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Our vocabulary of commendation and condemnation is perpetually changing, but it has always relied on “thick” ethical terms, which combine description and evaluation.

“How to flourish” was one such topic, “flourishing” being a workable rendering of Aristotle’s term eudaimonia. We might also translate the term in the usual way, as “happiness,” as long as we suspend some of that word’s modern associations; eudaimonia wasn’t something that waxed and waned with our moods

For Aristotle, ethics was centrally concerned with how to live a good life: a flourishing existence was also a virtuous one.

“famously terse, often crabbed in their style.” Crabbed, fragmented, gappy: it can be a headache trying to match his pronouns to the nouns they refer to. Some of his arguments are missing crucial premises; others fail to spell out their conclusions.

Aristotle is obscure in other ways, too. His highbrow potshots at unnamed contemporaries, his pop-cultural references, must have tickled his aristocratic Athenian audience. But the people and the plays he referred to are now lost or forgotten. Some readers have found his writings “affectless,” stripped of any trace of a human voice, or of a beating human heart.

Flourishing is the ultimate goal of human life; a flourishing life is one that is lived in accord with the various “virtues” of the character and intellect (courage, moderation, wisdom, and so forth); a flourishing life also calls for friendships with good people and a certain measure of good fortune in the way of a decent income, health, and looks.

much of what it says can sound rather obvious

Virtue is not just about acting rightly but about feeling rightly. What’s best, Aristotle says, is “to have such feelings at the right time, at the right objects and people, with the right goal, and in the right manner.” Good luck figuring out what the “right time” or object or manner is.

Virtue is a state “consisting in a mean,” Aristotle maintains, and this mean “is defined by reference to reason, that is to say, to the reason by reference to which the prudent person would define it.

The phrase “prudent person” here renders the Greek phronimos, a person possessed of that special quality of mind which Aristotle called “phronesis.” But is Aristotle then saying that virtue consists in being disposed to act as the virtuous person does? That sounds true, but trivially so.

it helps to reckon with the role that habits of mind play in Aristotle’s account. Meyer’s translation of “phronesis” is “good judgment,” and the phrase nicely captures the combination of intelligence and experience which goes into acquiring it, along with the difficulty of reducing it to a set of explicit principles that anyone could apply mechanically, like an algorithm.

“good judgment” is an improvement on the old-fashioned and now misleading “prudence”; it’s also less clunky than another standby, “practical wisdom.”

The enormous role of judgment in Aristotle’s picture of how to live can sound, to modern readers thirsty for ethical guidance, like a cop-out. Especially when they might instead pick up a treatise by John Stuart Mill and find an elegantly simple principle for distinguishing right from wrong, or one by Kant, in which they will find at least three. They might, for that matter, look to Jordan Peterson, who conjures up as many as twelve.

the question of how to flourish could receive a gloomy answer from Aristotle: it may be too late to start trying. Why is that? Flourishing involves, among other things, performing actions that manifest virtues, which are qualities of character that enable us to perform what Aristotle calls our “characteristic activity

But how do we come to acquire these qualities of character, or what Meyer translates as “dispositions”? Aristotle answers, “From our regular practice.”

In a passage missing from Meyer’s ruthless abridgment, Aristotle warns, “We need to have been brought up in noble habits if we are to be adequate students of noble and just things. . . . For we begin from the that; if this is apparent enough to us, we can begin without also knowing why. Someone who is well brought up has the beginnings, or can easily acquire them.”

Aristotle suggests, more generally, that you should identify the vices you’re susceptible to and then “pull yourself away in the opposite direction, since by pulling hard against one fault, you get to the mean (as when straightening out warped planks).

Sold as a self-help manual in a culture accustomed to gurus promulgating “rules for living,” Aristotle’s ethics may come as a disappointment. But our disappointment may tell us more about ourselves than it does about Aristotle.

Michael Oakeshott wrote that “nobody supposes that the knowledge that belongs to the good cook is confined to what is or may be written down in the cookery book.” Proficiency in cooking is, of course, a matter of technique

My tutor’s fundamental pedagogical principle was that to teach a text meant being, at least for the duration of the tutorial, its most passionate champion. Every smug undergraduate exposé of a fallacy would be immediately countered with a robust defense of Aristotle’s reasoning.

“How to read Aristotle? Slowly.”

