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In the late 1990s, the sociologists Kathryn Edin and Maria Kefalas interviewed 162 low-income single mothers in Camden, N.J., and Philadelphia to understand why they had children without being married. “Money is seldom the primary reason” why mothers say they are no longer with their children’s fathers. Instead, mothers point to “far more serious” offenses: “It is the drug and alcohol abuse, the criminal behavior and consequent incarceration, the repeated infidelity, and the patterns of intimate violence that are the villains looming largest in poor mothers’ accounts of relational failure.”

But it doesn’t take behavior this harmful to discourage marriage; often, simple compatibility or constancy can be elusive.

Ms. Camino, for her part, has dabbled in dating since her partner left, but hasn’t yet met anyone who shares her values, someone who’s funny and — she hesitates to use the word “feminist” — but a man who won’t just roll his eyes and say something about being on her period whenever she voices an opinion.

“There are women that are just out here trying, and the men aren’t ready,” she told me. “They don’t care, most of them.” Who, exactly, is Ms. Camino supposed to marry?

For as long as people have been promoting marriage, they have also been observing that a good man is hard to find

what was once dismissed as the complaint of “picky” women is now supported by a raft of data

The same pundits plugging marriage also bemoan the crisis among men and boys, what has come to be known as “male drift” — men turning away from college, dropping out of the work force, or failing to look after their health.

even this nod ignores the qualitative aspect of the dating experience — the part that’s hard to cover in surveys, or address with policy.

a senior fellow at the American Enterprise Institute who recently surveyed more than 5,000 Americans about dating and relationships, found that nearly half of college-educated women said they were single because they had trouble finding someone who meets their expectations, versus one-third of men.

For a variety of reasons — mixed messages from the broader culture about toughness and vulnerability, the activity-oriented nature of male friendships — it seems that by the time men begin dating, they are relatively “limited in their ability and willingness to be fully emotionally present and available,” he said.

Navigating interpersonal relationships in a time of evolving gender norms and expectations “requires a level of emotional sensitivity that I think some men probably just lack, or they don’t have the experience,

He had recently read about a high school creative writing assignment in which boys and girls were asked to imagine a day from the perspective of the opposite sex. While girls wrote detailed essays showing they had already spent significant time thinking about the subject, many boys simply refused to do the exercise, or did so resentfully

Mr. Cox likened that to heterosexual relationships today: “The girls do extra and the boys do little or nothing.”

educated women freeze their eggs because they’re unable to find a suitable male partner: Ms. Inhorn points to a large gap in the number of college-educated women versus college-educated men during their reproductive years — on the order of several million.

Ms. Inhorn’s book goes beyond these quantitative mismatches to document the qualitative experience of women who are actively searching for partners — the frustration, hurt and disappointment.

“Almost without exception,” she writes, “women in this study were ‘trying hard’ to find a loving partner,” mostly through dating sites and apps. Women in their late 30s reported “online ageism,” others described removing their Ph.D from their profiles so as not to intimidate potential dates; still others found that men were often commitment-averse.

Ms. Inhorn compiled a sort of taxonomy of cads, such as the “Alpha males” who “want to be challenged by work, not by their partners” or the “Polyamorous men” who claim “that their multiple attachments to women are all ‘committed.’” Her breakdown — table 1.1 in the book — reads like a rigorous academic version of all the complaints you’ve ever heard from your single female friends.

to truly address the decline in heterosexual marriage, we must attend to the details — to acknowledge the qualitative aspects of relationship formation

in particular, we should listen to the experiences of women who are attempting to find partners. We should care about the interior lives, not just the educational attainment or the employment status, of the men who could be those partners.

It requires taking the stories of single women seriously, and not treating them as punchlines — something for which there is little historical precedent, but which a handful of scholars are slowly beginning to do.

Lesson #5: Proportionality should be a guideline in war.

