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

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

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

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

Hellscape

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

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

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

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

What does that mean for news? Nothing good.

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

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

Two big takeaways:

(1) Ad-supported publications will not survive

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

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

(2) Size is determinative.

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

Audiences were valuable; content was commoditized.

But everything in between? That’s a crapshoot.

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

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

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

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

Part of the answer, to be fair, is luck. Russia’s invasion of Ukraine caused a major energy shock in Europe, which had come to rely on imports of Russian natural gas. America, which exports gas, was much less affected.

What about inflation? When you use comparable measures, America also has the lowest inflation rate among major economies.

It’s true that one recent poll found that a majority of Americans and 60 percent of Republicans say that unemployment is near a 50-year high. But it’s actually near its lowest level since the 1960s.

A second, probably more important factor was that the United States pursued aggressively expansionary fiscal policy

Many economists were extremely critical, warning that this spending would fuel inflation, which it probably did for a while. But inflation has subsided, while “Big Fiscal” helped the economy get to full employment — arguably the first time we’ve had truly full employment in decades.

A strong job market may in turn have had major long-term benefits, by drawing previously marginalized Americans into the work force.

the percentage of U.S. adults in their prime working years participating in the labor force is now at its highest level in 20 years. One number I find especially striking is labor force participation by Americans with a disability, which has soared.

One last thing: When Covid struck, all advanced countries took strong measures to limit economic hardship, but they took different approaches. European governments generally paid employers to keep workers on their payrolls, even if they were temporarily idle. America, for the most part, let layoffs happen but protected workers with expanded unemployment benefits.

There was a case for each approach. Europe’s approach helped keep workers connected to their old jobs; the U.S. approach created more flexibility, making it easier for workers to move to different jobs if the post-Covid economy turned out to look quite different from the economy before the pandemic.

is clear: We have been remarkably successful, even if nobody will believe it.

If we don’t draw some lines now, legions of citizens could be manipulated, disenfranchised or lose faith in the whole system — opening doors to foreign adversaries who want to do the same. AI might break us in 2024.

“The ability of AI to interfere with our elections, to spread misinformation that’s extremely believable is one of the things that’s preoccupying us,” Schumer said, after watching me so easily create a deepfake of him. “Lots of people in the Congress are examining this.”

Of course, fibbing politicians are nothing new, but examples keep multiplying of how AI supercharges misinformation in ways we haven’t seen before. Two examples: The presidential campaign of Florida Gov. Ron DeSantis (R) shared an AI-generated image of former president Donald Trump embracing Anthony S. Fauci. That hug never happened. In Chicago’s mayoral primary, someone used AI to clone the voice of candidate Paul Vallas in a fake news report, making it look like he approved of police brutality.

But what will happen when a shocking image or audio clip goes viral in a battleground state shortly before an election? What kind of chaos will ensue when someone uses a bot to send out individually tailored lies to millions of different voters?

A wide 85 percent of U.S. citizens said they were “very” or “somewhat” concerned about the spread of misleading AI video and audio, in an August survey by YouGov. And 78 percent were concerned about AI contributing to the spread of political propaganda.

We can’t put the genie back in the bottle. AI is already embedded in tech tool campaigns that all of us use every day. AI creates our Facebook feeds and picks what ads we see. AI built into our phone cameras brightens faces and smooths skin.

What’s more, there are many political uses for AI that are unobjectionable, and even empowering for candidates with fewer resources. Politicians can use AI to manage the grunt work of sorting through databases and responding to constituents. Republican presidential candidate Asa Hutchinson has an AI chatbot trained to answer questions like him. (I’m not sure politician bots are very helpful, but fine, give it a try.)

Clarke’s solution, included in a bill she introduced on political ads: Candidates should disclose when they use AI to create communications. You know the “I approve this message” notice? Now add, “I used AI to make this message.”

But labels aren’t enough. If AI disclosures become commonplace, we may become blind to them, like so much other fine print.

The bigger ask: We want candidates and their supporting parties and committees not to use AI to deceive us.

So what’s the difference between a dangerous deepfake and an AI facetune that makes an octogenarian candidate look a little less octogenarian?

“The core definition is showing a candidate doing or saying something they didn’t do or say,”

Sure, give Biden or Trump a facetune, or even show them shaking hands with Abraham Lincoln. But don’t use AI to show your competitor hugging an enemy or fake their voice commenting on current issues.

