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This is what connects figures as disparate as Jordan Peterson and J.D. Vance and Peter Thiel and Donald Trump. These are the ideas that unite both the mainstream and the weirder figures of the so-called postliberal right, from Patrick Deneen to the writer Bronze Age Pervert.

I think the Republican Party’s collapse into incoherence reflects the fact that much of the modern right is reactionary, not conservative

As Paul Valéry, the French poet, once said, “Ancient Greece is the most beautiful invention of the modern age.” To treat Andreessen’s essay as an argument misses the point. It’s a vibe. And the vibe is reactionary.

It’s a coalition obsessed with where we went wrong: the weakness, the political correctness, the liberalism, the trigger warnings, the smug elites. It’s a coalition that believes we were once hard and have become soft; worse, we have come to lionize softness and punish hardness.

The story of the reactionary follows a template across time and place. It “begins with a happy, well-ordered state where people who know their place live in harmony and submit to tradition and their God,” Mark Lilla writes in his 2016 book, “The Shipwrecked Mind: On Political Reaction.”

He continues:Then alien ideas promoted by intellectuals — writers, journalists, professors — challenge this harmony, and the will to maintain order weakens at the top. (The betrayal of elites is the linchpin of every reactionary story.) A false consciousness soon descends on the society as a whole as it willingly, even joyfully, heads for destruction. Only those who have preserved memories of the old ways see what is happening. Whether the society reverses direction or rushes to its doom depends entirely on their resistance.

The Silicon Valley cohort Andreessen belongs to has added a bit to this formula. In their story, the old way that is being lost is the appetite for risk and inequality and dominance that drives technology forward and betters human life. What the muscled ancients knew and what today’s flabby whingers have forgotten is that man must cultivate the strength and will to master nature, and other men, for the technological frontier to give way

Now Andreessen has distilled the whole ideology to a procession of stark bullet points in his latest missive, the buzzy, bizarre “Techno-Optimist Manifesto.”

it’s the pairing of the reactionary’s sodden take on modern society with the futurist’s starry imagining of the bright tomorrow. So call it what it is: reactionary futurism

Andreessen’s argument is simple: Technology is good. Very good. Those who stand in its way are bad.

“The Enemy.” The list is long, ranging from “anti-greatness” to “statism” to “corruption” to “the ivory tower” to “cartels” to “bureaucracy” to “socialism” to “abstract theories” to anyone “disconnected from the real world … playing God with everyone else’s lives”

So who is it, exactly, who extinguishes the dancing star within the human soul?

Our present society has been subjected to a mass demoralization campaign for six decades — against technology and against life — under varying names like “existential risk,” “sustainability,” “E.S.G.,” “sustainable development goals,” “social responsibility,” “stakeholder capitalism,” “precautionary principle,” “trust and safety,” “tech ethics,” “risk management,” “degrowth,” “the limits of growth.”

The enemy, in other words, is anything or anyone who might seek to yoke technology to social goals or structures

For years, I’ve been arguing for politics to take technology more seriously, to see new inventions as no less necessary than social insurance and tax policy in bringing about a worthier world. Too often, we debate only how to divvy up what we already have. We have lost the habit of imagining what we could have; we are too timid in deploying the coordinated genius and muscle of society

I’ve been digging into the history of where and when we lost faith in technology and, more broadly, growth. At the core of that story is an inability to manage, admit or even see when technologies or policies go awry

The turn toward a less-is-more politics came in the 1970s, when the consequences of reckless growth became unignorable

Did we, in some cases, overcorrect? Absolutely. But the only reason we can even debate whether we overcorrected is because we corrected: The Clean Air Act and the Clean Water Act and a slew of other bills and regulations did exactly what they promised.

It is telling that Andreessen groups sustainability and degrowth into the same bucket of antagonists

Degrowth is largely, though not wholly, skeptical of technological solutions to our problems

But the politics of sustainability — as evidenced in legislation like the Inflation Reduction Act — have settled into another place entirely: a commitment to solving our hardest environmental problems by driving technology forward, by investing and deploying clean energy infrastructure at a scale unlike anything the government has done since the 1950s.

Andreessen focuses at some length on the nuclear future he believes we’ve been denied —

but curiously ignores the stunning advances in solar and wind and battery power that public policy has delivered.

He yearns for a kind of person, not just a kind of technology. “We believe in ambition, aggression, persistence, relentlessness — strength,” he writes, italics included. “We believe in merit and achievement. We believe in bravery, in courage.”

There are ways in which these virtues have become undervalued, in which the left, in particular, has a dysfunctional relationship with individual achievement and entrepreneurial élan.

Andreessen’s ideas trace an odd, meme-based philosophy that has flourished in some corners of the internet known as effective accelerationism

“Effective accelerationism aims to follow the ‘will of the universe’: leaning into the thermodynamic bias towards futures with greater and smarter civilizations that are more effective at finding/extracting free energy from the universe,”

“E/acc has no particular allegiance to the biological substrate for intelligence and life, in contrast to transhumanism.” OK!

