawei 5G — the United States simply could not handle it and decided to use its control over advanced semiconductor manufacturing and other high-tech exports from America, as well as from our allies, to ensure China always remained in our rearview mirror

Beijing came up with a new strategy, called “dual circulation.” It said: We will use state-led investments to make everything we possibly can at home, to become independent of the world. And we will use our manufacturing prowess to make the world dependent on our exports.

Chinese officials also argue that a lot of American politicians — led by Trump but echoed by many in Congress — suddenly seemed to find it very convenient to put the blame for economic troubles in the U.S.’s middle class not on any educational deficiencies, or a poor work ethic, or automation or the 2008 looting by financial elites, and the crisis that followed, but on China’s exports to the United States.

As Beijing sees it, China not only became America’s go-to boogeyman, but in their frenzy to blame Beijing for everything, members of Congress started to more recklessly promote Taiwan’s independence.

Xi told President Biden at their summit in Bali in November, in essence: I will not be the president of China who loses Taiwan. If you force my hand, there will be war. You don’t understand how important this is to the Chinese people. You’re playing with fire.

at some level Chinese officials now understand that, as a result of their own aggressive actions in recent years on all the fronts I’ve listed, they have frightened both the world and their own innovators at precisely the wrong time.

I don’t buy the argument that we are destined for war. I believe that we are doomed to compete with each other, doomed to cooperate with each other and doomed to find some way to balance the two. Otherwise we are both going to have a very bad 21st century.

I have to say, though, Americans and Chinese remind me of Israelis and Palestinians in one respect: They are both expert at aggravating the other’s deepest insecurities.

China’s Communist Party is now convinced that America wants to bring it down, which some U.S. politicians are actually no longer shy about suggesting. So, Beijing is ready to crawl into bed with Putin, a war criminal, if that is what it takes to keep the Americans at bay.

Americans are now worried that Communist China, which got rich by taking advantage of a global market shaped by American rules, will use its newfound market power to unilaterally change those rules entirely to its advantage. So we’ve decided to focus our waning strength vis-à-vis Beijing on ensuring the Chinese will always be a decade behind us on microchips.

I don’t know what is sufficient to reverse these trends, but I think I know what is necessary.

If it is not the goal of U.S. foreign policy to topple the Communist regime in China, the United States needs to make that crystal clear, because I found a lot more people than ever before in Beijing think otherwise.

As for China, it can tell itself all it wants that it has not taken a U-turn in recent years. But no one is buying it. China will never realize its full potential — in a hyper-connected, digitized, deep, dual-use, semiconductor-powered world — unless it understands that establishing and maintaining trust is now the single most important competitive advantage any country or company can have. And Beijing is failing in that endeavor.

In his splendid biography of the great American statesman George Shultz, Philip Taubman quotes one of Shultz’s cardinal rules of diplomacy and life: “Trust is the coin of the realm.”

And if divestment against Israel is carried out, when should it end?

Oil and gas divesting is meant never to end; oil and gas consumption is meant to end. Divestment from South Africa ended with apartheid.

So university leaders will be forced to ask an often heterogeneous group of students what would earn Israel its social license back. A cease-fire? A new Israeli government? A two-state solution? The end of Israel as a Jewish state?

But even if an endowment could provide a list of every underlying investment, it would likely then be inundated for more calls to divest, for more discovered connections — however small — to Israel, and for reasons related to other offenses discoverable with an online search

The answer, of course, is that endowments can’t be in the moral adjudication business — and they should never have headed this way

This does not mean that investing should be a returns-at-any-cost exercise. But it does mean that the real world does not always provide objective answers to how to balance benefits and consequences of companies providing products and services:

Biden’s Department of Education has interpreted Title VI to apply when students “experience discrimination, including harassment,” on the basis of their “shared ancestry or ethnic characteristics.”

these statements — even if fairly rooted in the text of Title VI — are not a solution

Executive orders and administrative regulations are more ephemeral than federal statutes. The next president (or one elected in 2036 or 2052) may choose to interpret Title VI differently. Biden’s interpretation is broader than Trump’s, for example. Courts will also have their own say, and they are now less deferential to presidential interpretations of the law than they’ve been in decades.

The definitions don’t just implicate the First Amendment, they also breed confusion around the very concept of harassment itself. Hearing unpleasant or even hateful thoughts or ideas isn’t “harassment.”

The best parts of the Antisemitism Awareness Act explicitly incorporate discrimination based on “actual or perceived shared ancestry or ethnic characteristics” into federal statutory law, elevating the legal protections well beyond the executive orders and guidance letters of previous administrations.

If the law had stopped there — or even if it had gone further and explicitly stated that discrimination on the basis of actual or perceived Jewish identity is by definition discrimination on the basis of shared ancestry, then it would be a vital addition to federal law.