I was never slow enough. There was always another nuance, another textual knot to unravel

Sometimes we acquire our skills by repeatedly applying a rule—following a recipe—but when we succeed what we become are not good followers of recipes but good cooks. Through practice, as Aristotle would have said, we acquire judgment.

What we were doing with this historical text wasn’t history but philosophy. We were reading it not for what it might reveal about an exotic culture but for the timelessly important truths it might contain—an attitude at odds with the relativism endemic in the rest of the humanities.

There is no shortcut to understanding Aristotle, no recipe. You get good at reading him by reading him, with others, slowly and often. Regular practice: for Aristotle, it’s how you get good generally.

“My parents taught me the difference between right and wrong,” he said, “and I can’t think what more there is to say about it.” The appropriate response, and the Aristotelian one, would be to agree with the spirit of the remark. There is such a thing as the difference between right and wrong. But reliably telling them apart takes experience, the company of wise friends, and the good luck of having been well brought u

we are all Aristotelians, most of the time, even when forces in our culture briefly persuade us that we are something else. Ethics remains what it was to the Greeks: a matter of being a person of a certain sort of sensibility, not of acting on “principles,” which one reserves for unusual situations of the kind that life sporadically throws up

That remains a truth about ethics even when we’ve adopted different terms for describing what type of person not to be: we don’t speak much these days of being “small-souled” or “intemperate,” but we do say a great deal about “douchebags,” “creeps,” and, yes, “assholes.

In one sense, it tells us nothing that the right thing to do is to act and feel as the person of good judgment does. In another sense, it tells us virtually everything that can be said at this level of generality.

If self-help means denying the role that the perceptions of others play in making us who we are, if it means a set of rules for living that remove the need for judgment, then we are better off without it.

Aristotle had little hope that a philosopher’s treatise could teach someone without much experience of life how to make the crucial ethical distinctions. We learn to spot an “asshole” from living; how else

when our own perceptions falter, we continue to do today exactly what Aristotle thought we should do. He asserts, in another significant remark that doesn’t make Meyer’s cut, that we should attend to the words of the old and experienced at least as much as we do to philosophical proofs: “these people see correctly because experience has given them their eye.”

Is it any surprise that the Internet is full of those who need help seeing rightly? Finding no friendly neighborhood phronimos to provide authoritative advice, you defer instead to the wisdom of an online community.

“The self-made man,” Oakeshott wrote, “is never literally self-made, but depends upon a certain kind of society and upon a large unrecognized inheritance.”

It points us in the right direction: toward the picture of a person with a certain character, certain habits of thinking and feeling, a certain level of self-knowledge and knowledge of other people.

We have long lived in a world desperate for formulas, simple answers to the simple question “What should I do?”

the algorithms, the tenets, the certificates are all attempts to solve the problem—which is everybody’s problem—of how not to be an asshole. Life would be a lot easier if there were rules, algorithms, and life hacks solving that problem once and for all. There aren’t.

At the heart of the Nicomachean Ethics is a claim that remains both edifying and chastening: phronesis doesn’t come that easy. Aristotle devised a theory that was vague in just the right places, one that left, intentionally, space to be filled in by life. 

Twenty-four centuries later, we’re still guided by the approach toward ethical life that Aristotle exemplified, one in which the basic question is not what we do but who we are

The Internet has no shortage of moralists and moralizers, but one ethical epicenter is surely the extraordinary, addictive subreddit called “Am I the Asshole?,” popularly abbreviated AITA

I believe most of us tell a story about our lives and then come to live within that story. You can’t know who you are unless you know how to tell a coherent story about yourself. You can know what to do next only if you know what story you are a part of

“A man is always a teller of tales,” the philosopher Jean-Paul Sartre observed. “He lives surrounded by his stories and the stories of others, he sees everything that happens to him through them, and he tries to live his own life as if he were telling a story.”

The story Musk came to inhabit is one of the oldest in our civilization: A male hero of uncertain reputation emerges from an obscure place to save a doomed people through acts of daring

It is the story of Moses, Jesus, Superman, John Wayne westerns, Luke Skywalker, Harry Potter and the Lord of the Rings.

“While other entrepreneurs struggled to develop a worldview, he developed a cosmic view,

Musk’s self-conception is that he is building companies to save humanity, according to Isaacson. SpaceX is to make humans a multiplanetary species, so we can escape to Mars if something apocalyptic happens to earth. Tesla’s mission is to move humanity past a hydrocarbon economy, toward a sustainable future. His new firm xAI is there to help prevent artificial intelligence from taking over the world. Neuralink, which embeds technology into people’s brains, is there to help the blind see and the paralyzed walk.