Take Andreessen’s naming of trust and safety teams as among his enemies.

That, in a way, is my core disagreement with Andreessen. Reactionary futurism is accelerationist in affect but deccelerationist in practice

How has that worked out? A new analysis by Similarweb found that traffic to twitter.com fell in the United States by 19 percent from September 2022 to September 2023 and traffic on mobile devices fell by almost 18 percent. Indications are that advertising revenue on the platform is collapsing.

Andreessen spends much of his manifesto venerating the version of markets that you hear in the first few weeks of Econ 101, before the professor begins complicating the picture with all those annoying market failures

Throughout his essay, Andreessen is at pains to attack those who might slow the development of artificial intelligence in the name of safety, but nothing would do more to freeze progress in A.I. than a disaster caused by its reckless deployment

It is hard to read Andreessen’s manifesto, with its chopped-up paragraphs and its blunt jabs of thought delivered for maximum engagement and polarization, and not feel that Andreessen now reflects the medium in which he has made his home: X. He doesn’t just write in the way the medium rewards. He increasingly seems to think in its house style, too.

One reason I left Twitter long ago is that I noticed that it was a kind of machine for destroying trust. It binds you to the like-minded but cuts you from those with whom you have even modest disagreements

There is a reason that Twitter’s rise was conducive to politics of revolution and reaction rather than of liberalism and conservatism. If you are there too often, seeing the side of humanity it serves up, it is easy to come to think that everything must be burned down.

Musk purchased Twitter (in an acquisition that Andreessen Horowitz helped finance) and gutted its trust and safety teams. The result has been a profusion of chaos, disinformation and division on his platform

Treating so much of society with such withering contempt will not speed up a better future. It will turn people against the politics and policies of growth, just as it did before. Trust is the most essential technology of all.

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

many foreign firms are looking for better uses for their money, as China’s economy slows and geopolitical tensions rise. Chilly relations between Beijing and the U.S.-led West have pushed global companies to rethink their supply chains and exposure to China.

The data show that for all but two quarters between 2014 and the middle of last year, foreign firms were reinvesting more in China than they were transferring abroad. In 2021, for instance, firms reinvested a net $170 billion. 

That shifted in the middle of 2022, when China was under sporadic lockdowns and the U.S. Federal Reserve began raising interest rates to combat rocketing inflation. Outflows have continued in each quarter since. 

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.

Since 1992, the number of people getting inheritances from parents has nearly doubled even as bequests from grandparents and aunts and uncles have remained flat. Your 50s will be your peak inheriting ages, which makes sense given that an average 65-year-old in the U.S. can expect to live to around age 83 and your parents are, sadly, mortal.

If you look only at the lucky few who inherited anything, their average is $266,00

And if you look only at those in their 70s, it climbs to $344,000. Of course, that’s the value at the time of the gift. Add inflation and market-level returns and many bequests are worth much more by the time you earn your septuagenarian badge.

when we ran the numbers, we found they weren’t random at all.

White folks are about three times more likely to inherit than their Black, Hispanic or Asian friend

it remains vast enough to help explain why the typical White family has more than six times the net worth of the typical Black American famil

Up and down the demographic charts, it appears to be a case of to whom much is given … much more is given

Folks in the bottom 50 percent of earners inherit at half the national rate, while those in the top 1 percent are twice as likely to inherit something.

he confirmed that inheritances make the rich richer. But a rich kid’s true inheritance goes far beyond cash value: In a million less-measurable ways, elite parents give you a head start in life. By the time they die and hand you a windfall, you’ve already used all your advantages to accumulate wealth of your own.

“It’s not just the dollar amount that you get when your parents die,” Ricco said. “It’s the safety net that you had to start a business when you were younger, or the ability to put down a larger share of your savings into a down payment and a house because you know that you can save less for retirement.

“Little things like that are probably the main mechanisms through which intergenerational wealth is transmitted and are not easily captured just by the final value of what you see.”

Just one variable — how much you inherit — can account for more than 60 percent of U.S. wealth inequality

So, if you had to guess someone’s economic station in life and you could peek at only one data point, inheritance would be a pretty good bet. It’s one of the clearest socioeconomic signals on the planet.

“They actually reflect many advantages, many inequalities of opportunities that we face.”

The U.S. tax system does little to temper our uneven inheritance. Consider the stepped-up basis provision, “one of the most egregious (tax loopholes) that we have,”

When you sell something at a profit, you typically pay capital gains tax. But you can avoid that tax by holding the asset until you expire. At your death, the cost basis of your assets gets stepped up to their current value — meaning your heirs avoid getting taxed on what might be a very substantial gain.