McNamara talks about the proportions of cities destroyed in Japan by the US before the dropping of the nuclear bomb, comparing the destroyed Japanese cities to similarly-sized cities in the US: Tokyo, roughly the size of New York City, was 51% destroyed; Toyama, the size of Chattanooga, was 99% destroyed; Nagoya, the size of Los Angeles, was 40% destroyed; Osaka, the size of Chicago, was 35% destroyed; Kobe, the size of Baltimore, was 55% destroyed; etc. He says LeMay once said that, had the United States lost the war, they would have been tried for war crimes, and agrees with this assessment.

Lesson #7: Belief and seeing are both often wrong. McNamara affirms Morris' framing of lesson 7 in relation to the Gulf of Tonkin incident: "We see what we want to believe."

Lesson #8: Be prepared to reexamine your reasoning. McNamara says that, even though the United States is the strongest nation in the world, it should never use that power unilaterally: "if we can't persuade nations with comparable values of the merit of our cause, we better reexamine our reasoning."

We, the richest nation in the world, have failed in our responsibility to our own poor and to the disadvantaged across the world to help them advance their welfare in the most fundamental terms of nutrition, literacy, health and employment.

we are not omniscient. If we cannot persuade other nations with similar interests and similar values of the merits of the proposed use of that power, we should not proceed unilaterally except in the unlikely requirement to defend directly the continental U.S., Alaska and Hawaii.

War is a blunt instrument by which to settle disputes between or within nations, and economic sanctions are rarely effective. Therefore, we should build a system of jurisprudence based on the International Court—that the U.S. has refused to support—which would hold individuals responsible for crimes against humanity.

If we are to deal effectively with terrorists across the globe, we must develop a sense of empathy—I don't mean "sympathy," but rather "understanding"—to counter their attacks on us and the Western World.

We underestimated the power of nationalism to motivate a people to fight and die for their beliefs and values.

Our misjudgments of friend and foe, alike, reflected our profound ignorance of the history, culture, and politics of the people in the area, and the personalities and habits of their leaders.

We failed then—and have since—to recognize the limitations of modern, high-technology military equipment, forces, and doctrine. We failed, as well, to adapt our military tactics to the task of winning the hearts and minds of people from a totally different culture.

We did not recognize that neither our people nor our leaders are omniscient. Our judgment of what is in another people's or country's best interest should be put to the test of open discussion in international forums. We do not have the God-given right to shape every nation in our image or as we choose.

We did not hold to the principle that U.S. military action … should be carried out only in conjunction with multinational forces supported fully (and not merely cosmetically) by the international community.

The economy that Hickel envisions would cease to pursue growth, green or otherwise. Materials and energy will still be consumed, and waste generated, but at much lower levels. All impacts on the natural world will be tethered to the question, “Growth for whom, and to what ends?” In place of an individualistic consumer economy, Hickel’s post-growth economy would direct itself toward the creation of public goods that allow the many to live well—mass transit, health care—rather than to keep a few in luxury.

A growing body of research reveals an inverse relationship between “happiness” and growth beyond a certain point.

In the rich countries, general contentment peaked in 1950, when GDP and real per capita incomes were fractions of their present size (and inequality near modern historic lows); degrowthers posit that similar happiness levels will be reclaimed on the way back down the economic mountain

Hickel describes a post-growth economy defined by stability and equality, and the freedom and leisure possible when the economy is no longer subservient to the god of growth

He estimates that the U.S. economy could be scaled down by as much as 65 percent while still improving the lives of its citizens. This includes the metric most often tied to celebrations of endless growth: life expectancy.

degrowth will entail a steep reduction across a much wider range of high-energy consumer goods. Keeping a global economy within safe ecological limits is a zero-sum game.

When limited resources are directed toward clean energy infrastructure, public health care, and regenerative agriculture, it will still be possible to build and power modern 24-hour hospitals in every city, but not to have Xbox consoles, two-car garages, and giant appliances in every home.

would have to redefine it, too.

The post-growth economy could not succeed solely by redistributing wealth; it would have to redefine it, too.

