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the intellectual right effectively dismissed the book

Here is David Brooks, echoing the conservative consensus in 2006:

As any number of historians, sociologists and pollsters can tell you, the evangelical Protestants who now exercise a major influence on the Republican Party are an infinitely diverse and contradictory group, and their relationship to these hyperpartisans is extremely ambivalent.

The idea that members of the religious right form an “infinitely diverse and contradictory group” and were in no way “hyperpartisan” is now clearly absurd. Christianism, in fact, turned out to be the central pillar of Trump’s success, with white evangelicals giving unprecedented and near-universal support — 84 percent — to a shameless, disgusting pagan, because and only because he swore to smite their enemies.

The fusion of Trump and Christianism is an unveiling of a sort — proof of principle that, in its core, Christianism is not religious but political, a reactionary cult susceptible to authoritarian preacher

Christianism is to the American right what critical theory is to the American left: a reductionist, totalizing creed that “others” half the country, and deeply misreads the genius of the American project.

Christianism starts, as critical theory does, by attacking the core of the Founding: in particular, its Enlightenment defense of universal reason, and its revolutionary removal of religion from the state.

Mike Johnson’s guru, pseudo-historian David Barton, claims that the Founders were just like evangelicals today, and intended the government at all levels to enforce “Christian values” — primarily, it seems, with respect to the private lives of others. As Pete Wehner notes, “If you listen to Johnson speak on the ‘so-called separation of Church and state’ and claim that ‘the Founders wanted to protect the church from an encroaching state, not the other way around,’ you will hear echoes of Barton.”

Christianism is a way to think about politics without actually thinking. Johnson expressed this beautifully last week: “I am a Bible-believing Christian. Someone asked me today in the media, they said, ‘It’s curious, people are curious: What does Mike Johnson think about any issue under the sun?’ I said, ‘Well, go pick up a Bible off your shelf and read it. That’s my worldview.

this tells us nothing, of course. The Bible demands interpretation in almost every sentence and almost every word; it contains universes of moral thought and thesauri of ambiguous words in a different ancient language; it has no clear blueprint for contemporary American politics, period

Yet Johnson uses it as an absolute authority to back up any policy he might support

The submission to (male) authority is often integral to fundamentalism

Trump was an authority figure, period. He was a patriarch. He was the patriarch of their tribe. And he was in power, which meant that God put him there. After which nothing needs to be said. So of course if the patriarch says the election is rigged, you believe him.

And of course you do what you can to make sure that God’s will be done — by attempting to overturn the election results if necessary.

Christianism is a just-so story, with no deep moral conflicts. Material wealth does not pose a moral challenge, for example, as it has done for Christians for millennia. For Christianists, it’s merely proof that God has blessed you and you deserve it.

“I believe that scripture, the Bible is very clear: that God is the one that raises up those in authority. And I believe that God has ordained and allowed each one of us to be brought here for this specific moment.” That means that Trump was blessed by God, and not just by the Electoral College in 2016. And because he was blessed by God, it was impossible that Biden beat him fairly in 2020.

More than three-quarters of those representing the most evangelical districts are election deniers, compared to just half of those in the remaining districts. Fully three-quarters of the deniers in the caucus hail from evangelical districts.

since the Tea Party, the turnover in primary challenges in these evangelical districts has been historic — a RINO-shredding machine. No wonder there were crosses being carried on Capitol Hill on January 6, 2021. The insurrectionists were merely following God’s will. And Trump’s legal team was filled with the faithful.

Tom Edsall shows the skew that has turned American politics into something of a religious war: “When House districts are ranked by the percentage of voters who are white evangelicals, the top quintile is represented by 81 Republicans and 6 Democrats and the second quintile by 68 Republicans and 19 Democrats.”

the overwhelming majority of the Republican House Caucus (70%) represents the Most Evangelical districts (top two quintiles). Thus, we can see that a group that represents less than 15% of the US population commands 70% of the districts comprising the majority party in the House of Representatives.

And almost all those districts are safe as houses. When you add Christianism to gerrymandering, you get a caucus that has no incentive to do anything but perform for the cable shows.

This is not a caucus interested in actually doing anything.