The pledge also includes not using AI to suppress voting, such as using an authoritative voice or image to tell people a polling place has been closed. That is already illegal in many states, but it’s still concerning how believable AI might make these efforts seem.

Don’t deepfake yourself. Making yourself or your favorite candidate appear more knowledgeable, experienced or culturally capable is also a form of deception.

(Pressed on the ethics of his use of AI, Adams just proved my point that we desperately need some ground rules. “These are part of the broader conversations that the philosophical people will have to sit down and figure out, ‘Is this ethically right or wrong?’ I’ve got one thing: I’ve got to run the city,” he said.)

The golden rule in my pledge — don’t use AI to be materially deceptive — is similar to the one in an AI regulation proposed by a bipartisan group of lawmakers

Such proposals have faced resistance in Washington on First Amendment grounds. The free speech of politicians is important. It’s not against the law for politicians to lie, whether they’re using AI or not. An effort to get the Federal Election Commission to count AI deepfakes as “fraudulent misrepresentation” under its existing authority has faced similar pushback.

But a pledge like the one I outline here isn’t a law restraining speech. It’s asking politicians to take a principled stand on their own use of AI

Schumer said he thinks my pledge is just a start of what’s needed. “Maybe most candidates will make that pledge. But the ones that won’t will drive us to a lower common denominator, and that’s true throughout AI,” he said. “If we don’t have government-imposed guardrails, the lowest common denominator will prevail.”

Now, after the Peronista government of Alberto Fernández and Cristina Fernández de Kirchner has failed to halt the country’s economic decline, a new force among Argentina’s Generation Z is rising.

This time, it’s young men who are at the forefront. Milei is speaking for them.

An admirer of Donald Trump and former Brazilian president Jair Bolsonaro, Milei is campaigning on an Argentine version of “Drain the Swamp.” His aggressive style, outlandish comments and unusual presentation — he claims he hasn’t brushed that hair in years — have drawn millions of viewers to his videos and disrupted traditional politics

He has branded Pope Francis — the Argentine former Archbishop of Buenos Aires Jorge Bergoglio, the first South American pontiff — an “evil” leftist. Climate change, he says, is a “socialist lie.” He would hold a referendum to undo the three-year-old law that legalized abortion. He has called for creating a market for the sale of organs.

But he has also offered frustrated Argentines a break from the status quo: He has proposed shutting down the central bank, dollarizing the economy and taking a “chain saw” to government spending.

His attacks on the peso are already shocking the Argentine economy; the currency has taken a nose dive in the widely traded black market in recent weeks. The inflation rate has skyrocketed.

If Milei wins, it will likely be on the strength of the country’s young. Voters aged 18 to 29 account for a quarter of the electorate, and polls show they’re overwhelmingly inclined to vote for the iconoclast. That’s especially true for young men.

Coronel grew up watching the North American right-wing provocateurs Jordan Peterson, Ben Shapiro and Milo Yiannopoulos on a YouTube channel that translated their words into Spanish. “They were a fundamental part of my ideological awakening,” he said. But his greatest inspiration was Trump.

“We stopped listening to the intellectuals to listen to the politicians,” Coronel said.

“While everyone was focused on feminist demands and gay rights, there was a generation slowly starting to pay attention to Javier Milei.”

He decided to become an economist in 1989 during the early days of hyperinflation in Argentina. He worked as a risk analyst for Corporacion America, owned by one of Argentina’s billionaires, before leaping into television as a regular guest on shows.

Milei’s unconventional ideas and brash style — rants peppered with personal insults — was a TV hit. As the peso plunged and inflation skyrocketed, his economic theories began to find an audience.

He was elected to Congress in 2021 on pledges to tear the political elite down. He gained national prominence by raffling off his congressional salary each month.

Milei describes himself as a liberal-libertarian or a miniarchist. He supports limiting government to just a few functions — ideally, only security and justice — a night-watchman state.

He promises to slash the number of federal ministries from 18 to eight. He applies his free-market ideas to just about everything — he proposes loosening gun restrictions to “maximize the cost of robbery” — and letting the invisible hand of the market do the rest.

“Sometimes I have to pinch myself to ask whether I am living a dream or it’s a reality,” he told The Washington Post. “Because what Javier Milei proposes in politics hasn’t been heard in Argentina for 80 years.”