He argues that short-term growth would have to continue in those countries that have still not achieved the basic levels of sanitation, infrastructure, and education needed for a decent standard of living, to close the gap. Their larger goal, meanwhile, would be to break free from their historical role as a source of natural resources and cheap labor for the north.

For degrowth to be just, global, and effective, the sharpest reduction in consumption will have to come from the north, where the greatest damage to the planet is currently being done

Ecological economists generally agree that the safe outer limit is eight tons

One person in a low-income country has a materials footprint of roughly two tons per year, a measure of total raw materials consumed, including those embodied in imports. In lower-middle–income countries, that number is four tons; in upper-middle–income countries, 12 tons. In the high-income nations of North America, Europe, and Asia, the number leaps to 28

The wealthiest 20 percent of the human population is responsible for 90 percent of “overshoot” carbon in the atmosphere (that is, a level of carbon that exceeds the limit needed to keep global temperature rise below 2 degrees Celsius)

The planet’s richest one percent has a carbon footprint twice the size of the poorest half of the world’s population combined

For the global north, degrowth not only starts at home, it starts with the biggest houses.

Less Is More doesn’t end in a poetic appreciation for nature’s majesty, but by teasing out its implications for the political project of preserving a habitable planet. Hickel devotes much of the book to explaining that degrowth must be central to this project, promising not just survival, but real democracy, social abundance, and liberation.

Both involve broad social shifts away from private consumption and toward the production of shared public goods.

This beautiful coincidence overlaps with policy programs like the Green New Deal in important way

In July 1979, shortly after installing a set of solar panels over the West Wing, Jimmy Carter did something peculiar for a peacetime president. He asked Americans to sacrifice: to consume less, take public transit more, value community over material things, and buy bonds to fund domestic energy development, including solar

Next to Schumacher’s “Buddhist economics,” Debsian socialism was reformist tinkering. Schumacher didn’t see liberation as a matter of reshuffling the ownership and management structures of the smokestack-powered growth economy. He believed a deeper transformation was needed to maintain a livable planet. This would require new socioecological blueprints “designed for permanence.” As the left and the right battled for control over growth’s levers and spoils, Schumacher pointed out how both had become blind to the rise of growth as its own self-justifying, pan-ideological religion; its patterns of production and consumption, he observed, required “a degree of violence” that did not “fit into the laws of the universe.”

They determined that infinite growth was, in fact, impossible on a finite planet. Barring a major course correction, the team projected, growthism would result in an ecological systems breakdown sometime in the middle of the twenty-first century

This warning, detailed in the 1972 bestseller The Limits to Growth, has aged better than the scorn heaped on it

We are now witnessing what appears to be the beginnings of the collapse predicted nearly 50 years ago

In his new book, Less Is More, Jason Hickel, an anthropologist and journalist, attempts to bring a comprehensive critique of growth closer to the center of the conversation, arguing through a sweeping history of capitalism that it’s uncontrolled growth, not its controlled arrest and reversal, that is the preposterous concept.

This economic and political revolution was reinforced by a complementary scientific one that displaced the lingering animist cosmology of pre-capitalist Europe. The dualism of Francis Bacon and Descartes held reason to be distinct from and superior to matter.

The idea of limitless growth is a relatively recent one. In Less Is More, Hickel traces its origins to the enclosure of the European commons in the sixteenth century

Starving refugees were scattered and forced into a new economy defined by neo-feudal servitude and wage labor. Landowners, meanwhile, began amassing great stores of surplus wealth.