But the law did not stop there. It goes on to require schools to consider the International Holocaust Remembrance Alliance’s working definition of antisemitism when determining whether there has been a violation of Title VI

This is a serious mistake. The alliance’s definition includes examples of antisemitism that encompass a broad range of statements that are protected by the First Amendment.

Both the Trump and the Biden administrations attempted to solve the problem by interpreting Title VI to apply to antisemitism, at least in some circumstances. The Trump administration issued an executive order stating that “discrimination against Jews may give rise to a Title VI violation when the discrimination is based on an individual’s race, color or national origin.”

That’s an inescapable part of life in a free, pluralistic nation

Harassment is something else entirely.

In a 1999 case, Davis v. Monroe County Board of Education, the Supreme Court defined student-on-student harassment under Title IX (the federal statute prohibiting sex discrimination in federally funded education) as conduct “so severe, pervasive and objectively offensive, and that so undermines and detracts from the victims’ educational experience, that the victims are effectively denied equal access to an institution’s resources and opportunities.”

Harassment doesn’t depend so much on the content or viewpoint of the objectionable speech as where, when and how it happens.

If students chant, “Globalize the intifada,” at a lawful public protest, then that’s protected

If they shout down Jewish students in class using the same phrase, or chant it outside the dorm rooms of Jewish students at 3 a.m., then they’re engaging in harassment. Jewish students can’t study or sleep on an equal basis with other students.

In both of those circumstances, the actual content of the words is less important than the timing and the targets. A person can commit an act of antisemitic harassment if he targets Jewish students with words that have nothing to do with ancestry or ethnicity

For example, if someone stands outside a Jewish student’s room night after night yelling, “Michael Jordan is the GOAT” relentlessly so that the student can’t sleep or targets her Jewish roommate with constant interruption and distraction then she’s engaging in antisemitic harassment not because of the content or viewpoint of the words, but rather because of the identity of the target and the time and manner of the speech.

I’d like to humbly offer a better way. Strip the problematic incorporation of the alliance’s antisemitism definition and examples from the bill entirely. Instead, simply amend Title VI itself to make it explicit that discrimination based on “actual or perceived shared ancestry or ethnic characteristics” is prohibited by the statute and that antisemitic discrimination meets that definition.

by revising Title VI to clearly prohibit discrimination against Jews without any further amplification or definition, antisemitic harassment will fit neatly into existing case law that has longed harmonized free speech principles and nondiscrimination law

The alarm is growing louder, but the German public remains unconvinced that the security of Germany and Europe has been fundamentally threatened by a newly aggressive Russia.

Mr. Pistorius’s status as one of the country’s most popular politicians has given him a freedom to speak that others — including his boss, Chancellor Olaf Scholz — do not enjoy.

The prospect of a re-elected Mr. Trump has German officials and many of their fellow NATO counterparts informally discussing whether the nearly 75-year-old alliance structure they are planning to celebrate in Washington this year can survive without the United States at its center. Many German officials say that Mr. Putin’s best strategic hope is NATO’s fracture.

Only a year ago NATO was celebrating a new sense of purpose and a new unity, and many were confidently predicting Mr. Putin was on the run.

now, with an undependable America, an aggressive Russia and a striving China, as well as a seemingly stalemated war in Ukraine and a deeply unpopular conflict in Gaza, German officials are beginning to talk about the emergence of a new, complicated and troubling world, with severe consequences for European and trans-Atlantic security.

some of Mr. Pistorius’s colleagues are warning that if American funding dries up and Russia prevails, its next target will be closer to Berlin.

“If Ukraine were forced to surrender, that would not satisfy Russia’s hunger for power,” the chief of Germany’s intelligence service, Bruno Kahl, said last week. “If the West does not demonstrate a clear readiness to defend, Putin will have no reason not to attack NATO anymore.”

In the decades since the Soviet Union collapsed, most Germans have grown accustomed to the notions that the country’s security would be assured if it worked with Russia, not against it, and that China is a necessary partner with a critical market for German automobiles and equipment.

Mr. Scholz, a Social Democrat whose party traditionally sought decent ties with Moscow, seems reluctant to discuss the far more confrontational future with Russia or China that German defense and intelligence chiefs describe so vividly.

few politicians will take on the subject in public. Mr. Scholz is especially careful, tending to Germany’s relationship with the United States and wary of pushing Russia and its unpredictable president too hard.

Mr. Scholz has moved with great caution. He has opposed — along with Mr. Biden — setting a timetable for Ukraine’s eventual entry into the alliance

The most vivid example of his caution is his continued refusal to provide Ukraine a long-range, air-launched cruise missile called the Taurus.