Say you’re a natural-soda fan who bought $1,000 of Hansen Natural Corp. stock in 2000. You watched your money grow to more than $1.15 million as sleepy Hansen became the world-eating Monster Beverage Corp. Selling the stock would force you to pay capital gains on more than $1 million in earnings, so instead, you took it to the grave

(If you needed cash, you probably borrowed against your stockpiled stock pile, a common strategy among the 1 percent.)

If your heirs sell it, they’ll pay no taxes. If the value of the stock rises to, say, $1.151 million, they would owe taxes only on that extra $1,000.

Now multiply that loophole by the millions of homes, businesses, equities and other assets being handed down each year

It encourages older folks to hoard homes and businesses they can no longer make full use of, assets our housing-starved millennial readers would gladly snap up.

Early on, Goldwein said, it may have been considered necessary because it was difficult to determine the original value of long-held property. Revenue lost to the loophole was partly offset by a simpler-to-administer levy: the estate tax.

For now, you’ll pay the federal estate tax only on the part of your fortune that exceeds $12.92 million ($25.84 million for couples), and rising to $13.61 million in 2024 — and that’s only if your tax lawyers aren’t smart enough to dodge it.

“Between politicians continuing to cut the estate tax and taxpayers becoming increasingly good at avoiding it, very few now pay it,” Goldwein said. “That means we now have a big net tax break for most people inheriting large amounts of money.”

Kumon presents a convincing explanation: If you didn’t produce a male heir in Japan, it was customary to adopt one. A surplus son from another family would marry into yours. That kept your property in the family.

In Europe, if an elite family didn’t produce a male heir, which happened more than a quarter of the time, the default was for a daughter to marry into another well-off family and merge assets. So while Japanese family lines remained intact from generation to generation, European family lines merged, concentrating wealth into fewer and fewer hands.

As other families compete to marry into the Darcys’ colossal estate — spoiler for a novel from 1813! — inequality increases.

Given a few centuries, even subtle variations in inheritance patterns can produce sweeping societal differences.

“People have faced higher prices and that is difficult, but that doesn’t explain why people have not cut back,” she said of a phenomenon known as revealed preference. “They have spent as if they see nothing but good times in front of them. So why are their actions so out of whack with their words?”

Many said their own finances were good enough — they had jobs, owned houses, made ends meet. But they felt as if they were “just getting by,” with “nothing left over.” Many felt angry and anxious over prices and the pandemic and politics.

Also, economists said, wages have increased alongside prices. Real median earnings for full-time workers are slightly higher than at the end of 2019, and for many low earners, their raises have outpaced inflation. But it’s common for people to think about prices at face value, rather than relative to their income, a habit economists call money illusion.

“The pandemic shattered a lot of illusions of control,” Professor Stevenson said. “I wonder how much that has made us more aware of all the places we don’t have control, over prices, over the housing market.”

Inflation weighed heavily on voters — nearly all of them mentioned frustration at the price of something they buy regularly.

Consumer prices were up 3.2 percent in October from the year before, a decline in the year-over-year inflation rate from more than 8 percent in mid-2022. But inflation “casts a long shadow on how people evaluate things,” said Lawrence Katz, an economist at Harvard. Some people may expect prices to return to what they were before — something that rarely happens

Those feelings may be driving attitudes about the economy, economists speculated, sounding more like their colleagues from another branch of social science, psychology.

Younger people — who were a key to President Biden’s win in 2020 but showed less support for him in the new poll — had concerns specific to their phase of life. In the poll, 93 percent of them rated the economy unfavorably, more than any other age group.

“Everyone thinks a wage increase is something they deserve, and a price increase is imposed by the economy on them,” Professor Katz said.

There’s a sense that it’s become harder to achieve the things their parents did, like buying a home. Houses are less affordable than at the height of the 2006 bubble, and less than half of Americans can afford one.

“More than likely, half my income will go toward rent,” he said. “I was really hoping on that student loan forgiveness.”

Yet overall, economists said, data shows that more people are quitting jobs to start better ones, moving to more desirable places because they can work remotely, and starting new businesses.

He said he makes almost $80,000, serving in the military and working as a DoorDash deliverer, yet feels he had more spending money a decade ago, when he was two pay grades lower.

he uncertainty Mr. Blanck and Ms. Linn share about the future ran through many voters’ stories, darkening their economic outlook.

“The degree of volatility that we’ve experienced from different events — from the pandemic, from inflation — leaves them not confident that even if objectively good things are going on, it’s going to persist,”

In response to the pandemic, the United States built an extensive welfare state, and it has since been dismantled. While wealth has increased for families across the income spectrum, data shows, and there are indications that inequality could be shrinking, the changes have been small relative to decades of growing inequality, leading to a sense for some that the system is rigged.

“When things are going well, that means rich people are getting richer and all of us are pretty much second,” said Manuel Zimberoff, 26, a manufacturing engineer in Philadelphia. “And if things are going poorly, rich people are still getting richer, and all of us are screwed.”