By the mid-1800s, a new “science” had arisen from these assumptions. Neoclassical economics fully abstracted the economy from the natural world. The economy was geared not toward the creation of a happy and prosperous society, but toward the perpetual growth of wealth as its own end, achieved in an inherently virtuous cycle of converting labor and resources into capital, to be accumulated and reinvested in faster and more productive conversions of labor and resources

This ideology subsumed and profaned notions about progress and morality held by the classical economists, until eventually the field even l

This process unfolded despite repeated warnings along the way. Classical economists like John Stuart Mill and, to a lesser extent, Adam Smith not only acknowledged the existence of natural limits to growth, but saw economic development as a phase; at some point, they believed, nations would create enough wealth to pursue other definitions of progres

the caveats issued by Simon Kuznets, father of the concept adopted in the twentieth century as growth’s universal and signature metric: gross domestic product. Kuznets, Hickel points out, “warned that we should never use GDP as a normal measure of economic progress,” because GDP does not distinguish between productive and destructive behavior

Most people encounter the growth debate, if they encounter it at all, through the idea of “green growth.

This is a vision for our collective future based on the belief that technological advance will drastically reduce the amount of raw materials needed to sustain growth—a process known as dematerialization—and “decouple” growing GDP from its ecological impacts.

boosters of the idea point to the transition by rich countries from manufacturing to service-based economies, as well as efficiency gains in energy and in the use of materials

The belief that green growth will save us, also known as “ecomodernism” or “ecopragmatism,” has become a trendy article of faith among elites who acknowledge climate change and the dangers of breaching ecological boundaries

n 2017, Barack Obama threw his support behind the idea in an article for Science magazine, maintaining that signs of decoupling in major economies “should put to rest the argument that combatting climate change requires accepting lower growth or a lower standard of living.”

The argument that capitalism can grow itself out of the present crisis may be soothing to those who like the world as it is. It also relies on the kind of accounting tricks and rejection of reality

By only counting the emissions created within a country that imports most of its cars, washing machines, and computers, you end up pushing the emissions related to their production off the books. When you factor them back in, the picture is much less green. A number of recent studies show no evidence of meaningful decoupling—in energy or materials—even as the world increases its use of renewable energy and finds ways to use some materials more efficiently.

Green growth, Hickel concludes, is an ecologically incoherent “fairy tale.”

consider what the ecomodernist position asks us to believe. The current system requires annual growth of roughly 3 percent to avoid the shock of recession. This means doubling the size of the economy every 23 years

he economy of 2000 must be 20 times larger in the year 2100, and 370 times larger in the year 2200.

Hickel is less interested in the macroeconomic details of this future than are growth critics based in economics departments, like Tim Jackson and Kate Raworth, and more focused on the leisure, security, and general human flourish

he makes an alluring case that degrowth does not require anything like the “command-and-control fiasco of the Soviet Union, or some back-to-the-caves, hair-shirted disaster of voluntary impoverishment.”

Attaining the benefits of the post-growth economy would, however, require what the present consumer society considers “sacrifices.

it’s not clear how many of them are ready to give up its superficial pleasures enabled by consumer debt

Among nations, there’s also the question of fairness: Wouldn’t it be unjust to impose degrowth across the world, when it’s disproportionately the countries of the global north that have spent centuries burning through the planet’s resources?

This output tracks to the one percent’s share of global wealth—a number equal to the GDP of the bottom 169 countries.

Even if you accept the argument that inequality would be best addressed by more centuries of trickle-down growth, you keep running up against the simple fact of its impossibility. Even just one more century of growth—which so far has shown no sign of taking a less destructive form—will require multiple earths

Hickel is serious about bringing the system critiques of E.F. Schumacher and others out of their traditional cloisters and into the streets, and has sought allies in this effort

emphasize what Hickel calls the “beautiful coincidence” of degrowth: that “what we need to do to survive is the same as what we need to do to have better lives.”

Both are internationalist in outlook, and see the world through a lens of climate justice as well as climate equilibrium.

that is, communicating the many benefits of moving beyond the insecurity and terrors of the current system, and building a new society that is sustainable, stable, democratic, and fundamentally better in every way.

But I was constantly confronted by the contradictions embedded in American leadership, the knowledge that our government arms autocrats while its rhetoric appeals to the dissidents trying to overthrow them or that our nation enforces rules — for the conduct of war, the resolution of disputes and the flow of commerce — while insisting that America be excused from following them when they become inconvenient.