I don’t know how we best break the grip of the fundamentalist psyche on the right. It’s a deep human tendency — to give over control to a patriarch or a holy book rather than engage in the difficult process of democratic interaction with others, compromise, and common ground.

he phenomenon has been given new life by a charismatic con-man in Donald Trump, preternaturally able to corral the cultural fears and anxieties of those with brittle, politicized faith.

What I do know is that, unchecked, this kind of fundamentalism is a recipe not for civil peace but for civil conflict

It’s a mindset, a worldview, as deep in the human psyche as the racial tribalism now endemic on the left. It controls one of our two major parties. And in so far as it has assigned all decisions to one man, Donald Trump, it is capable of supporting the overturning of an election — or anything else, for that matter, that the patriarch wants. Johnson is a reminder of that.

— giving the next generation of Republican officeholders, senior advisers, judges and appointees explicit permission and encouragement to believe that the country is on the verge of collapse.

The list of people making these arguments includes former officials in the Trump administration, some of whom are likely to be considered for top jobs in the event of a Trump restoration in 2024.

The ideas about the threat of an all-powerful totalitarian left and the dismal state of the country — even the most outlandish of them — are taken seriously by conservative politicians as well as prominent influencers on the right.

If Mr. Trump manages to win the presidency again in 2024, many of these intellectual catastrophists could be ready and willing to justify deeds that could well bring American liberal democracy to its knees.

Mr. Anton’s “Flight 93” essay originally appeared on a website with modest traffic, but two days later Rush Limbaugh was reading it aloud in its entirety on his radio show. The essay set the tone of life-or-death struggle (and related imagery) that is common among catastrophists.

Mr. Anton updated and amplified the argument in a 2021 book, “The Stakes: America at the Point of No Return.”

The prospect of Mr. Biden’s becoming president constituted an “existential threat,” Mr. Eastman said, to the survivability of the country. Would we “completely repudiate every one of our founding principles” and allow ourselves to be “eradicated”? Those were the stakes, as he viewed them.

Once a thinker begins to conceive of politics as a pitched battle between the righteous and those who seek the country’s outright annihilation, extraordinary possibilities open up.

in May 2021, Mr. Anton came to conduct a two-hour podcast with a far-right Silicon Valley tech guru and self-described “monarchist,” Curtis Yarvin, in which the two agreed that the American “regime” is today most accurately described as a “theocratic oligarchy.” In that arrangement, an elite class of progressive “priests” ensconced in executive branch agencies, the universities, elite media and other leading institutions of civil society promulgate and enforce a distorted and self-serving version of reality that illegitimately justifies their rule.

It culminated in Mr. Yarvin sketching a scenario in which a would-be dictator he alternatively describes as “Caesar” and “Trump” defies the laws and norms of democratic transition and uses a “Trump app” to direct throngs of his supporters on the streets of the nation’s capital to do his bidding, insulating the would-be dictator from harm and the consequences of his democracy-defying acts.

Mr. Anton described Caesarism as one-man rule that emerges “after the decay of a republican order, when it can no longer function.”

he would prefer the country to embrace the principles of “1787 forever.” But if that is no longer possible, he said, the rule of a Caesar can be a necessary method to restore order.)

Those on the right primarily concerned about the fate of traditionalist Christian morals and worship in the United States insist that we already live in a regime that oppresses and brutalizes religious believers and conservatives. And they make those charges in a theologically inflected idiom that’s meant to address and amplify the right’s intense worries about persecution by progressives.

Among the most extreme catastrophists writing in this vein is Stephen Wolfe, whose book “The Case for Christian Nationalism” calls for a “just revolution” against America’s “gynocracy” (rule by women) that emasculates men, persuading them to affirm “feminine virtues, such as empathy, fairness and equality.” In its place, Mr. Wolfe proposes the installation of a “Christian prince,” or a form of “theocratic Caesarism.”

Other authors aspire to greater nuance by calling the dictatorship weighing down on religious believers soft totalitarianism, usually under the rule of social-justice progressivism. These writers often draw direct parallels between the fate of devout Christians in the contemporary United States and the struggles of Eastern Europeans who sought to practice their faith but were harshly persecuted by Soviet tyranny

the most recent book by the writer Rod Dreher, “Live Not by Lies: A Manual for Christian Dissidents.”