Sometimes the story Musk tells about himself seems so grandiose it enters the realm of epic myth.

A person so consumed by a myth is not seeking to be conventionally successful, Dennis Ford argues in his book “The Search for Meaning”; he or she is trying “to be faithful to the mythic pattern.”

A person within this mythic consciousness can easily distort reality, confabulate and lie. Such a person can have the grandiose sense that he is indispensable to our species

Musk’s perennial crisis/urgency mentality, which drives him to behave as a craptaculous jerk to the people around him and serves as a rationalization for when he does, also fits.

People who have met Musk sometimes say it’s as if he is not a fully rounded human being, but seems like a character playing a role.

Perhaps it’s because he is still inhabiting an adventure story.

Musk’s apparent attachment to the hero myth seems to both make him fearless and also frequently a kind of monster. The mythic mind is a self-involved mind, which can never quite regard other people as being as important as the hero/self

the Musk of Isaacson’s book is on a series of epic quests — and is complex enough to be simultaneously hero and villain.

The AI boosters emphasized the incredible potential of their innovation, and Netanyahu raised practical objections to their enthusiasm. They cited futurists such as Ray Kurzweil to paint a bright picture of a post-AI world; Netanyahu cited the Bible and the medieval Jewish philosopher Maimonides to caution against upending human institutions and subordinating our existence to machines.

Musk matter-of-factly explained that the “very positive scenario of AI” is “actually in a lot of ways a description of heaven,” where “you can have whatever you want, you don’t need to work, you have no obligations, any illness you have can be cured,” and death is “a choice.” Netanyahu incredulously retorted, “You want this world?”

By the time the panel began to wind down, the Israeli leader had seemingly made up his mind. “This is like having nuclear technology in the Stone Age,” he said. “The pace of development [is] outpacing what solutions we need to put in place to maximize the benefits and limit the risks.”

Netanyahu was a naysayer about the Arab Spring, unwilling to join the rapturous ranks of hopeful politicians, activists, and democracy advocates. But he was also right.

This was less because he is a prophet and more because he is a pessimist. When it comes to grandiose predictions about a better tomorrow—whether through peace with the Palestinians, a nuclear deal with Iran, or the advent of artificial intelligence—Netanyahu always bets against. Informed by a dark reading of Jewish history, he is a cynic about human nature and a skeptic of human progress.

fter all, no matter how far civilization has advanced, it has always found ways to persecute the powerless, most notably, in his mind, the Jews. For Netanyahu, the arc of history is long, and it bends toward whoever is bending it.

This is why the Israeli leader puts little stock in utopian promises, whether they are made by progressive internationalists or Silicon Valley futurists, and places his trust in hard power instead

“The weak crumble, are slaughtered and are erased from history while the strong, for good or for ill, survive. The strong are respected, and alliances are made with the strong, and in the end peace is made with the strong.”

To his many critics, myself included, Netanyahu’s refusal to envision a different future makes him a “creature of the bunker,” perpetually governed by fear. Although his pessimism may sometimes be vindicated, it also holds his country hostag

In other words, the same cynicism that drives Netanyahu’s reactionary politics is the thing that makes him an astute interrogator of AI and its promoters. Just as he doesn’t trust others not to use their power to endanger Jews, he doesn’t trust AI companies or AI itself to police its rapidly growing capabilities.

ather than yet another history book telling you how humanity got here, they take their respective disciplines to task for dealing in myths.

this thought-provoking book is armed to the teeth with fascinating ideas and interpretations that go against mainstream thinking

Colonisation exposed us to new ideas that shocked and confused us. Graeber & Wengrow focus on the French coming into contact with Native Americans in Canada, and in particular on Wendat Confederacy philosopher–statesman Kandiaronk as an example of European traders, missionaries, and intellectuals debating with, and being criticized by indigenous people. Historians have downplayed how much these encounters shaped Enlightenment ideas.

Its legacy, shaped via several iterations, is the modern textbook narrative: hunter-gathering was replaced by pastoralism and then farming; the agricultural revolution resulted in larger populations producing material surpluses; these allowed for specialist occupations but also needed bureaucracies to share and administer them to everyone; and this top-down control led to today’s nation states. Ta-daa!