He helped extend the war in Vietnam and expand it to Cambodia and Laos, where the United States rained down more bombs than it dropped on Germany and Japan in World War II. That bombing — often indiscriminately massacring civilians — did nothing to improve the terms on which the Vietnam War ended; if anything, it just indicated the lengths to which the United States would go to express its displeasure at losing.

For decades, he was a coveted guest at gatherings of statesmen and tycoons, perhaps because he could always provide an intellectual framework for why some people are powerful and justified in wielding power

Mr. Kissinger was fixated on credibility, the idea that America must impose a price on those who ignore our demands to shape the decisions of others in the future. It’s hard to see how the bombing of Laos, the coup in Chile or the killings in East Pakistan (now Bangladesh) contributed to the outcome of the Cold War.

But Mr. Kissinger’s unsentimental view of global affairs allowed him to achieve consequential breakthroughs with autocratic countries closer to America’s weight class — a détente with the Soviet Union that reduced the escalatory momentum of the arms race and an opening to China that deepened the Sino-Soviet split, integrated the People’s Republic of China into the global order and prefaced Chinese reforms that lifted hundreds of millions of people out of poverty.

From a strategic standpoint, Mr. Kissinger surely knew, being a superpower carried with it a cavernous margin of error that can be forgiven by history

Now history has come full circle. Around the world, we see a resurgence of autocracy and ethnonationalism, most acutely in Russia’s war against Ukraine

Just a few decades after the end of the Vietnam War, the same countries we’d bombed were seeking expanded trade with the United States. Bangladesh and East Timor are now independent nations that receive American assistance. Chile is governed by a millennial socialist whose minister of defense is Mr. Allende’s granddaughter.

Superpowers do what they must. The wheel of history turns. When and where you live determines whether you get crushed or lifted by it

But that worldview mistakes cynicism — or realism — for wisdom. The story, what it’s all about, matters. Ultimately, the Berlin Wall came down not because of chess moves made on the board of a great game but rather because people in the East wanted to live like the people in the West.

Economics, popular culture and social movements mattered. Despite all our flaws, we had a better system and story.

Credibility, after all, is not just about whether you punish an adversary to send a message to another; it’s also about whether you are what you say you are. No one can expect perfection in the affairs of state any more than in relations among human beings.

But the United States has paid a price for its hypocrisy, though it’s harder to measure than the outcome of a war or negotiation. Over the decades, our story about democracy has come to ring hollow to a growing number of people who can point to the places where our actions drained our words of meaning and “democracy” just sounded like an extension of American interests.

Similarly, our insistence on a rules-based international order has been ignored by strongmen who point to America’s sins to justify their own.

The generous defense is that Mr. Kissinger represented an ethos that saw the ends (the defeat of the Soviet Union and revolutionary Communism) as justifying the means. But for huge swaths of the world, this mind-set carried a brutal message that America has often conveyed to its own marginalized populations: We care about democracy for us, not for them.

In Gaza the United States has supported an Israeli military operation that has killed civilians at a pace that has once again suggested to much of the world that we are selective in our embrace of international laws and norms.

Meanwhile, at home, we see how democracy has become subordinate to the pursuit of power within a chunk of the Republican Party.

This is where cynicism can lead. Because when there is no higher aspiration, no story to give meaning to our actions, politics and geopolitics become merely a zero-sum game. In that kind of world, might makes right.

his is also a cautionary tale. As imperfect as we are, the United States needs our story to survive. It’s what holds together a multiracial democracy at home and differentiates us from Russia and China abroad.

That story insists that a child in Laos is equal in dignity and worth to our children and that the people of Chile have the same right of self-determination as we do. For the United States, that must be a part of national security. We forget that at our peril.

his political antennae have told him, correctly in my view, that the Conservative Party is going to lose the next election and then undergo a major reorientation that will see its patrician liberal wing of upper-class internationalists getting marginalised and then dropping out.