Patrick Deneen of the University of Notre Dame offers the most elaborate and intellectually sophisticated response in his recent book, “Regime Change: Toward a Postliberal Future.”

“Regime Change” is a much darker book that goes well beyond diagnosing America’s ills to propose what sounds, in certain passages, like a radical cure.

The source of these maladies, Mr. Deneen claims, is liberalism, which until recently has dominated both political parties in the United States, imposing an ideology of individual rights and historical progress on the country from above. This ideology, he says, denigrates tradition, faith, authority and community.

Growing numbers of Americans supposedly reject this outlook, demanding a postliberal government and social, cultural and economic order — basically, hard-right policies on religious and moral issues and hard left on economics. But the forces of liberalism are entrenched on the center left and center right, using every power at their disposal to prevent regime change.

In some passages, he advocates a “peaceful but vigorous overthrow of a corrupt and corrupting liberal ruling class” and proposes modest reforms to replace i

in other passages, Mr. Deneen goes much further, describing the separation of church and state as a “totalitarian undertaking” that must be reversed so that American public life can be fully integrated with conservative forms of Christianit

He even affirmatively quotes a passage from Machiavelli in which he talks of the need to use “extralegal and almost bestial” forms of resistance, including “mobs running through the streets,” in order to topple the powers that be.

Mr. Deneen and other discontented intellectuals of the religious right can perhaps be most accurately described as political reactionaries looking to undertake a revolutionary act in reverse.

Costin Alamariu, the person generally understood to be writing under the pseudonym Bronze Age Pervert.

He self-published a book in 2018, “Bronze Age Mindset,” which follows Friedrich Nietzsche and other authors beloved by the European far right in proclaiming that Western civilization itself is on the verge of collapse, its greatest achievements far in the past, its present a “garbage world” in an advanced state of decay.

All around us, Mr. Alamariu declares, greatness and beauty are under assault. Who are its enemies? Women, for one. (“It took 100 years of women in public life for them to almost totally destroy a civilization.”) Then there’s belief in democratic equality. (“I believe that democracy is the final cause of all the political problems I describe.”)

But blame must most of all be laid at the feet of the creature Mr. Alamariu calls the “bugman,” a term he uses to describe a majority of human beings alive today. This insectlike infestation venerates mediocrity and is “motivated by a titanic hatred of the well-turned-out and beautiful.”

Mr. Alamariu proposes breeding great men of strength who model themselves on pirates, disregarding laws and norms, plundering and taking anything they want and ultimately installing themselves as absolute rulers over the rest of us.

“Now imagine a man of Trump’s charisma, but who is not merely beholden to the generals, but one of them, and able to rule and intimidate them as well as seduce the many. … Caesars and Napoleons are sure to follow.”

In a recent essay, Mr. Alamariu wrote: “I believe in fascism or ‘something worse’ …. I believe in rule by a military caste of men who would be able to guide society toward a morality of eugenics.”

Mr. Alamariu’s recently self-published doctoral dissertation reached No. 23 on Amazon sitewide in mid-September. Among those on the right treating the author as a friend, ally or interlocutor worthy of respectful engagement are the prominent activist Christopher Rufo, the author Richard Hanania and the economist-blogger Tyler Cowen.

These writers are giving Republican elites permission and encouragement to do things that just a few years ago would have been considered unthinkable.

In a second term, Mr. Trump’s ambition is to fire tens of thousands of career civil servants throughout the federal bureaucracy and replace them with loyalists. He also reportedly plans to staff the executive branch with more aggressive right-wing lawyers. These would surely be people unwaveringly devoted to the president and his agenda as well as the danger the Democratic Party supposedly poses to the survival of the United States.

These writers also exercise a powerful influence on media personalities with large audiences. Tucker Carlson has interviewed Curtis Yarvin and declared that with regard to the 2024 election, “everything is at stake. What wouldn’t they do? What haven’t they done? How will you prepare yourself?”

Other right-wing influencers with large followings assert more bluntly that if conservatives lose in 2024, they will be hunted down and murdered by the regime.

It’s important that we respond to such statements by pointing out there is literally no evidence to support them. Other intellectual catastrophists are likewise wrong to suggest the country is ruled by a progressive tyranny, and we can know this because people on the right increasingly say such things while facing no legal consequences at all.