Milei’s originality is perhaps exactly why Gen Z is so transfixed by him. It’s a generation craving authenticity, Argentine political analyst Ana Iparraguirre said. “They see this guy telling it like it is,” she said. “I might not like that he’ll be selling guns in the streets, but at least this guy is not faking it.”

Most of his 1.4 million TikTok followers are younger than 24, according to his social media team. Iñaki Gutierrez, a 22-year old unpaid volunteer who manages his TikTok, said Milei managed to win the primaries in remote provinces “we didn’t even set foot in.” “TikTok was the answer,” Gutierrez said.

The fastest-growing social media site in Latin America has helped elect a wave of millennial presidents in the region, including Nayib Bukele in El Salvador and, last week, Daniel Noboa in Ecuador.

Milei’s TikTok posts offer Gen Z voters an outlet for rebellion against a system that they say is doing very little for them.

According to one recent survey, more than 65 percent of young voters say they would leave Argentina if they could.

“They feel they have no future,” Iparraguirre said. “If you’ve got nothing to lose you may as well try something different.”

Fragoso’s girlfriend, Victoria Alegre, 23, walking with him in a mall in Buenos Aires this week, said she thinks Milei is a machista who could roll back rights for women. Fragoso said he also dislikes the way Milei speaks about feminism. But he’s willing to overlook it, he said, to take a chance on something — anything — different.

“They said we were dangerous and that we needed to be quiet,” Milei shouted. “But we’re here, we fought the battle and we’re going to win!

Second, our margin of safety is shrinking: The power of American deterrence in the Far East is declining. While there are some favorable long-term trends, for the next few years at least, China and North Korea are likely to see more reasons to test the will and the power of the U.S. and its allies.

If China decides on forcible unification with Taiwan, it has two principal options. It can invade the island directly, or it can try to blockade it. Taiwan, which imports 97% of its energy supply and also depends on food imports, is vulnerable to such a blockade.

Whether China invades or blockades, the regional and global consequences would be the gravest shock to the global economy since World War II.

Regionally, the effect of closing the South China Sea and the waters around Taiwan to international trade would be calamitous. South Korea and Japan are both heavily dependent on imported fuel and food. Both economies depend on the ability of their great manufacturing companies to import raw materials and export finished goods. A suspension of maritime trade would effectively put both economies on life support, while making it difficult for tens of millions of people to heat their homes, run their cars or feed their children.

North Korea, seeing an opening in the global and regional chaos, would take the opportunity to attack at a time when U.S. forces would have enormous difficulty reinforcing and resupplying the South.

China would also be hit. Ships wouldn’t travel through war zones to Shanghai, Qingdao or Tianjin. The U.S. would likely, in addition to sanctions, enforce a blockade against ships seeking to supply China with goods deemed important for war.

For the rest of the world this would mean a massive supply-chain headache. From Taiwan’s semiconductors, vital for many industries and consumer products, to all the things that China, Japan and South Korea produce, the products of the Far East would vanish from inventories and store shelves.

Globally, makers of the raw materials for those countries, as well as growers of such agricultural commodities as soybeans and grain, would lose access to major markets.

the financial consequences of the war could pose insurmountable challenges for the world’s central banks. Stocks would crash. Currencies would gyrate. Debt markets would implode as sovereign borrowers like China and Japan faced wartime conditions and corporations dependent on Asian economies struggled to manage their debts.

Lulled into complacency by a long era of peace, most of us have yet to appreciate fully the dangers we face. Vladimir Putin’s invasion of Ukraine and the Hamas attack on Israel should have made clear that we live in an era when the unthinkable can happen overnight. These days, we must not only learn to think about the unthinkable, in nuclear strategist Herman Kahn’s phrase. We also need to prepare for it.

The report, as Svrluga writes, “paints a picture of a university that discouraged people from reporting crimes, underreported the claims it received and, meanwhile, marketed its Virginia campus as one of the safest in the country.” The details are grim. According to the report, “Liberty failed to warn the campus community about gas leaks, bomb threats and people credibly accused of repeated acts of sexual violence — including a senior administrator and an athlete.”

A campus safety consultant told Svrluga, “This is the single most blistering Clery report I have ever read. Ever.”