And cities did not automatically imply social stratification. The Dawn of Everything fascinates with its numerous examples of large settlements without ruling classes, such as Ukrainian mega-sites, the Harappan civilization, or Mexican city-states.

ake agriculture. Rather than humans enthusiastically entering into what Harari in Sapiens called a Faustian bargain with crops, there were many pathways and responses

Experiments show that plant domestication could have been achieved in as little as 20–30 years, so the fact that cereal domestication here took some 3,000 years questions the notion of an agricultural “revolution”. Lastly, this book includes many examples of areas where agriculture was purposefully rejected. Designating such times and places as “pre-agricultural” is misleading, write the authors, they were anti-agricultural.

The idea that agriculture led to large states similarly needs revision

correlation is not causation, and some 15–20 additional centres of domestication have since been identified that followed different paths. Some cities have previously remained hidden in the sediments of ancient river deltas until revealed by modern remote-sensing technology.

“extensive agriculture may thus have been an outcome, not a cause, of urbanization”

this simplistic tale of progress ignores and downplays that there was nothing linear or inevitable about where we have ended up.

These instead relied on collective decision-making through assemblies or councils, which questions some of the assumptions of evolutionary psychology about scale: that larger human groups require complex (i.e. hierarchical) systems to organize them.

e what is staring them in the face

humans have always been very capable of consciously experimenting with different social arrangements. And—this is rarely acknowledged—they did so on a seasonal basis, spending e.g. part of the year settled in large communal groups under a leader, and another part as small, independently roving bands.

Throughout, Graeber & Wengrow convincingly argue that the only thing we can say about our ancestors is that “there is no single pattern. The only consistent phenomenon is the very fact of alteration […] If human beings, through most of our history, have moved back and forth fluidly between different social arrangements […] maybe the real question should be ‘how did we get stuck?

Next to criticism, the authors put out some interesting ideas of their own, of which I want to quickly highlight two.

The first is that some of the observed variations in social arrangements resulted from schismogenesis. Anthropologist Gregory Bateson coined this term in the 1930s to describe how people define themselves against or in opposition to others, adopting behaviours and attitudes that are different.

The second idea is that states can be described in terms of three elementary forms of domination: control of violence, control of information, and individual charisma, which express themselves as sovereignty, administration, and competitive politics.

Asking which past society most resembles today’s is the wrong question to ask. It risks slipping into an exercise in retrofitting, “which makes us scour the ancient world for embryonic versions of our modern nation states”

I have left unmentioned several other topics: the overlooked role of women, the legacy of Rousseau’s and Hobbes’s ideas, the origins of inequality and the flawed assumptions hiding behind that question

There are so many historical details and delights hiding between these covers that I was thoroughly enthralle

If you have any interest in big history, archaeology, or anthropology, this book is indispensable. I am confident that the questions and critiques raised here will remain relevant for a long time to come.

I was particularly impressed by the in-depth critique by worbsintowords on his YouTube channel What is Politics? of (so far) five videos

Over the years, we have seen huge setbacks to the progress of liberal and democratic institutions, with the rise of fascism and communism in the 1930s, or the military coups and oil crises of the 1960s and ’70s. And yet, liberal democracy has endured and come back repeatedly, because the alternatives are so bad. People across varied cultures do not like living under dictatorship, and they value their individual freedom. No authoritarian government presents a society that is, in the long term, more attractive than liberal democracy, and could therefore be considered the goal or endpoint of historical progress.

The philosopher Hegel coined the phrase the end of history to refer to the liberal state’s rise out of the French Revolution as the goal or direction toward which historical progress was trending. For many decades after that, Marxists would borrow from Hegel and assert that the true end of history would be a communist utopia. When I wrote an article in 1989 and a book in 1992 with this phrase in the title, I noted that the Marxist version was clearly wrong and that there didn’t seem to be a higher alternative to liberal democracy.

setbacks do not mean that the underlying narrative is wrong. None of the proffered alternatives look like they’re doing any better.

Liberal democracy will not make a comeback unless people are willing to struggle on its behalf. The problem is that many who grow up living in peaceful, prosperous liberal democracies begin to take their form of government for granted. Because they have never experienced an actual tyranny, they imagine that the democratically elected governments under which they live are themselves evil dictatorships conniving to take away their rights

Some of the phrases added to King’s answer appear to be taken significantly out of context, while others appear to be fabricated:

“We should remember that King was always more radical than we like to imagine or talk about,” Eig continued. “He was a Christian radical, and his radicalism came from a different place than Malcolm’s did, but they always had a lot in common. They always believed that you had to take radical steps to change America, to end racism, to create a country that lived up to the words of its promises.”

in another part of the transcript, Haley asks King about critics labeling him an “extremist,” to which King responded: “At first, it disturbed me. Then I began to consider that, yes, I would like to think myself an extremist — in the light of Christ-like spirit which made Jesus an extremist for love.”