For roughly two decades, partisanship has increasingly been correlated with views about the economy: Research has shown that people rate the economy more poorly when their party is not in power. Nearly every Republican in the poll rated the economy unfavorably, and 59 percent of Democrats did.

He brought up U.S. funding in Ukraine and the Middle East. He wanted to know: Is that the reason our economy is “slowing down?” He wasn’t sure, but he thought it might be. He plans to vote for “the Republican, any Republican,” he said. “Democrats have disappointed me.”

So extreme is inequality that the lowest-earning 50% of the world population – 4 billion people – account for as little as 12% of total emissions.

And those at the very bottom of the pile barely register at all. Mali’s per capita C02 emissions are about one-seventy-fifth of those in the US. Even if the lowest-earning third of the global population – more than 2.6 billion people – were to raise themselves above the $3.2-a-day poverty line, it would increase total emissions by a mere 5% – that is, one-third of the emissions of the richest 1%.

Half the world’s population, led by the top 10% of the income distribution – and, above all, by the global elite – drive a globe-spanning productive system that destabilises the environment for everyone

The worst effects are suffered by the poorest, and in the coming decades the impact will become progressively more extreme. And yet their poverty means they are virtually powerless to protect themselves.

This is the triple inequality that defines the climate global equation: the disparity in responsibility for producing the problem; the disparity in experiencing the impacts of the climate crisis; and the disparity in the available resources for mitigation and adaptation.

global heating will pose huge distributional problems. How will climate refugees be resettled? How will the economy adapt?

For fragile states such as Iraq, it may prove too much. The risk is that they will tip from just about coping into outright collapse, failing to provide water and the electricity for cooling – the bare essentials for survival in extreme heat

You might say, plus ça change. The poor suffer and the rich prosper. But the consequences of the climate triple inequality are radical and new

Rich countries have long traded on unequal terms with the poor. During the era of colonialism, they plundered raw materials and enslaved tens of millions. For two generations after decolonisation, economic growth largely bypassed what was then known as the third world.

As we run ever closer to the edge of the environmental envelope – the conditions within which our species can thrive – the development of the rich world systematically undercuts the conditions for survival of billions of people in the climate danger zone

The middle 40% of the world’s income distribution now account for 41% of global emissions, meaning they have achieved a considerable level of energy consumption. But this “global middle class”, concentrated above all in east Asia, crowds out the carbon budget remaining for those on the lowest incomes, and their growth inflicts irreversible damage on some of the poorest and most disempowered people in the world.

Since the 1980s, with the acceleration of China’s economic growth, the scope of development has dramatically widened.

They are not so much exploited or bypassed as victimised by the climactic effects of economic growth taking place elsewhere. This violent and indirect entanglement is new in its quality and scale

Violent and unequal relationships between groups usually involve some degree of interaction and can, as a result, be resisted. Workers can strike.

But arms-length ecological victimisation entails no such relationship and offers correspondingly fewer channels for resistance from within the system.

can we not hope for more constructive responses to the triple inequality?

This question is still what gives such huge importance to the global climate conferences such as Cop28, which starts on 30 November. They may seem like staid and ritualistic affairs, but it is in such venues that the lethal connection between oil, gas and coal production, rich-world consumption and the lethal risks facing those in the climate danger zone can be articulated in political form.

since then the resistance of US and European negotiators has hardened. As we approach Cop28, the organisation and the financing of the fund are yet

Such a fund is no solution to the problem of the triple inequality. For that we need a comprehensive energy transition and new models of truly inclusive and sustainable development

But a loss and damage fund does one essential thing. It recognises that the global climate crisis is no longer a problem of future development. We have entered the stage where the failure to urgently address the mounting crisis becomes an active process of victimisation. A victimisation that cries out, at least, for an admission of responsibility and adequate compensation.

Adam Tooze is a professor of history at Columbia University

All the empathy and humility in the world will not mean much against the pressures of intolerance and tribalism without an invaluable quality that Sulzberger did not emphasise: courage.

Sulzberger seems to underestimate the struggle he is in, that all journalism and indeed America itself is in

In describing the essential qualities of independent journalism in his essay, he unspooled a list of admirable traits – empathy, humility, curiosity and so forth. These qualities have for generations been helpful in contending with the Times’s familiar problem, which is liberal bias

on their own, these qualities have no chance against the Times’s new, more dangerous problem, which is in crucial respects the opposite of the old one.

The Times’s problem has metastasised from liberal bias to illiberal bias, from an inclination to favour one side of the national debate to an impulse to shut debate down altogether

the internet knocked the industry off its foundations. Local newspapers were the proving ground between college campuses and national newsrooms. As they disintegrated, the national news media lost a source of seasoned reporters and many Americans lost a journalism whose truth they could verify with their own eyes.

far more than when I set out to become a journalist, doing the work right today demands a particular kind of courage:

the moral and intellectual courage to take the other side seriously and to report truths and ideas that your own side demonises for fear they will harm its cause.

