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“It is genius for the current consumer culture,” Christine Whelan, a clinical professor of consumer science at the University of Wisconsin at Madison, told me. “It encourages and then meets the need for the thing, so we then continue on the hedonic treadmill: Buy the latest thing we want and then have it delivered immediately and then buy the next latest thing.”

With traditional retail, “there’s the friction of having to go to the store, there’s the friction of will the store have it, there’s the friction of carrying it,” Whelan said. “There’s the friction of having to admit to another human being that you’re buying it. And when you remove the friction, you also remove a lot of individual self-control. The more you are in the ecosystem and the easier it is to make a purchase, the easier it is to say yes to your desire rather than no.”

“It used to be that being a consumer was all about choice,”

But now, “two-thirds of people start their product searches on Amazon.

Prime discourages comparison shopping—looking around is pointless when everything you need is right here—even as Amazon’s sheer breadth of products makes shoppers feel as if they have agency.

“Consumerism has become a key way that people have misidentified freedom,”

what Amazon represents is a corporate infrastructure that is increasingly directed at getting as many consumers as possible locked into a consumerist process—an Amazon consumer for life.”

Amazon offers steep discounts to college students and new parents, two groups that are highly likely to change their buying behavior. It keeps adding more discounts and goodies to the Prime bundle, making subscribing ever more appealing. And, in an especially sinister move, it makes quitting Prime maddeningly difficult.

the United States now has more Prime memberships than households. In 2020,

In 2019, Amazon shaved a full day off its delivery time, making one-day shipping the default, and also making Prime an even more tantalizing proposition: Why hop in the car for anything at all when you could get it delivered tomorrow, for free?

As subscription numbers grew through the 2010s, the revenue from them helped Amazon pump more money into building fulfillment centers (to get products to people even faster), acquiring new businesses (to control even more of the global economy), and adding more perks to the bundle (to encourage more people to sign up)

“Every decision we make is based upon the fact that Amazon can get these books cheaper and faster. The prevailing expectation is you can get anything online shipped for”— he scrunched his fingers into air quotes—“‘free,’ in one or two days. And there’s really only one company that can do that. They do that because they’re willing to push and exploit their workers.”

Thanks in large part to the revenue from Prime subscriptions and from the things subscribers buy, Amazon’s value has multiplied roughly 97 times, to $1.76 trillion, since the service was introduced. Amazon is the second-largest private employer in the United States, after Walmart, and it is responsible for roughly 40 percent of all e-commerce in the United States.

It controls hundreds of millions of square feet across the country and is opening more fulfillment centers all the time. It has acquired dozens of other companies, most recently the film studio MGM for $8.5 billion. Its cloud-computing operation, Amazon Web Services, is the largest of its kind and provides the plumbing for a vast swath of the internet, to a profit of $13.5 billion last year.

Amazon has entered some 40 million American homes in the form of the Alexa smart speaker, and some 150 million American pockets in the form of the Amazon app

“Amazon is a beast we’ve never seen before,” Alimahomed-Wilson told me. “Amazon powers our Zoom calls. It contracts with ICE. It’s in our neighborhoods. This is a very different thing than just being a large retailer, like Walmart or the Ford Motor Company.”

I find it useful to compare Big Tech to climate change, another force that is altering the destiny of everyone on Earth, forever. Both present themselves to us all the time in small ways—a creepy ad here, an uncommonly warm November there—but are so big, so abstract, so everywhere that they’re impossible for any one person to really understand

Both are the result of a decades-long, very human addiction to consumption and convenience that has been made grotesque and extreme by the incentives and mechanisms of the internet, market consolidation, and economic stratification

Both have primarily been advanced by a small handful of very big companies that are invested in making their machinations unseeable to the naked eye.

Speed and convenience aren’t actually free; they never are. Free shipping isn’t free either. It just obscures the real price.

Next-day shipping comes with tremendous costs: for labor and logistics and transportation and storage; for the people who pack your stuff into those smiling boxes and for the people who deliver them; for the planes and trucks and vans that carry them; for the warehouses that store them; for the software ensuring that everything really does get to your door on time, for air-conditioning and gas and cardboard and steel. Amazon—Prime in particular—has done a superlative job of making all those costs, all those moving parts, all those externalities invisible to the consumer.

The pandemic drove up demand for Amazon, and for labor: Last year, company profits shot up 70 percent, Bezos’s personal wealth grew by $70 billion, and 1,400 people a day joined the company’s workforce.