The Taurus has a range of more than 300 miles, meaning Ukraine could use it to strike deep into Russia. And Mr. Scholz is not willing to take that chance — nor is the country’s Bundestag, which voted against a resolution calling for the transfer. While the decision seems to fit German opinion, Mr. Scholz wants to avoid the subject.

Polls show that Germans want to see a more capable German military. But only 38 percent of those surveyed said they wanted their country to be more involved in international crises, the lowest figure since that question began to be asked in 2017, according to the Körber Foundation, which conducted the survey. Of that group, 76 percent said the engagement should be primarily diplomatic, and 71 percent were against a military leadership role for Germany in Europe.

German military officials recently set off a small outcry when they suggested that the country must be “kriegstüchtig,” which roughly translates to the ability to fight and win a war.

Norbert Röttgen, an opposition legislator and a foreign policy expert with the Christian Democrats, said the term was regarded as “rhetorical overreach” and quickly dropped.

“Scholz has always said that ‘Ukraine must not lose but Russia must not win,’ which indicated that he’s always thought of an impasse that would lead to a diplomatic process,” Mr. Röttgen said. “He thinks of Russia as more important than all the countries between us and them, and he lacks a European sense and of his possible role as a European leader.”

Mr. Scholz clearly feels most comfortable relying heavily on Washington, and senior German officials say he especially mistrusts Emmanuel Macron, the president of France, who has argued for European “strategic autonomy.” Mr. Macron has found few followers on the continent.

Even Mr. Scholz’s main European defense initiative, a coordinated ground-based air defense against ballistic missiles known as Sky Shield, depends on a mix of American, American-Israeli and German missile systems.

Mr. Scholz’s ambitions are also hamstrung by his increasingly weak economy. It shrank 0.3 percent last year, and roughly the same is expected in 2024. The cost of the Ukraine war and China’s economic problems — which have hit the auto and manufacturing sectors hardest — have exacerbated the problem.

While Mr. Scholz acknowledges that the world has changed, “he is not saying that we must change with it,” said Ulrich Speck, a German analyst.

“He is saying that the world has changed and that we will protect you,”

Germans, and even the Social Democrats, “have come to the realization that Germany lives in the real world and that hard power matters,”

“At the same time,” he said, “there’s still this hope that this is all just a bad dream, and Germans will wake up and be back in the old world.”

Two sources said that during the early weeks of the war they were permitted to kill 15 or 20 civilians during airstrikes on low-ranking militants. Attacks on such targets were typically carried out using unguided munitions known as “dumb bombs”, the sources said, destroying entire homes and killing all their occupants.

“You don’t want to waste expensive bombs on unimportant people – it’s very expensive for the country and there’s a shortage [of those bombs],” one intelligence officer said. Another said the principal question they were faced with was whether the “collateral damage” to civilians allowed for an attack.

“Because we usually carried out the attacks with dumb bombs, and that meant literally dropping the whole house on its occupants. But even if an attack is averted, you don’t care – you immediately move on to the next target. Because of the system, the targets never end. You have another 36,000 waiting.”

ccording to conflict experts, if Israel has been using dumb bombs to flatten the homes of thousands of Palestinians who were linked, with the assistance of AI, to militant groups in Gaza, that could help explain the shockingly high death toll in the war.

Details about the specific kinds of data used to train Lavender’s algorithm, or how the programme reached its conclusions, are not included in the accounts published by +972 or Local Call. However, the sources said that during the first few weeks of the war, Unit 8200 refined Lavender’s algorithm and tweaked its search parameters.

Responding to the publication of the testimonies in +972 and Local Call, the IDF said in a statement that its operations were carried out in accordance with the rules of proportionality under international law. It said dumb bombs are “standard weaponry” that are used by IDF pilots in a manner that ensures “a high level of precision”.

“The IDF does not use an artificial intelligence system that identifies terrorist operatives or tries to predict whether a person is a terrorist,” it added. “Information systems are merely tools for analysts in the target identification process.”

In earlier military operations conducted by the IDF, producing human targets was often a more labour-intensive process. Multiple sources who described target development in previous wars to the Guardian, said the decision to “incriminate” an individual, or identify them as a legitimate target, would be discussed and then signed off by a legal adviser.

n the weeks and months after 7 October, this model for approving strikes on human targets was dramatically accelerated, according to the sources. As the IDF’s bombardment of Gaza intensified, they said, commanders demanded a continuous pipeline of targets.

“We were constantly being pressured: ‘Bring us more targets.’ They really shouted at us,” said one intelligence officer. “We were told: now we have to fuck up Hamas, no matter what the cost. Whatever you can, you bomb.”