One of the glories of embracing illiberalism is that, like Trump, you are always right about everything, and so you are justified in shouting disagreement down.

leaders of many workplaces and boardrooms across America find that it is so much easier to compromise than to confront – to give a little ground today in the belief you can ultimately bring people around

This is how reasonable Republican leaders lost control of their party to Trump and how liberal-minded college presidents lost control of their campuses. And it is why the leadership of the New York Times is losing control of its principles.

Over the decades the Times and other mainstream news organisations failed plenty of times to live up to their commitments to integrity and open-mindedness. The relentless struggle against biases and preconceptions, rather than the achievement of a superhuman objective omniscience, is what mattered

. I thought, and still think, that no American institution could have a better chance than the Times, by virtue of its principles, its history, its people and its hold on the attention of influential Americans, to lead the resistance to the corruption of political and intellectual life, to overcome the encroaching dogmatism and intolerance.

As the country became more polarised, the national media followed the money by serving partisan audiences the versions of reality they preferred

This relationship proved self-reinforcing. As Americans became freer to choose among alternative versions of reality, their polarisation intensified.

as the top editors let bias creep into certain areas of coverage, such as culture, lifestyle and business, that made the core harder to defend and undermined the authority of even the best reporters.

here have been signs the Times is trying to recover the courage of its convictions

The paper was slow to display much curiosity about the hard question of the proper medical protocols for trans children; but once it did, the editors defended their coverage against the inevitable criticism.

As Sulzberger told me in the past, returning to the old standards will require agonising change. He saw that as the gradual work of many years, but I think he is mistaken. To overcome the cultural and commercial pressures the Times faces, particularly given the severe test posed by another Trump candidacy and possible presidency, its publisher and senior editors will have to be bolder than that.

As a Democrat from a family of Democrats, a graduate of Yale and a blossom of the imagined meritocracy, I had my first real chance, at Buchanan’s rallies, to see the world through the eyes of stalwart opponents of abortion, immigration and the relentlessly rising tide of modernity.

the Times is failing to face up to one crucial reason: that it has lost faith in Americans, too.

For now, to assert that the Times plays by the same rules it always has is to commit a hypocrisy that is transparent to conservatives, dangerous to liberals and bad for the country as a whole.

It makes the Times too easy for conservatives to dismiss and too easy for progressives to believe.

The reality is that the Times is becoming the publication through which America’s progressive elite talks to itself about an America that does not really exist.

It is hard to imagine a path back to saner American politics that does not traverse a common ground of shared fact.

It is equally hard to imagine how America’s diversity can continue to be a source of strength, rather than become a fatal flaw, if Americans are afraid or unwilling to listen to each other.

I suppose it is also pretty grandiose to think you might help fix all that. But that hope, to me, is what makes journalism worth doing.

Since Adolph Ochs bought the paper in 1896, one of the most inspiring things the Times has said about itself is that it does its work “without fear or favour”. That is not true of the institution today – it cannot be, not when its journalists are afraid to trust readers with a mainstream conservative argument such as Cotton’s, and its leaders are afraid to say otherwise.

Most important, the Times, probably more than any other American institution, could influence the way society approached debate and engagement with opposing views. If Times Opinion demonstrated the same kind of intellectual courage and curiosity that my colleagues at the Atlantic had shown, I hoped, the rest of the media would follow.

You did not have to go along with everything that any tribe said. You did not have to pretend that the good guys, much as you might have respected them, were right about everything, or that the bad guys, much as you might have disdained them, never had a point. You did not, in other words, ever have to lie.

This fundamental honesty was vital for readers, because it equipped them to make better, more informed judgments about the world. Sometimes it might shock or upset them by failing to conform to their picture of reality. But it also granted them the respect of acknowledging that they were able to work things out for themselves.

The Atlantic did not aspire to the same role as the Times. It did not promise to serve up the news of the day without any bias. But it was to opinion journalism what the Times’s reporting was supposed to be to news: honest and open to the world.

Those were the glory days of the blog, and we hit on the idea of creating a living op-ed page, a collective of bloggers with different points of view but a shared intellectual honesty who would argue out the meaning of the news of the day

They were brilliant, gutsy writers, and their disagreements were deep enough that I used to joke that my main work as editor was to prevent fistfights.

Under its owner, David Bradley, my colleagues and I distilled our purpose as publishing big arguments about big ideas

we also began producing some of the most important work in American journalism: Nicholas Carr on whether Google was “making us stupid”; Hanna Rosin on “the end of men”; Taylor Branch on “the shame of college sports”; Ta-Nehisi Coates on “the case for reparations”; Greg Lukianoff and Jonathan Haidt on “the coddling of the American mind”.