Amazon is so big that every sector of our economy has bent to respond to the new way of consuming that it invented. Prime isn’t just bad for Amazon’s workers—it’s bad for Target’s, and Walmart’s. It’s bad for the people behind the counter at your neighborhood hardware store and bookstore, if your neighborhood still has a hardware store and a bookstore. Amazon has accustomed shoppers to a pace and manner of buying that depends on a miracle of precision logistics even when it’s managed by one of the biggest companies on Earth. For the smaller guys, it’s downright impossible.

Amazon’s revenue from subscriptions alone—mostly Prime—was $25.2 billion, which is a 31 percent increase from the previous year

Just as abstaining from flying for moral reasons won’t stop sea-level rise, one person canceling Prime won’t do much of anything to a multinational corporation’s bottom line. “It’s statistically insignificant to Amazon. They’ll never feel it,” Caine told me. But, he said, “the small businesses in your neighborhood will absolutely feel the addition of a new customer. Individual choices do make a big difference to them.”

Whelan teaches a class at UW called Consuming Happiness, and she is fond of giving her students the adage that you can buy happiness—“if you spend your money in keeping with your values: spending prosocially, on experiences. Tons of research shows us this.”

The economist Thomas Malthus, now dismissed by mainstream economics as an interesting crank, is resurrected by Galor as the man who correctly saw that for millennia humanity had been trapped by its own fertility into subsistence, starvation and famine. As soon as material matters improved, the birthrate went up, so did the population, and the pressure on food resources exploded – returning humanity to starvation

great sections of Galor’s book are to be applauded

What broke the Malthusian armlock on humanity’s destiny, argues Galor, is the gradual quickening in the introduction of technologies that required mass education for their successful implementation. This triggered a virtuous circle of more innovation, more investment in education, more need to invest in the quality of children rather than quantity, so that birthrates declined sufficiently to allow living standards and life expectancy to rise. Because it was now rational to invest in children’s education rather than get them working, child labour and exploitation fell away

Above all he shows how cultural attitudes persist long after whatever concatenation of events brought them into being, so that countries and cultures that get ahead tend to stay ahead

He is scathing about the shock programmes of market liberalisation that accompanied the “Washington consensus”, ignorant of these persistent traits. Effective market economies can’t be built spontaneously in cultures that are hostile to the very conception.

his optimism about humanity shines through – prize its diversity, commit to educate its children and they will find their way to innovate and create a culture of growth

It’s a great way to look at the world, but a healthy recognition that power, capitalism, finance, the existence and structure of states and public philosophies – some right, some wrong – are all part of the brew would have made his account more realistic

Let’s start with the obvious: Israel has a right to defend itself, rescue the hostages, arrest and prosecute Hamas and engage in lawful armed combat with its enemy.

People claiming the Hamas attack is the ‘violence of the oppressed’ are deluded. Hamas rules Gaza like a mafia state: its operatives walk around neighbourhoods in twos, dressed in dark suits, prying into people’s business. They run the place on a mixture of terror, public service provision and the kudos of their fighters.

They are feared but there is widespread disrespect for them, especially among secular and nationalist sections of the population.

Paradoxically, the western ‘anti-imperialists’ trying to apologise for the terror attack, and the Israeli right calling for retribution against civilians, both need to identify Hamas with the Palestinian population of Gaza in order to justify violence. But there is no basis for doing so.

The fact that a violent action takes place in the context of a wider oppression does not make it either (a) just (b) lawful under international law or c) effective in pursuit of social justice.

In this case, Hamas’s act of terror looks set to achieve the opposite.

What does Hamas want?

Hamas has offered a truce and asked for negotiations, stating that it has ‘achieved its objective’. If so, it’s logical to conclude that the immediate objective was to demonstrate proof-of-concept of an unstoppable pogromist terror. Do as we ask or we do this again, might be a fair summary.

The wider aim, according to numerous experts, is to force Hamas and Iran back into the power-broking process in the Middle East region, paralysing Saudi-Israeli rapprochement.

The firm view of the Islamic Republic is that the governments that are gambling on normalizing relations with the Zionist regime will suffer losses. Defeat awaits them…Today, the situation of the Zionist regime is not a situation that encourages closeness to it. They [other governments] should not make this mistake. The usurper [Zionist] regime is coming to an end.

Hamas could only achieve the aim of ending Saudi-Israeli rapprochement with an attack designed to trigger massive retribution, risking a regional all-out war.

there’s a line in Khamenei’s 3 October speech that, in retrospect looks explanatory: Thus, [the Zionists] are filled with grudge. They are filled with anger! Of course, the Quran exclaims: “Say, “die of your rage!” (3:119). That’s right. Be angry, and die of your rage. And this will happen. They are dying. With God’s help, this matter of ‘die of your rage’ is happening now as regards the Zionist regime.