In their place will emerge an earthier, more provincial pro-nation state party that is genuinely socially conservative, particularly around the totemic issue of border control.

As immigration minister he looked into the future of migration trends and realised that the international arrangements currently in place are completely unsustainable and that the British public will turn towards a Nigel Farage political vehicle to remedy things if the Tories do not. 

Blue Wall, Home Counties Tory liberalism of a kind that prioritises foreign aid over domestic levelling up or international law over basic border control is destined to become so much political roadkill. The actual Liberal Democrats or Keir Starmer’s new Blairism will hoover up voters who believe in that stuff.

Jenrick has detected both the electoral and intellectual power of scepticism about mass, uncontrolled migration.

The National or ‘New’ Conservative movement, which prioritises the ideas of citizen preference in public services and social housing, strong law and order, pro-family policy, resisting Woke onslaughts from the identitarian left, and the enhancement of social solidarity is the coming force.

It will either take a controlling interest in the Tory party or create a party of its own – perhaps in conjunction with senior voices in Reform or even the SDP – after a calamitous Conservative defeat next year. Either way, a big shake-out is coming and the smart people are turning right

The problem is never guns. The problem is abortions. (“When you break up the nuclear family, when you tell a generation of people that life has no value, no meaning, then you do wind up with school shooters.”)

The problem is not guns; it is teaching evolution. It is the theories of Charles Darwin! “Because we’ve taught a whole generation — a couple of generations now — of Americans, that there’s no right or wrong, that it’s about survival of the fittest, and [that] you evolve from the primordial slime. Why is that life of any sacred value? Because there’s nobody sacred to whom it’s owed.”

But the problem is never the gun. Hearts stop all the time, for myriad reasons. They are vulnerable to poverty and despair and anxiety, and the United States has all of those in ample supply.

Obviously the problem is the human heart. The human heart cannot stand the strain of living in the United States (a nice place, were it not for the nagging suspicion that any time you gather in a public place you might be gruesomely murdered with a gun). The human heart was not built for this low whine of anxious terror.

The problem is not guns. It’s not weapons. We have to protect ourselves. (From what, Mike? From what?) We must have our guns, to protect ourselves. (Then what are we arming the police like this for? Why are they laden with all this military-grade equipment, if protecting myself is not something I’m supposed to be outsourcing to them?)

The problem is the human heart. It breaks a little bit each time we see another mass shooting. If only they were a harder target. That is the problem. That so many hearts are aching for something to change, for a framework of laws that does not accept gun violence as inevitable.

Mea culpa. For those past two decades, I’d prospered and thrived in the new political economy. And unharmed by automation or globalization or the new social contract, I’d effectively ignored the fact that the majority of my fellow Americans weren’t prospering or thriving.

And I and my cohort of hippie-to-yuppie liberal Baby Boomers were complicit in that.

Economic inequality has reverted to the levels of a century ago and earlier, and so has economic insecurity, while economic immobility is almost certainly worse than it’s ever been.

What’s happened since the 1970s and ’80s didn’t just happen. It looks more like arson than a purely accidental fire, more like poisoning than a completely natural illness, more like a cheating of the many by the few—and although I’ve always been predisposed to disbelieve conspiracy theories, this amounts to a long-standing and well-executed conspiracy, not especially secret, by the leaders of the capitalist class, at the expense of everyone else.

In 40 years, the share of wealth owned by our richest 1 percent has doubled, the collective net worth of the bottom half has dropped to almost zero, the median weekly pay for a full-time worker has increased by just 0.1 percent a year, only the incomes of the top 10 percent have grown in sync with the economy, and so on

A union? Sure, fine. But I was talent. I was creative. I was an individual. College graduates tend to think of themselves that way, younger ones all the more, younger Baby Boomers at the time probably the most ever. And the intensified, all-encompassing individualism that blew up during the 1960s—I do my thing, and you do your thing—was not a mindset or temperament that necessarily reinforced feelings of solidarity with fellow workers or romantic feelings about unions.