I was starting to see some effects of the new campus politics within the Atlantic. A promising new editor had created a digital form for aspiring freelancers to fill out, and she wanted to ask them to disclose their racial and sexual identity. Why? Because, she said, if we were to write about the trans community, for example, we would ask a trans person to write the story

There was a good argument for that, I acknowledged, and it sometimes might be the right answer. But as I thought about the old people, auto workers and abortion opponents I had learned from, I told her there was also an argument for correspondents who brought an outsider’s ignorance, along with curiosity and empathy, to the story.

A journalism that starts out assuming it knows the answers, it seemed to me then, and seems even more so to me now, can be far less valuable to the reader than a journalism that starts out with a humbling awareness that it knows nothing.

In the age of the internet it is hard even for a child to sustain an “innocent eye”, but the alternative for journalists remains as dangerous as ever, to become propagandists. America has more than enough of those already.

When I looked around the Opinion department, change was not what I perceived. Excellent writers and editors were doing excellent work. But the department’s journalism was consumed with politics and foreign affairs in an era when readers were also fascinated by changes in technology, business, science and culture.

Fairly quickly, though, I realised two things: first, that if I did my job as I thought it should be done, and as the Sulzbergers said they wanted me to do it, I would be too polarising internally ever to lead the newsroom; second, that I did not want that job, though no one but my wife believed me when I said that.

there was a compensating moral and psychological privilege that came with aspiring to journalistic neutrality and open-mindedness, despised as they might understandably be by partisans. Unlike the duelling politicians and advocates of all kinds, unlike the corporate chieftains and their critics, unlike even the sainted non-profit workers, you did not have to pretend things were simpler than they actually were

On the right and left, America’s elites now talk within their tribes, and get angry or contemptuous on those occasions when they happen to overhear the other conclave. If they could be coaxed to agree what they were arguing about, and the rules by which they would argue about it, opinion journalism could serve a foundational need of the democracy by fostering diverse and inclusive debate. Who could be against that?

The large staff of op-ed editors contained only a couple of women. Although the 11 columnists were individually admirable, only two of them were women and only one was a person of colour

Not only did they all focus on politics and foreign affairs, but during the 2016 campaign, no columnist shared, in broad terms, the worldview of the ascendant progressives of the Democratic Party, incarnated by Bernie Sanders. And only two were conservative.

This last fact was of particular concern to the elder Sulzberger. He told me the Times needed more conservative voices, and that its own editorial line had become predictably left-wing. “Too many liberals,” read my notes about the Opinion line-up from a meeting I had with him and Mark Thompson, then the chief executive, as I was preparing to rejoin the paper. “Even conservatives are liberals’ idea of a conservative.” The last note I took from that meeting was: “Can’t ignore 150m conservative Americans.”

As I knew from my time at the Atlantic, this kind of structural transformation can be frightening and even infuriating for those understandably proud of things as they are. It is hard on everyone

experience at the Atlantic also taught me that pursuing new ways of doing journalism in pursuit of venerable institutional principles created enthusiasm for change. I expected that same dynamic to allay concerns at the Times.

If Opinion published a wider range of views, it would help frame a set of shared arguments that corresponded to, and drew upon, the set of shared facts coming from the newsroom.

New progressive voices were celebrated within the Times. But in contrast to the Wall Street Journal and the Washington Post, conservative voices – even eloquent anti-Trump conservative voices – were despised, regardless of how many leftists might surround them.

The Opinion department mocked the paper’s claim to value diversity. It did not have a single black editor

Eventually, it sank in that my snotty joke was actually on me: I was the one ignorantly fighting a battle that was already lost. The old liberal embrace of inclusive debate that reflected the country’s breadth of views had given way to a new intolerance for the opinions of roughly half of American voters.

Out of naivety or arrogance, I was slow to recognise that at the Times, unlike at the Atlantic, these values were no longer universally accepted, let alone esteemed

After the 9/11 attacks, as the bureau chief in Jerusalem, I spent a lot of time in the Gaza Strip interviewing Hamas leaders, recruiters and foot soldiers, trying to understand and describe their murderous ideology. Some readers complained that I was providing a platform for terrorists, but there was never any objection from within the Times.

Our role, we knew, was to help readers understand such threats, and this required empathetic – not sympathetic – reporting. This is not an easy distinction but good reporters make it: they learn to understand and communicate the sources and nature of a toxic ideology without justifying it, much less advocating it.

Today’s newsroom turns that moral logic on its head, at least when it comes to fellow Americans. Unlike the views of Hamas, the views of many Americans have come to seem dangerous to engage in the absence of explicit condemnation

Focusing on potential perpetrators – “platforming” them by explaining rather than judging their views – is believed to empower them to do more harm.