The question, then, is why the intellectual catastrophists have gotten to this point — and why others on the right are listening to them. The answer, I think, is an intense dislike of what America has become, combined with panic about the right’s ability to win sufficient power in the democratic arena to force a decisive change.

In refusing to accept that deal, many of the right’s most prominent writers are ceasing to behave like citizens, who must be willing to share rule with others, in favor of thinking and acting like commissars eager to serve a strongman.

It tweaked its algorithm to boost authoritative sources in the news feed and turned off recommendations to join groups based around political or social issues. Facebook is reversing some of these steps now, but it cannot make people forget this toolbox exists in the future

Nothing symbolizes this shift as neatly as Facebook’s decision in October (and Twitter’s shortly after) to start banning Holocaust denial. Almost exactly a year earlier, Zuckerberg had proudly tied himself to the First Amendment in a widely publicized “stand for free expression” at Georgetown University.

The evolution continues. Facebook announced earlier this month that it will join platforms such as YouTube and TikTok in removing, not merely labeling or down-ranking, false claims about COVID-19 vaccines.

the pandemic also showed that complete neutrality is impossible. Even though it’s not clear that removing content outright is the best way to correct misperceptions, Facebook and other platforms plainly want to signal that, at least in the current crisis, they don’t want to be seen as feeding people information that might kill them.

As platforms grow more comfortable with their power, they are recognizing that they have options beyond taking posts down or leaving them up. In addition to warning labels, Facebook implemented other “break glass” measures to stem misinformation as the election approached.

Down-ranking, labeling, or deleting content on an internet platform does not address the social or political circumstances that caused it to be posted in the first place

Content moderation comes to every content platform eventually, and platforms are starting to realize this faster than ever.

Platforms don’t deserve praise for belatedly noticing dumpster fires that they helped create and affixing unobtrusive labels to them

Warning labels for misinformation might make some commentators feel a little better, but whether labels actually do much to contain the spread of false information is still unknown.

News reporting suggests that insiders at Facebook knew they could and should do more about misinformation, but higher-ups vetoed their ideas. YouTube barely acted to stem the flood of misinformation about election results on its platform.

When internet platforms announce new policies, assessing whether they can and will enforce them consistently has always been difficult. In essence, the companies are grading their own work. But too often what can be gleaned from the outside suggests that they’re failing.

And if 2020 finally made clear to platforms the need for greater content moderation, it also exposed the inevitable limits of content moderation.

Even before the pandemic, YouTube had begun adjusting its recommendation algorithm to reduce the spread of borderline and harmful content, and is introducing pop-up nudges to encourage user

even the most powerful platform will never be able to fully compensate for the failures of other governing institutions or be able to stop the leader of the free world from constructing an alternative reality when a whole media ecosystem is ready and willing to enable him. As Renée DiResta wrote in The Atlantic last month, “reducing the supply of misinformation doesn’t eliminate the demand.”

Even so, this year’s events showed that nothing is innate, inevitable, or immutable about platforms as they currently exist. The possibilities for what they might become—and what role they will play in society—are limited more by imagination than any fixed technological constraint, and the companies appear more willing to experiment than ever.

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.”

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

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

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

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

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

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

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

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

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

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

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

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

Nonviolence.

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

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

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

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

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

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

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

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

Sometimes Black students must be protected not only from words, but words that sound like other words. In 2020, Greg Patton was suspended from teaching a class in communications at the University of Southern California. The reason was that one of his lectures included noting that in Mandarin, a hesitation term is “nèi ge,” which means “that …” and has nothing to do, of course, with the N-word. Several Black students said they felt injured by experiencing this word in the class.

The offense can even be 100 years in the past. In 2021 at the University of Wisconsin, Madison, some Black students were upset when walking past a boulder on campus that was referred to as a “niggerhead” by a newspaper reporter in 1925, when that term was common for large, dark rocks. The school had the boulder removed.

In cases like those last two, it seems that Black students are being taught a performed kind of delicacy. If you can’t bear walking past a rock someone called a dirty name 100 years ago, how are you going to deal with life?

In my view, the solution is not to decide whether to penalize all hate speech or to allow all of it regardless of whom it is addressed to. Administrators should certainly decry and penalize not just antisemitism but racism on campuses when it is severe and pervasive and constitutes conduct.

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.