I’ve been following (and covering) Liberty’s moral collapse for years, and the list of scandals and lawsuits plaguing the school is extraordinarily long. The best known of these is the saga of Jerry Falwell Jr. Falwell, the former president and son of the school’s founder, resigned amid allegations of sexual misconduct involving himself, his wife and a pool boy turned business associate named Giancarlo Granda.

Why? Because he realized the health of the church wasn’t up to the state, nor was it dependent on the church’s nonbelieving neighbors.

Paul demonstrates ferocious anger at the church’s internal sin, but says this about those outside the congregation: “What business is it of mine to judge those outside the church? Are you not to judge those inside? God will judge those outside. ‘Expel the wicked person from among you.’”

Yet as we witness systemic misconduct unfold at institution after institution after institution, often without any real accountability, we can understand that many members of the church have gotten Paul’s equation exactly backward. They are remarkably tolerant of even the most wayward, dishonest and cruel individuals and institutions in American Christianity. At the same time, they approach those outside with a degree of anger and ferocity that’s profoundly contributing to American polarization.

Under this moral construct, internal critique is perceived as a threat, a way of weakening American evangelicalism. It’s seen as contributing to external hostility and possibly even the rapid secularization of American life that’s now underway. But Paul would scoff at such a notion. One of the church’s greatest apostles didn’t hold back from critiquing a church that faced far greater cultural or political headwinds — including brutal and deadly persecution at the hands of the Roman state — than the average evangelical can possibly imagine.

Falwell is nationally prominent in part because he was one of Donald Trump’s earliest and most enthusiastic evangelical supporters. Falwell sued the school, the school sued Falwell, and in September Falwell filed a scorching amended complaint, claiming that other high-ranking Liberty officers and board members had committed acts of sexual and financial misconduct yet were permitted to retain their positions

Liberty University is consequential not just because it’s an academic superpower in Christian America, but also because it’s a symbol of a key reality of evangelical life — we have met the enemy of American Christianity, and it is us.

So fear creates recessions in the long run — and if we continue to have rising fear, the probability of a European recession grows and the probability of a US recession grows. Geopolitics is playing a bigger role in everyone’s equations.”

Geopolitical risk is a major component in shaping all our lives. We are having rising fear throughout the world, and less hope. Rising fear creates a withdrawal from consumption or spending more.

“When the Russian invasion occurred in Ukraine, we said that the peace dividend is over,” Larry Fink, chief executive of investment giant BlackRock, told The Sunday Times. “Now, with the instability in the Middle East, we’re going to almost a whole new future.

Dimon noted that inflation had “levelled off a little bit” overall, but said: “It’s not clear to me that long-term forces are not inflationary … And that’s why I’m saying rates could possibly go up from here. That’s life in the fast lane.”

Higher borrowing costs have started to hit debt-fuelled sectors that boomed in the zero-rates era — such as commercial property, where $80 billion (£65 billion) of assets across the US are in some form of financial distress, according to MSCI, and private equity.

[the legendary investor] Warren Buffett says you see who’s swimming naked when the tide goes out. Not everyone is really ready for 6 or 7 per cent rates, but I wouldn’t rule them out.”

Fink pointed out that the transmission of rate rises into the US economy was less direct than in the UK

“I’m a fundamental believer that we’re going to have higher inflation for longer, and it’s going to require the [Fed] to raise rates higher — probably one or two more tightenings — and that will ultimately be the way we get into recession.”

Many senior figures on Wall Street worry about the US government’s ability to finance itself in the medium term. As in the UK, the market for government debt was underpinned by huge waves of quantitative easing (QE) after the financial crisis, as the Federal Reserve, in effect, bought assets including Treasuries to boost the economy. Following a revival of the programme during Covid, it came to an end in March last year.

The withdrawal of QE, combined with lacklustre appetite for Treasuries among US banks and international investors such as China, could force the government to pay higher prices at a time of near-record borrowing.

“It might be a 20km headwind right now, but next year it’s going to be 25km and it’s going to grow,” a top investor said of the decreasing international demand for US government debt.

US stock market floats and fundraisings, the heartbeat of capital markets, slumped to their lowest level since 1998 last year as the spike in interest rates punctured valuations of growth stocks in sectors such as tech and healthcare.