Thrall was asked about his depictions of Israelis, and whether he had qualms about “humanizing the occupation.”

I don’t like the fact that the statement Nguyen signed gestured only vaguely at Hamas’s slaughter of Israeli civilians. In calling off his Friday evening appearance, 92NY, a Jewish organization, was playing by rules much of the left established, privileging sensitivity to traumatized communities ahead of the robust exchange of ideas.

“I was very glad to be asked that question,” Thrall told me. “Because that was absolutely the ambition of the book, to depict real people” rather than villains and saints.

if someone as evenhanded as Thrall now finds his talks being dropped, we’re in an especially repressive period. And in a time of war, particularly a war shrouded in fiercely competing narratives, free speech is more important than ever.

Thrall is not alone; in recent weeks several literary and cultural events by pro-Palestinian speakers or groups have been either scrapped or relocated.

And supporters of Israel are hardly alone in creating a censorious atmosphere; particularly on college campuses, it is Zionists who feel silenced and intimidated

Nevertheless, a commitment to free speech, like a commitment to human rights, shouldn’t depend on others reciprocating; such commitments are worth trying to maintain even in the face of unfairness

Something similar might be said about “The Maniac,” Benjamín Labatut’s new novel, whose designated Prometheus is the Hungarian-born polymath John von Neumann, a pioneer of A.I. as well as an originator of game theory.

both narratives are grounded in fact, using the lives and ideas of real people as fodder for allegory and attempting to write a new mythology of the modern world.

on Neumann and Oppenheimer were close contemporaries, born a year apart to prosperous, assimilated Jewish families in Budapest and New York. Von Neumann, conversant in theoretical physics, mathematics and analytic philosophy, worked for Oppenheimer at Los Alamos during the Manhattan Project. He spent most of his career at the Institute for Advanced Study, where Oppenheimer served as director after the war.

More than most intellectual bastions, the institute is a house of theory. The Promethean mad scientists of the 19th century were creatures of the laboratory, tinkering away at their infernal machines and homemade monsters. Their 20th-century counterparts were more likely to be found at the chalkboard, scratching out our future in charts, equations and lines of code.

MANIAC. The name was an acronym for “Mathematical Analyzer, Numerical Integrator and Computer,” which doesn’t sound like much of a threat. But von Neumann saw no limit to its potential. “If you tell me precisely what it is a machine cannot do,” he declared, “then I can always make a machine which will do just that.” MANIAC didn’t just represent a powerful new kind of machine, but “a new type of life.”

More than 200 years after the Shelleys, Prometheus is having another moment, one closer in spirit to Mary’s terrifying ambivalence than to Percy’s fulsome gratitude. As technological optimism curdles in the face of cyber-capitalist villainy, climate disaster and what even some of its proponents warn is the existential threat of A.I., that ancient fire looks less like an ember of divine ingenuity than the start of a conflagration. Prometheus is what we call our capacity for self-destruction.

Oppenheimer wasn’t a principal author of that theory. Those scientists, among them Niels Bohr, Erwin Schrödinger and Werner Heisenberg, were characters in Labatut’s previous novel, “When We Cease to Understand the World.” That book provides harrowing illumination of a zone where scientific insight becomes indistinguishable from madness or, perhaps, divine inspiration. The basic truths of the new science seem to explode all common sense: A particle is also a wave; one thing can be in many places at once; “scientific method and its object could no longer be prised apart.”

. Oppenheimer’s designation as Prometheus is precise. He snatched a spark of quantum insight from those divinities and handed it to Harry S. Truman and the U.S. Army Air Forces.

Labatut’s account of von Neumann is, if anything, more unsettling than “Oppenheimer.” We had decades to get used to the specter of nuclear annihilation, and since the end of the Cold War it has been overshadowed by other terrors. A.I., on the other hand, seems newly sprung from science fiction, and especially terrifying because we can’t quite grasp what it will become.