So, too, does the view that the strongest defense of the humanities lies not in the appeal to their utility — that literature majors may find good jobs, that theaters may economically revitalize neighborhoods

— but rather in the appeal to their defiantly nonutilitarian character, so that individuals can know more than how things work, and develop their powers of discernment and judgment, their competence in matters of truth and goodness and beauty, to equip themselves adequately for the choices and the crucibles of private and public life.

We are not becoming transhumanists, obviously. We are too singular for the Singularity. But are we becoming posthumanists?

In American culture right now, as I say, the worldview that is ascendant may be described as posthumanism.

The posthumanism of the 1970s and 1980s was more insular, an academic affair of “theory,” an insurgency of professors; our posthumanism is a way of life, a social fate.

In “The Age of the Crisis of Man: Thought and Fiction in America, 1933-1973,” the gifted essayist Mark Greif, who reveals himself to be also a skillful historian of ideas, charts the history of the 20th-century reckonings with the definition of “man.

Here is his conclusion: “Anytime your inquiries lead you to say, ‘At this moment we must ask and decide who we fundamentally are, our solution and salvation must lie in a new picture of ourselves and humanity, this is our profound responsibility and a new opportunity’ — just stop.” Greif seems not to realize that his own book is a lasting monument to precisely such inquiry, and to its grandeur

“Answer, rather, the practical matters,” he counsels, in accordance with the current pragmatist orthodoxy. “Find the immediate actions necessary to achieve an aim.” But before an aim is achieved, should it not be justified? And the activity of justification may require a “picture of ourselves.” Don’t just stop. Think harder. Get it right.

Greif’s book is a prehistory of our predicament, of our own “crisis of man.” (The “man” is archaic, the “crisis” is not.) It recognizes that the intellectual history of modernity may be written in part as the epic tale of a series of rebellions against humanism

Who has not felt superior to humanism? It is the cheapest target of all: Humanism is sentimental, flabby, bourgeois, hypocritical, complacent, middlebrow, liberal, sanctimonious, constricting and often an alibi for power

what is humanism? For a start, humanism is not the antithesis of religion, as Pope Francis is exquisitely demonstrating

The worldview takes many forms: a philosophical claim about the centrality of humankind to the universe, and about the irreducibility of the human difference to any aspect of our animality

a methodological claim about the most illuminating way to explain history and human affairs, and about the essential inability of the natural sciences to offer a satisfactory explanation; a moral claim about the priority, and the universal nature, of certain values, not least tolerance and compassion

And posthumanism? It elects to understand the world in terms of impersonal forces and structures, and to deny the importance, and even the legitimacy, of human agency.

There have been humane posthumanists and there have been inhumane humanists. But the inhumanity of humanists may be refuted on the basis of their own worldview

the condemnation of cruelty toward “man the machine,” to borrow the old but enduring notion of an 18th-century French materialist, requires the importation of another framework of judgment. The same is true about universalism, which every critic of humanism has arraigned for its failure to live up to the promise of a perfect inclusiveness

there has never been a universalism that did not exclude. Yet the same is plainly the case about every particularism, which is nothing but a doctrine of exclusion; and the correction of particularism, the extension of its concept and its care, cannot be accomplished in its own name. It requires an idea from outside, an idea external to itself, a universalistic idea, a humanistic idea.

Asking universalism to keep faith with its own principles is a perennial activity of moral life. Asking particularism to keep faith with its own principles is asking for trouble.

there is no more urgent task for American intellectuals and writers than to think critically about the salience, even the tyranny, of technology in individual and collective life

Here is a humanist proposition for the age of Google: The processing of information is not the highest aim to which the human spirit can aspire, and neither is competitiveness in a global economy. The character of our society cannot be determined by engineers.

“Our very mastery seems to escape our mastery,” Michel Serres has anxiously remarked. “How can we dominate our domination; how can we master our own mastery?”

universal accessibility is not the end of the story, it is the beginning. The humanistic methods that were practiced before digitalization will be even more urgent after digitalization, because we will need help in navigating the unprecedented welter

Searches for keywords will not provide contexts for keywords. Patterns that are revealed by searches will not identify their own causes and reasons

The new order will not relieve us of the old burdens, and the old pleasures, of erudition and interpretation.