Lavender was developed by the Israel Defense Forces’ elite intelligence division, Unit 8200, which is comparable to the US’s National Security Agency or GCHQ in the UK.

After randomly sampling and cross-checking its predictions, the unit concluded Lavender had achieved a 90% accuracy rate, the sources said, leading the IDF to approve its sweeping use as a target recommendation tool.

Lavender created a database of tens of thousands of individuals who were marked as predominantly low-ranking members of Hamas’s military wing, they added. This was used alongside another AI-based decision support system, called the Gospel, which recommended buildings and structures as targets rather than individuals.

The accounts include first-hand testimony of how intelligence officers worked with Lavender and how the reach of its dragnet could be adjusted. “At its peak, the system managed to generate 37,000 people as potential human targets,” one of the sources said. “But the numbers changed all the time, because it depends on where you set the bar of what a Hamas operative is.”

broadly, and then the machine started bringing us all kinds of civil defence personnel, police officers, on whom it would be a shame to waste bombs. They help the Hamas government, but they don’t really endanger soldiers.”

Before the war, US and Israeli estimated membership of Hamas’s military wing at approximately 25-30,000 people.

there was a decision to treat Palestinian men linked to Hamas’s military wing as potential targets, regardless of their rank or importance.

According to +972 and Local Call, the IDF judged it permissible to kill more than 100 civilians in attacks on a top-ranking Hamas officials. “We had a calculation for how many [civilians could be killed] for the brigade commander, how many [civilians] for a battalion commander, and so on,” one source said.

Another source, who justified the use of Lavender to help identify low-ranking targets, said that “when it comes to a junior militant, you don’t want to invest manpower and time in it”. They said that in wartime there was insufficient time to carefully “incriminate every target”

So you’re willing to take the margin of error of using artificial intelligence, risking collateral damage and civilians dying, and risking attacking by mistake, and to live with it,” they added.

When it came to targeting low-ranking Hamas and PIJ suspects, they said, the preference was to attack when they were believed to be at home. “We were not interested in killing [Hamas] operatives only when they were in a military building or engaged in a military activity,” one said. “It’s much easier to bomb a family’s home. The system is built to look for them in these situations.”

Such a strategy risked higher numbers of civilian casualties, and the sources said the IDF imposed pre-authorised limits on the number of civilians it deemed acceptable to kill in a strike aimed at a single Hamas militant. The ratio was said to have changed over time, and varied according to the seniority of the target.

The IDF’s targeting processes in the most intensive phase of the bombardment were also relaxed, they said. “There was a completely permissive policy regarding the casualties of [bombing] operations,” one source said. “A policy so permissive that in my opinion it had an element of revenge.”

“There were regulations, but they were just very lenient,” another added. “We’ve killed people with collateral damage in the high double digits, if not low triple digits. These are things that haven’t happened before.” There appears to have been significant fluctuations in the figure that military commanders would tolerate at different stages of the war

One source said that the limit on permitted civilian casualties “went up and down” over time, and at one point was as low as five. During the first week of the conflict, the source said, permission was given to kill 15 non-combatants to take out junior militants in Gaza

at one stage earlier in the war they were authorised to kill up to “20 uninvolved civilians” for a single operative, regardless of their rank, military importance, or age.

“It’s not just that you can kill any person who is a Hamas soldier, which is clearly permitted and legitimate in terms of international law,” they said. “But they directly tell you: ‘You are allowed to kill them along with many civilians.’ … In practice, the proportionality criterion did not exist.”

Experts in international humanitarian law who spoke to the Guardian expressed alarm at accounts of the IDF accepting and pre-authorising collateral damage ratios as high as 20 civilians, particularly for lower-ranking militants. They said militaries must assess proportionality for each individual strike.

An international law expert at the US state department said they had “never remotely heard of a one to 15 ratio being deemed acceptable, especially for lower-level combatants. There’s a lot of leeway, but that strikes me as extreme”.

Sarah Harrison, a former lawyer at the US Department of Defense, now an analyst at Crisis Group, said: “While there may be certain occasions where 15 collateral civilian deaths could be proportionate, there are other times where it definitely wouldn’t be. You can’t just set a tolerable number for a category of targets and say that it’ll be lawfully proportionate in each case.”

Whatever the legal or moral justification for Israel’s bombing strategy, some of its intelligence officers appear now to be questioning the approach set by their commanders. “No one thought about what to do afterward, when the war is over, or how it will be possible to live in Gaza,” one said.

Another said that after the 7 October attacks by Hamas, the atmosphere in the IDF was “painful and vindictive”. “There was a dissonance: on the one hand, people here were frustrated that we were not attacking enough. On the other hand, you see at the end of the day that another thousand Gazans have died, most of them civilians.”