The cautious mood on Wall Street comes against a backdrop of surprisingly strong US growth. The economy expanded by an astonishing 4.9 per cent in the third quart

the Biden administration is shovelling stimulus into the system via big pieces of legislation promising to accelerate America’s adoption of renewables, rebuild its advanced semiconductor industry and increase its spending on roads, bridges and broadband.

We have huge stimulus,” said Fink. “People are not factoring in the Inflation Reduction Act, the Chips Act and the Infrastructure Act, which are about $970 billion of stimulus. Those are the largest stimuluses ever when there’s not a pandemic or a financial crisis ... And it’s at a time when you can have unions win a 25 per cent labour increase … These are very inflationary, whether it’s the fiscal stimulus or these wage increases.”

It all comes back to that word. Unexpectedly high growth, massive government stimulus and now two wars that threaten to spill out into broader crises — it all spells inflation. The flurry of hope in markets that Fed and the Bank of England have reached the top of their rate-raising cycles may yet prove premature

But when economists talk about inflation, they mean the rate at which prices are increasing, not their absolute level.

The first is: what disinflation? Prices are still a lot higher than they were three years ago.

let me deal with two complaints I often get when I talk about disinflation.

If you want a measure that’s closer to how people currently spend their money, you want the Harmonized Index of Consumer Prices.

The second complaint I constantly hear involves assertions that the supposed fall in inflation is fake, because economists exclude the prices of the things real people actually buy.

this is almost exactly wrong. The U.S. Consumer Price Index contains a lot of stuff people do not, in fact, actually buy. As we’ve discussed before in this newsletter, a quarter of the index is “owners’ equivalent rent,” an estimate of what homeowners would be paying if they were renting their houses.

trying to get the overall level of prices back to what it was before an inflationary shock, as opposed to stabilizing them, is almost always a bad idea.

The bottom line is that disinflation is real — indeed, spectacular.

Are we all the way back to 2 percent inflation? Probably not, although there’s a real angels-dancing-on-the-head-of-a-pin feel to the debate over the right measure of underlying inflation, and even over what that term really means

ut we’ve gotten most of the way there, without a recession or even a large rise in unemployment.

So why were many economists so pessimistic last fall?

what strikes me about the dire inflation predictions of summer and fall 2022 is their non sequiturness (non sequituritality?)

The Biden fiscal stimulus of early 2021 was very large, so it made sense to worry about excessive spending driving prices up. Predictions that inflation would remain stubbornly high, however, didn’t draw at all on the same logic; instead, pessimists came up with new, completely unrelated justifications for their pessimism.

these arguments for persistent inflation weren’t just unrelated to the original case for inflation; they were also unrelated to each other — almost as if economists were looking for reasons to be pessimistic.

I’d like to see some hard thinking about how so many of my colleagues got this story so wrong, and maybe even a bit of introspection about their motivations.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Now, students will participate in a jigsaw activity. Below are three articles about three different student populations that have been affected by the war in Ukraine. Assign each student, or have them choose, one of the articles to become an “expert” in. Make sure there are about an even number of students reading each article.

5. What are some of the fears or challenges teachers themselves are facing because of the war?6. You’ve read one of three articles about what education is like for a specific group of students. What role is school serving for the group you read about? Is there anything more schools could be doing to support these young people? If so, what and why?

What role can schools serve, even during war? How important do you think education is in a time like this? Do you believe educators should teach about what is happening in Ukraine? How do you think they should handle this sensitive subject?

Many teachers answered our call in mid-March to tell us how they were addressing the war in their classrooms. Here are some responses that show the many ways, large and small, that educators have sought to help their students understand the conflict and its roots, the plight of the Ukrainian people, the role of the United States and more. They have been edited for length and clarity.

I was shocked at how hungrily they soaked up the information, especially once Russia officially invaded Ukraine. These 10-, 11- and 12-year-olds wanted to learn more about what was happening in their world in the “right way” — via vetted news sources, exactly as you mentioned. After each episode, we discussed positives that we heard, we shared “wonders” (the things that we want to find more information on), and we shared one word to summarize the new information.

That day, my students’ remarks on the Russian invasion of Ukraine fit into five categories: empathy for the people of Ukraine, fear of World War III, criticism of Putin, criticism of memes that treat the invasion as a joke, and geopolitical curiosity.