‘Die of your rage’ might actually be a good summary of what Hamas intends Israel to now do.

Enraged by the barbarity of the attacks, Israel unleashes unprecedented collective punishment against Gaza, triggering both Hezbollah and West Bank militants to join in the fight; this in turn prompts a wave of anti-Semitic demonstrations in western cities, and draws the USA into a regional quagmire, testing the limits of American support for Israel

Meanwhile combat losses, and retribution over the complete failure of Netanyahu’s strategy of ‘managing’ the conflict, raise political divisions in Israeli society to the point where its democracy fails.

In a context where both Russia and China have complex hybrid destabilisation operations going on in western democracies, and where the Brics+ project is pursuing the active decomposition of the rules-based order, this objective does not look as mad as at first sight.

the ‘multipolar world’ turns out not to be one of peaceful coexistence, but characterised by extreme conflicts and genocide.

In pursuit of systemic competition Beijing and Moscow are scraping at every open wound in the body geopolitic

it’s what you get when you purposefully dismantle an international order based on treaties and explicit rules. And where elites in Russia, the USA, Brasil and parts of Europe are openly experimenting with ethno-nationalist politics.

Chaos, then, is a feature of multipolarity, not a bug.

Israel has signalled its military objective is to destroy Hamas. From my experience in Gaza I would say: that is possible.

But be in no doubt. It will need a sustained urban combat operation, a long-term military occupation, massive loss of civilian life, an existential refugee crisis in Sinai, and the diversion of US-supplied ammunition and resources from Ukraine.

Attempting it with a largely conscript/reservist army, full of recently mobilised and enraged soldiers? Again it’s worth remembering Khamenei’s exhortation to Israelis to ‘die of your rage’.

The very impossibility of all these outcomes shows why we need an internationally mediated peace, alongside a functional two-state solution, which allows the people of Gaza to live in peace, exercise democracy and travel across borders.

not only will liberal sympathy for Israel evaporate, but the Muslim minorities in some Western countries will be radicalised.

Typically, from my experience, combat in Gaza takes the following form. There is a street with children playing at one end; in the middle it is eerily deserted; at the other end is the IDF and above is an IDF drone. But there is no front line. The mujahedeen are in tunnels, popping up to take sniper shots or lay IEDs at night, and only committing ATGMs once a vehicle comes into view. The only front line is, for most of the time, between the IDF and Palestinian civilians.

Both sides risk miscalculating. Hamas does not care what happens to Palestinian civilians in Gaza, many of whom hate Hamas.

But there is a danger of miscalculation for Israel too. Netanyahu’s far-right government completely missed the threat, actively stoked tensions in the West Bank and Al Aqsa, and could easily now double down on a self-destructive course.

Ultimately, you cannot hold two million people in an open air prison without a gaoler to keep order. If Hamas can’t do it, the IDF will have to be a permanent occupation force, or it will have to install the PA, or the UN will have to send a stabilisation force.

Danger of miscalculation

The Brics+ ideology

The Gaza crisis is the latest example of how the Russian/Chinese ‘multipolar world’ project works in practice. It doesn’t matter whether there is a chain of command that goes Moscow→Tehran→Hamas. There is a chain of understanding – seize every opportunity to militarise all conflict; exploit every unexpected breakthrough; make all violence symbolic; weaponise the information space and push conflict into the heartlands of ‘imperialism’.

the Brics+ ideology. Its central tenets are that a multipolar world is better than the charter system; that universalism and international law are over; that the West no longer has the right to use the structures of international governance to normalise concepts like democracy or human rights; and that everything that disorganises the rules-based order is progressive, even when carried out by reactionary political forces.

Arab nationalism no longer looks like the dominant ideology on the demonstrations we’ve seen in Sydney, London and NYC. Alongside it there’s a mixture of Islamism plus the ‘decolonisation’ agenda of postmodernist academia.

For the past two years, during the Ukraine war, this incipient red-brown ideology has been mostly contained:

with this conflict there is now a danger that the masses turn up, and are corralled into this emergent fusion of far-left/far-right politics.

I’ve spent the period post-2016 trying to equip the democratic left to defeat this ideology. It’s not about being ‘anti-woke’, or apologising for colonialism: it means teaching people that a cocktail of anti-humanism, anti-universalism and anti-rationality is a route to excusing the totalitarian states in Russia and China, and – now – the genocidal actions of their proxies.