Is all this — is humanism — sentimental? But sentimentality is not always a counterfeit emotion. Sometimes sentiment is warranted by reality.

The persistence of humanism through the centuries, in the face of formidable intellectual and social obstacles, has been owed to the truth of its representations of our complexly beating hearts, and to the guidance that it has offered, in its variegated and conflicting versions, for a soulful and sensitive existence

a complacent humanist is a humanist who has not read his books closely, since they teach disquiet and difficulty. In a society rife with theories and practices that flatten and shrink and chill the human subject, the humanist is the dissenter.

Experts compare the moment to the early days of social media, a technology offering tantalizing new tools for politics — and unforeseen threats.

For years, those fears had largely been speculative because the technology to produce such fakes was too complicated, expensive and unsophisticated.

His spokesman later stressed that the post was in jest and clearly labeled A.I.-generated. His campaign said in a statement that its use of A.I. is to entertain and make political points, not deceive.

Researchers have long worried about the impact of A.I. on elections. The technology can deceive and confuse voters, casting doubt over what is real, adding to the disinformation that can be spread by social networks.

Much of the content has been clearly fake. But a few creations have toed the line of disinformation. The Massa campaign produced one “deepfake” video in which Mr. Milei explains how a market for human organs would work, something he has said philosophically fits in with his libertarian views.

So far, the A.I.-generated content shared by the campaigns in Argentina has either been labeled A.I. generated or is so clearly fabricated that it is unlikely it would deceive even the most credulous voters. Instead, the technology has supercharged the ability to create viral content that previously would have taken teams of graphic designers days or weeks to complete.

To do so, campaign engineers and artists fed photos of Argentina’s various political players into an open-source software called Stable Diffusion to train their own A.I. system so that it could create fake images of those real people. They can now quickly produce an image or video of more than a dozen top political players in Argentina doing almost anything they ask.

For Halloween, the Massa campaign told its A.I. to create a series of cartoonish images of Mr. Milei and his allies as zombies. The campaign also used A.I. to create a dramatic movie trailer, featuring Buenos Aires, Argentina’s capital, burning, Mr. Milei as an evil villain in a straitjacket and Mr. Massa as the hero who will save the country.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

Sometimes the methods of imposing it were brutal, scholars say. At school in many French colonies, children speaking in their mother tongue were beaten or forced to wear an object around their necks known as a “symbol” — often a smelly object or an animal bone.

Still, many African countries adopted French as their official language when they gained independence, in part to cement their national identities. Some even kept the “symbol” in place at school.

At the festival, Le Magnific and other standup comedians threw jibes in French and ridiculed one another’s accents, drawing laughter from the audience. It mattered little if a few words were lost in translation.

“What makes our humor Pan-African is the French language,” said the festival’s organizer, Mohamed Mustapha, known across West Africa by his stage name, Mamane. A standup comedian from Niger, Mamane has a daily comedy program listened to by millions around the world on Radio France Internationale.

“It’s about survival, if we want to resist against Nollywood,” he said, referring to Nigeria’s film industry, “and English-produced content.”

Today, more a third of Ivorians speak French, according to the International Organization of the Francophonie. In Tunisia and the Democratic Republic of Congo — the world’s largest French-speaking country — it is more than half.

But in many Francophone countries, governments struggle to hire enough French-speaking teachers.

Still, Ms. Quéméner said French had long escaped France’s control.“French is an African language and belongs to Africans,” she said. “The decentralization of the French language is a reality.”

At the Hip Hop Académie, a youth program founded by the rapper Grödash in a Paris suburb, teens and children scribbled lyrics on notepads, following instructions to mix French and foreign languages.

Hip-hop, now dominating the French music industry, is injecting new words, phrases and concepts from Africa into France’s suburbs and cities.

“Countless artists have democratized French music with African slang,” said Elvis Adidiema, a Congolese music executive with Sony Music Entertainment. “The French public, from all backgrounds, has become accustomed to those sounds.”

“French is about to make a big leap, and she’s wondering how it’s going to go,” Mr. Laferrière said of the French language. “But she’s excited about where she’s headed.”

“They, not she. They are now multiple versions of French that speak for themselves. And that is the greatest proof of its vitality.”

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