Students then created infographics on Canva to illustrate their learning. Synthesizing that learning into smaller, digestible data bites helped them to make sense of such large, challenging concepts. Here are four examples of their work.

When discussing the conflict between Russia and Ukraine, that consisted of orienting everyone to where this conflict is happening geographically and what cities and countries are involved. We spoke about the history of NATO, key leaders, the concept of trade and supply chains — basically defining the common vocabulary and giving everyone the same tools for discussion.

That’s how I realized that my students needed to talk about the Russian invasion of Ukraine. As a result, I took the following steps the next day, with positive results.

As part of a larger project on the theme of “nostalgia,” students were asked to think of a family recipe that made them nostalgic. But we also talked about the food that brings us comfort no matter where we find ourselves. To help students connect to the Ukrainian people, we talked about the comforts of borscht with information from this article about a chef who is leading a drive to recognize the soup as a Ukrainian cultural heritage.

Teaching about Russia and Ukraine this spring encompassed history, vocabulary, maps, graphs, and photo analysis. We began with a brainstorm about what students had heard about what was happening with Ukraine and Russia. Then students moved on to define terms like Soviet Union, Cold War and NATO, and worked together to combine their definitions into one “best definition.” This vocabulary work set them up to read the Times article about what was happening in Ukraine as Russia invaded, annotating in the

Part of what has made the coverage of the war in Ukraine compelling is my students seeing visual inversions of their own lives. There’s a photo of a grandmother, but she’s holding an assault rifle. There are teenagers, not much older than they are, running drills. There’s a teacher, but instead of trying to manage a class, she’s barely managing to hold it together.

What do you notice about how the person is framed in the photograph?What is the posture? Where is their gaze?Imagine what they might be thinking as they gaze out of the frame.

This is an excellent piece to use when considering primary and secondary audiences, purpose, appeals, and overall effectiveness. It is also a story we can track to see if the speech moves anyone in Congress to change their position on the type of support to provide Ukraine.

Does the American government favor any countries over other countries? What is the policy that guides the American government when dealing with other countries?How does the American government handle disagreements with other countries?Which countries are American allies, or friends?Which are America’s traditional enemies? How is this determined? Does that history matter?

How does President Biden “create the enemy?” Why should America follow this course of action? What is he suggesting will happen if America does not? What does America stand to gain from this plan? Are potential losses discussed?Note patterns in rhetorical appeals, diction, values and themes. What assumptions does President Biden make about the American character or national identity? In what ways do American mythologies seem to bolster a “single story” of foreign policy?

Begins.” Students took notes on the use of ethos, pathos and logos in the construction of the podcast. They also responded to the importance of having free and independent journalists report on the war.

“We Lived Happily During the War,” “Dulce et Decorum Est” and “Dancing.”

E.I.H.R. cultivates partnerships among educators globally to create materials and deliver training based on best practices in Holocaust and human rights education. Together we deliver content and strategies for teaching conflict history and prevention, and sustainable peace. They have been building resources for teachers about Ukraine since Feb. 24, including this webinar on Understanding the Crisis in Ukraine from March 19.

“These countries have almost become guesthouses for terrorist organizations,” he said this month. “It is not possible for us to be in favor.”

The quandary would be simpler were it not for Turkey’s importance to the alliance. The country joined NATO in 1952 after aligning with the West against the Soviet Union; Turkey gives the alliance a crucial strategic position at the intersection of Europe and Asia, astride both the Middle East and the Black Sea. It hosts a major U.S. air base where American nuclear weapons are stored, and Mr. Erdogan has blocked Russian warships headed toward Ukraine.

Mr. Erdogan’s objections to the membership of Sweden and Finland have even renewed questions about whether NATO might be better off without Turkey.

“Turkey is a member of NATO, but under Mr. Erdogan it no longer subscribes to the values that underpin this great alliance,”

Some members of Congress have said as much. “Turkey under Erdogan should not and cannot be seen as an ally,”

“Turkey has undermined its own image,” said Alper Coskun, a former Turkish diplomat who is now a senior fellow at the Carnegie Endowment for International Peace. But, he added, “it is still a critical member of the alliance.”

The United States has also backed its affiliated fighters in Syria, the Y.P.G., or People’s Protection Units, who helped to battle the Islamic State and whom Mr. Erdogan attacked in his 2019 incursion into the country.