A case study of this is the statement issued by 31 Harvard student groups saying they ‘hold the Israeli regime entirely responsible for all the unfolding violence’ – just hours after the Hamas attack began.

the global left is rapidly splitting into irreconcilable camps – as Edward Thompson recognised it would, under the influence of post-structuralism in the 1970s.

The logical implication is that Palestinians have no agency whatsoever. That Hamas murders civilians because Israel has ‘structured’ Palestinian reality to make that inevitable. For people presumably wedded to ‘decolonising’ the curriculum, it is a shockingly colonialist premise.

The logic is that Israel is responsible for everything Hamas does because its violence has ‘structured every aspect of Palestinian existence’ since the Nakba.

There are many civilisations, and none is superior or inferior to another. They are equal since each civilisation represents a unique expression of its own culture, traditions, and the aspirations of its people.

In a way, what Putin preaches is an ‘intersectionality of the peoples’: identity politics raised from the level of the individual to the level of the ethnic group.

And it turns out anti-Enlightenment leftism makes it pretty easy to converge with that view. The common assumptions are disdain for universalism, scorn for international law and human rights, repudiation of the Enlightenment (and thus liberalism, social democracy, humanistic Marxism and anarchism) and worship of any totalitarian government that delivers economic development.

This is the modern incarnation of Stalinism, and – to the surprise of nobody who has studied actual Stalinism – it has no problem seeing fascists like Hamas as the ‘agent of progress’.

we need to understand how closely this hyper-deterministic and anti-universal world view maps onto the ideology presented, for example, by Putin at Valdai last week. For Putin there is no single human civilisation, only civilisations, which must be rooted in ethnicity establish their co-existence through the survival of the fittest:

One camp, he said, is a theology. The other a tradition of active reason. The first repudiates liberalism and universalism. The second recognises its debt to liberalism and wants to make universalism consistent

The first claims international law is a sham; the second knows that, though the institutions of the rules-based order are flawed, they are better than chaos.

that you can stand with the Israeli people under attack while simultaneously standing up for the Palestinian people’s right to self-determination.

Those flaunting their joy at the murder of Israeli civilians need to understand the licence this creates in the minds of rightwing ethno-nationalists in our own society. What Hamas did to the kids of Kfar Azar, the far right wants to do to you.

As long as life continues as it has — with people choosing smaller family sizes, as is now common in most of the world — then in the 22nd or 23rd century, our decline could be just as steep as our rise.

there is no consensus on exactly how quickly populations will fall after that. Over the past 100 years, the global population quadrupled, from two billion to eight billion.

What would happen as a consequence? Over the past 200 years, humanity’s population growth has gone hand in hand with profound advances in living standards and health: longer lives, healthier children, better education, shorter workweeks and many more improvements

In this short period, humanity has been large and growing. Economists who study growth and progress don’t think this is a coincidence. Innovations and discoveries are made by people. In a world with fewer people in it, the loss of so much human potential may threaten humanity’s continued path toward better lives.

It would be tempting to welcome depopulation as a boon to the environment. But the pace of depopulation will be too slow for our most pressing problems. It will not replace the need for urgent action on climate, land use, biodiversity, pollution and other environmental challenges

If the population hits around 10 billion people in the 2080s and then begins to decline, it might still exceed today’s eight billion after 2100

Population decline would come quickly, measured in generations, and yet arrive far too slowly to be more than a sideshow in the effort to save the planet. Work to decarbonize our economies and reform our land use and food systems must accelerate in this decade and the next, not start in the next century.

This isn’t a call to immediately remake our societies and economies in the service of birthrates. It’s a call to start conversations now, so that our response to low birthrates is a decision that is made with the best ideas from all of u

If we wait, the less inclusive, less compassionate, less calm elements within our society and many societies worldwide may someday call depopulation a crisis and exploit it to suit their agendas — of inequality, nationalism, exclusion or control

Births won’t automatically rebound just because it would be convenient for advancing living standards or sharing the burden of care work

We know that fertility rates can stay below replacement because they have. They’ve been below that level in Brazil and Chile for about 20 years; in Thailand for about 30 years; and in Canada, Germany and Japan for about 50.

In fact, in none of the countries where lifelong fertility rates have fallen well below two have they ever returned above it. Depopulation could continue, generation after generation, as long as people look around and decide that small families work best for them, some having no children, some having three or four and many having one or two.

Nor can humanity count on any one region or subgroup to buoy us all over the long run. Birthrates are falling in sub-Saharan Africa, the region with the current highest average rates, as education and economic opportunities continue to improve

The main reason that birthrates are low is simple: People today want smaller families than people did in the past. That’s true in different cultures and economies around the world. It’s what both women and men report in surveys.