After the profile of the Ohio man was published, media Twitter lit up with attacks on the article as “normalising” Nazism and white nationalism, and the Times convulsed internally. The Times wound up publishing a cringing editor’s note that hung the writer out to dry and approvingly quoted some of the criticism, including a tweet from a Washington Post opinion editor asking, “Instead of long, glowing profiles of Nazis/White nationalists, why don’t we profile the victims of their ideologies”?

the Times lacked the confidence to defend its own work

The editor’s note paraded the principle of publishing such pieces, saying it was important to “shed more light, not less, on the most extreme corners of American life”. But less light is what the readers got. As a reporter in the newsroom, you’d have to have been an idiot after that explosion to attempt such a profile

Empathetic reporting about Trump supporters became even more rare. It became a cliché among influential left-wing columnists and editors that blinkered political reporters interviewed a few Trump supporters in diners and came away suckered into thinking there was something besides racism that could explain anyone’s support for the man.

After a year spent publishing editorials attacking Trump and his policies, I thought it would be a demonstration of Timesian open-mindedness to give his supporters their say. Also, I thought the letters were interesting, so I turned over the entire editorial page to the Trump letters.

I wasn’t surprised that we got some criticism on Twitter. But I was astonished by the fury of my Times colleagues. I found myself facing an angry internal town hall, trying to justify what to me was an obvious journalistic decision

Didn’t he think other Times readers should understand the sources of Trump’s support? Didn’t he also see it was a wonderful thing that some Trump supporters did not just dismiss the Times as fake news, but still believed in it enough to respond thoughtfully to an invitation to share their views?

And if the Times could not bear to publish the views of Americans who supported Trump, why should it be surprised that those voters would not trust it?

Two years later, in 2020, Baquet acknowledged that in 2016 the Times had failed to take seriously the idea that Trump could become president partly because it failed to send its reporters out into America to listen to voters and understand “the turmoil in the country”. And, he continued, the Times still did not understand the views of many Americans

Speaking four months before we published the Cotton op-ed, he said that to argue that the views of such voters should not appear in the Times was “not journalistic”.

Conservative arguments in the Opinion pages reliably started uproars within the Times. Sometimes I would hear directly from colleagues who had the grace to confront me with their concerns; more often they would take to the company’s Slack channels or Twitter to advertise their distress in front of each other

This environment of enforced group-think, inside and outside the paper, was hard even on liberal opinion writers. One left-of-centre columnist told me that he was reluctant to appear in the New York office for fear of being accosted by colleagues.

An internal survey shortly after I left the paper found that barely half the staff, within an enterprise ostensibly devoted to telling the truth, agreed “there is a free exchange of views in this company” and “people are not afraid to say what they really think”.)

Even columnists with impeccable leftist bona fides recoiled from tackling subjects when their point of view might depart from progressive orthodoxy.

The bias had become so pervasive, even in the senior editing ranks of the newsroom, as to be unconscious

Trying to be helpful, one of the top newsroom editors urged me to start attaching trigger warnings to pieces by conservatives. It had not occurred to him how this would stigmatise certain colleagues, or what it would say to the world about the Times’s own bias

By their nature, information bubbles are powerfully self-reinforcing, and I think many Times staff have little idea how closed their world has become, or how far they are from fulfilling their compact with readers to show the world “without fear or favour”

sometimes the bias was explicit: one newsroom editor told me that, because I was publishing more conservatives, he felt he needed to push his own department further to the left.

The Times’s failure to honour its own stated principles of openness to a range of views was particularly hard on the handful of conservative writers, some of whom would complain about being flyspecked and abused by colleagues. One day when I relayed a conservative’s concern about double standards to Sulzberger, he lost his patience. He told me to inform the complaining conservative that that’s just how it was: there was a double standard and he should get used to it.

A publication that promises its readers to stand apart from politics should not have different standards for different writers based on their politics. But I delivered the message. There are many things I regret about my tenure as editorial-page editor. That is the only act of which I am ashamed.

I began to think of myself not as a benighted veteran on a remote island, but as Rip Van Winkle. I had left one newspaper, had a pleasant dream for ten years, and returned to a place I barely recognised.

The new New York Times was the product of two shocks – sudden collapse, and then sudden success. The paper almost went bankrupt during the financial crisis, and the ensuing panic provoked a crisis of confidence among its leaders. Digital competitors like the HuffPost were gaining readers and winning plaudits within the media industry as innovative. They were the cool kids; Times folk were ink-stained wrinklies.

In its panic, the Times bought out experienced reporters and editors and began hiring journalists from publications like the HuffPost who were considered “digital natives” because they had never worked in print. This hiring quickly became easier, since most digital publications financed by venture capital turned out to be bad businesses

Though they might have lacked deep or varied reporting backgrounds, some of the Times’s new hires brought skills in video and audio; others were practised at marketing themselves – building their brands, as journalists now put it – in social media. Some were brilliant and fiercely honest, in keeping with the old aspirations of the paper.

critically, the Times abandoned its practice of acculturation, including those months-long assignments on Metro covering cops and crime or housing. Many new hires who never spent time in the streets went straight into senior writing and editing roles.