Von Neumann, who died in 1957, did not teach machines to play Go. But when asked “what it would take for a computer, or some other mechanical entity, to begin to think and behave like a human being,” he replied that “it would have to play, like a child.”

the intellectual drama of “Oppenheimer” — as distinct from the dramas of his personal life and his political fate — is about how abstraction becomes reality. The atomic bomb may be, for the soldiers and politicians, a powerful strategic tool in war and diplomacy. For the scientists, it’s something else: a proof of concept, a concrete manifestation of quantum theory.

If Oppenheimer took hold of the sacred fire of atomic power, von Neumann’s theft was bolder and perhaps more insidious: He stole a piece of the human essence. He’s not only a modern Prometheus; he’s a second Frankenstein, creator of an all but human, potentially more than human monster.

“Technological power as such is always an ambivalent achievement,” Labatut’s von Neumann writes toward the end of his life, “and science is neutral all through, providing only means of control applicable to any purpose, and indifferent to all. It is not the particularly perverse destructiveness of one specific invention that creates danger. The danger is intrinsic. For progress there is no cure.”

The largest declines in news attention over this period were found among working-age and pre-retirement Americans—for example, more than six in ten Americans ages 50-64 paid close attention to the news in 2016 compared to less than half in 2022.

around two-thirds of those ages 65 or older say they follow the news “all or most of the time” (down from a high of 81 percent in 2018) compared to less than one-fifth of those ages 18 to 29.

One-third of U.S. adults in 2022 said they follow the news at least “some of the time” while just under three in ten said they pay attention to the news “only now and then” or “hardly at all”.

it occurs in conjunction with shifts in media consumption towards digital devices, overall declining trust in the media and other institutions, and “high levels of news fatigue” across demographic groups.

It’s easier for people to do something else with their time and find more enjoyable distractions that don’t involve keeping up with the latest implosion in the House of Representatives, fights between dumb politicians, or what new conflict is flaring up in another part of the world.

Even as fewer people than ever are paying close attention to what is actually going on in America and the world, more and more Americans (and politicians) are piping off routinely—online, in the workplace, and in family gatherings—with hard-and-fast opinions about what it all means.

the net result is a more divisive and less informed citizenry coupled with a clear inability of major institutions and political parties in America to do anything cooperative on common economic, security, and social problems.

In a pluralistic society like ours—with important rights to freedom of speech and individual beliefs—it is not the job of government or others to coerce people into paying more or closer attention to what is going on.

But media companies, government bodies, and philanthropists could certainly put more money and effort into creating trustworthy news platforms for reporting important facts, presenting neutral analyses, exploring successes and failures in public policy, and hosting civil discussions about the important issues shaping the country.

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.

There are a few important take-aways. First, this one didn’t come from the government, it was a private case by a video game maker that sued Google over its terms for getting access to the Google Play app store for Android, decided not by a fancy judge with an Ivy League degree but by a jury of ordinary people in San Francisco. In other words, private litigation, the ‘ambulance-chasing’ lawyers, are vital parts of our justice system.

Second, juries matter, even if they are riskier for everyone involved. It’s kind of like a mini poll, and the culture is ahead of the cautious legal profession. This quick decision is a sharp contrast with the 6-month delay to an opinion in the search case that Judge Mehta sought in the D.C. trial.

Third, tying claims, which is a specific antitrust violation, are good law. Tying means forcing someone to buy an unrelated product in order to access the actual product they want to buy. The specific legal claim here was about how Google forced firms relying on its Google Play app store to also use its Google Play billing service, which charges an inflated price of 30% of the price of an app. Tying is pervasive throughout the economy, so you can expect more suits along these lines.

And finally, big tech is not above the law. This loss isn’t just the first antitrust failure for Google, it’s the first antitrust loss for any big tech firm. I hear a lot from skeptics that the fix is in, that the powerful will always win, that justice in our system is a mirage. But that just isn’t true. A jury of our peers just made that clear.

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.”