The Turkish president wants the Y.P.G. to be designated as a terrorist group as well.

Some analysts say that Mr. Erdogan’s government views the P.K.K. much the way Washington saw Al Qaeda 20 years ago, and that the West cannot dismiss the concerns if it hopes to do business with Turkey.

Biden administration officials downplay the standoff and expect Mr. Erdogan to reach a compromise with Finland and Sweden.

Mr. Erdogan’s main priorities are getting his country’s security concerns about Kurdish separatists heard and getting the arms embargoes lifted, Mr. Peker said.

“He has this very complicated relationship with Putin that he has to maintain,” Mr. Edelman said. “This is a good way of throwing a little bone to Putin — ‘I’m still useful to you.’”

“We need to sit down and we need to cut a deal,” Mr. Smith said. “And we need to get aggressive about it, like now.”

From Papua New Guinea to Palau, the countries of the region have jurisdiction over an area of ocean three times as large as the continental United States, stretching from just south of Hawaii to exclusive economic zones butting up against Australia, Japan and the Philippines.

Chinese fishing fleets already dominate the seas between the area’s roughly 30,000 islands, seizing huge hauls of tuna while occasionally sharing intelligence on the movements of the U.S. Navy. If China can add ports, airports and outposts for satellite communications — all of which are edging closer to reality in some Pacific Island nations — it could help in intercepting communications, blocking shipping lanes and engaging in space combat.

Mr. Wang signed several new agreements, including a security deal that gives China the power to send security forces to quell unrest or protect Chinese investments, and possibly to build a port for commercial and military use.

Chinese officials deny that’s the plan. But the deal — along with others in the Solomons and Kiribati whose details have not been disclosed — has been made possible because of something else that’s visible and much-discussed in the Pacific: a longstanding lack of American urgency, innovation and resources.

American officials point out that the United States does have big military bases in Guam, along with close ties to countries like the Marshall Islands. And in February, Antony J. Blinken became the first secretary of state in 36 years to visit Fiji, where he announced that the United States would reopen an embassy in the Solomon Islands and engage more on issues like illegal fishing and climate change.

The Yanks, it is often said, used to be more productive. Many of the airports and hospitals still in use across the Pacific were built by the United States and its allies during World War II.

“The United States doesn’t have a significant presence in the Pacific at all,” said Anna Powles, a senior lecturer in security studies at Massey University in New Zealand. “I’m always shocked that in Washington they think they have a significant presence when they just don’t.”

“There’s a lot of talk,” said Sandra Tarte, the head of the government and international affairs department at the University of the South Pacific in Suva. “And not much real substance.”

Mr. Blinken said last week that “China is the only country with both the intent to reshape the international order and, increasingly, the economic, diplomatic, military and technological power to do it.” He promised that the United States would “shape the strategic environment around Beijing to advance our vision for an open and inclusive international system.”

The start-up embassy in the Solomons also looks less impressive on closer inspection. Replacing an embassy that closed in the 1990s during America’s post-Cold War withdrawal, the outpost will begin in leased office space with two U.S. staff members and five local hires.

The American Embassy, by contrast, sits on a hillside far from downtown Suva in a heavily fortified compound. It covers five nations (Fiji, Kiribati, Nauru, Tonga and Tuvalu), doesn’t have a full-time ambassador — President Biden nominated someone only last week — and is known for being understaffed.

Joseph Veramu, a former U.N. consultant who runs Integrity Fiji, which focuses on values like transparency, said in an interview in Suva that he had invited U.S. embassy officials to events five or six times in recent years. Only once did someone come — without saying much, and refusing to allow photos.

But what they do want, and what China seems better at providing right now, is consistent engagement and capacity building.

While the United States has shown off Coast Guard vessels it is using to police illegal fishing, China is planning to build maritime transportation hubs and high-tech law enforcement centers where Chinese officers can provide expertise and equipment.

“China has always maintained that big and small countries are all equals,” Mr. Xi, the Chinese leader, said in a written message to Pacific foreign ministers on Monday. “No matter how international circumstances fluctuate, China will always be a good friend.”

Clearly, China intends to keep emphasizing that friendship means building stuff and offering promises of prosperity, while expecting news censorship, resource access and security opportunities in exchange.

The pressing question in this part of the world is: What does friendship mean to America?

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

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