All these recruits arrived with their own notions of the purpose of the Times. To me, publishing conservatives helped fulfil the paper’s mission; to them, I think, it betrayed that mission.

then, to the shock and horror of the newsroom, Trump won the presidency. In his article for Columbia Journalism Review, Sulzberger cites the Times’s failure to take Trump’s chances seriously as an example of how “prematurely shutting down inquiry and debate” can allow “conventional wisdom to ossify in a way that blinds society.

Many Times staff members – scared, angry – assumed the Times was supposed to help lead the resistance. Anxious for growth, the Times’s marketing team implicitly endorsed that idea, too.

As the number of subscribers ballooned, the marketing department tracked their expectations, and came to a nuanced conclusion. More than 95% of Times subscribers described themselves as Democrats or independents, and a vast majority of them believed the Times was also liberal

A similar majority applauded that bias; it had become “a selling point”, reported one internal marketing memo. Yet at the same time, the marketers concluded, subscribers wanted to believe that the Times was independent.

As that memo argued, even if the Times was seen as politically to the left, it was critical to its brand also to be seen as broadening its readers’ horizons, and that required “a perception of independence”.

Readers could cancel their subscriptions if the Times challenged their worldview by reporting the truth without regard to politics. As a result, the Times’s long-term civic value was coming into conflict with the paper’s short-term shareholder value

The Times has every right to pursue the commercial strategy that makes it the most money. But leaning into a partisan audience creates a powerful dynamic. Nobody warned the new subscribers to the Times that it might disappoint them by reporting truths that conflicted with their expectations

When your product is “independent journalism”, that commercial strategy is tricky, because too much independence might alienate your audience, while too little can lead to charges of hypocrisy that strike at the heart of the brand.

It became one of Dean Baquet’s frequent mordant jokes that he missed the old advertising-based business model, because, compared with subscribers, advertisers felt so much less sense of ownership over the journalism

The Times was slow to break it to its readers that there was less to Trump’s ties to Russia than they were hoping, and more to Hunter Biden’s laptop, that Trump might be right that covid came from a Chinese lab, that masks were not always effective against the virus, that shutting down schools for many months was a bad idea.

there has been a sea change over the past ten years in how journalists think about pursuing justice. The reporters’ creed used to have its foundation in liberalism, in the classic philosophical sense. The exercise of a reporter’s curiosity and empathy, given scope by the constitutional protections of free speech, would equip readers with the best information to form their own judgments. The best ideas and arguments would win out

The journalist’s role was to be a sworn witness; the readers’ role was to be judge and jury. In its idealised form, journalism was lonely, prickly, unpopular work, because it was only through unrelenting scepticism and questioning that society could advance. If everyone the reporter knew thought X, the reporter’s role was to ask: why X?

Illiberal journalists have a different philosophy, and they have their reasons for it. They are more concerned with group rights than individual rights, which they regard as a bulwark for the privileges of white men. They have seen the principle of  free speech used to protect right-wing outfits like Project Veritas and Breitbart News and are uneasy with it.

They had their suspicions of their fellow citizens’ judgment confirmed by Trump’s election, and do not believe readers can be trusted with potentially dangerous ideas or facts. They are not out to achieve social justice as the knock-on effect of pursuing truth; they want to pursue it head-on

The term “objectivity” to them is code for ignoring the poor and weak and cosying up to power, as journalists often have done.

And they do not just want to be part of the cool crowd. They need to be

To be more valued by their peers and their contacts – and hold sway over their bosses – they need a lot of followers in social media. That means they must be seen to applaud the right sentiments of the right people in social media

The journalist from central casting used to be a loner, contrarian or a misfit. Now journalism is becoming another job for joiners, or, to borrow Twitter’s own parlance, “followers”, a term that mocks the essence of a journalist’s role.

The new newsroom ideology seems idealistic, yet it has grown from cynical roots in academia: from the idea that there is no such thing as objective truth; that there is only narrative, and that therefore whoever controls the narrative – whoever gets to tell the version of the story that the public hears – has the whip hand

What matters, in other words, is not truth and ideas in themselves, but the power to determine both in the public mind.

By contrast, the old newsroom ideology seems cynical on its surface. It used to bug me that my editors at the Times assumed every word out of the mouth of any person in power was a lie.

And the pursuit of objectivity can seem reptilian, even nihilistic, in its abjuration of a fixed position in moral contests. But the basis of that old newsroom approach was idealistic: the notion that power ultimately lies in truth and ideas, and that the citizens of a pluralistic democracy, not leaders of any sort, must be trusted to judge both.

Our role in Times Opinion, I used to urge my colleagues, was not to tell people what to think, but to help them fulfil their desire to think for themselves.