Humanity is building a better, freer world with more opportunities for everyone, especially for women

That progress also means that, for many of us, the desire to build a family can clash with other important goals, including having a career, pursuing projects and maintaining relationships

In a world of sustained low birthrates and declining populations, there may be threats of backsliding on reproductive freedom — by limiting abortion rights, for example

Nobody yet knows what to do about global depopulation. But it wasn’t long ago that nobody knew what to do about climate change. These shared challenges have much in common,

As with climate change, our individual decisions on family size add up to an outcome that we all share.

Six decades from now is when the U.N. projects the size of the world population will peak. There won’t be any quick fixes: Even if it’s too early today to know exactly how to build an abundant future that offers good lives to a stable, large and flourishing future population, we should already be working toward that goal.

If OnlyFans’s creator earnings were taken as a whole, the company would rank around No. 90 on Forbes’s list of the biggest private companies in America by revenue, ahead of Twitter (now called X), Neiman Marcus Group, New Balance, Hard Rock International and Hallmark Cards.

Many creators now operate like independent media companies, with support staffs, growth strategies and promotional budgets, and work to apply the cold quantification and data analytics of online marketing to the creation of a fantasy life.

The subscription site has often been laughed off as a tabloid punchline, a bawdy corner of the internet where young, underpaid women (teachers, nurses, cops) sell nude photos, get found out and lose their jobs.

pressures to perform for a global audience; an internet that never forgets. “There is simply no room for naivety,” one said in a guide posted to Reddit’s r/CreatorsAdvice.

America’s social media giants for years have held up online virality as the ultimate goal, doling out measurements of followers, reactions and hearts with an unspoken promise: that internet love can translate into sponsorships and endorsement deals

But OnlyFans represents the creator economy at its most blatantly transactional — a place where viewers pay upfront for creators’ labor, and intimacy is just another unit of content to monetize.

The fast ascent of OnlyFans further spotlights how the internet has helped foster a new style of modern gig work that creators see as safe, remote and self-directed,

Creators’ nonchalance about the digital sex trade has fueled a broader debate about whether the site’s promotion of feminist autonomy is a facade: just a new class of techno-capitalism, selling the same patriarchal dream.

But OnlyFans increasingly has become the model for how a new generation of online creators gets paid. Influencers popular on mainstream sites use it to capitalize on the audiences they’ve spent years building. And OnlyFans creators have turned going viral on the big social networks into a marketing strategy, using Facebook, Twitter and TikTok as sales funnels for getting new viewers to subscribe.

many creators, she added, still find it uniquely alluring — a rational choice in an often-irrational environment for gender, work and power. “Why would I spend my day doing dirty, degrading, minimum-wage labor when I can do something that brings more money in and that I have a lot more control over?”

it is targeting major “growth regions” in Latin America, Europe and Australia. (The Mexican diver Diego Balleza said he is using his $15-a-month account to save up for next year’s Paris Olympics.)

“Does an accountant always enjoy their work? No. All work has pleasure and pain, and a lot of it is boring and annoying. Does that mean they’re being exploited?”

Adams’s operation is registered in state business records as a limited liability company and offers quarterly employee performance reviews and catered lunch. It also runs with factory-like efficiency, thanks largely to a system designed in-house to track millions of data points on customers and content and ensure every video is rigorously planned and optimized.

Since sending her first photo in 2021, Adams’s OnlyFans accounts have earned $16.5 million in sales, more than 1.4 million fans and more than 11 million “likes.” She now makes about $30,000 a day — more than most American small businesses — from subscriptions, video sales, messages and tips, half of which is pure profit

Adams’s team sees its business as one of harmless, destigmatized gratification, in which both sides get what they want. The buyers are swiped over in dating apps, widowed, divorced or bored, eager to pay for the illusion of intimacy with an otherwise unattainable match. And the sellers see themselves as not all that different from the influencers they watched growing up on YouTube, charging for parts of their lives they’d otherwise share for free.

“This is normal for my generation, you know?

“I can go on TikTok right now and see ten girls wearing the bare minimum of clothing just to get people to join their page. Why not go the extra step to make money off it?”

the job can be financially precarious and mentally taxing, demanding not just the technical labor of recording, editing, managing and marketing but also the physical and emotional labor of adopting a persona to keep clients feeling special and eager to spend.

enix International Limited, is based, the company said its sales grew from $238 million in 2019 to more than $5.5 billion last year.

Its international army of creators has also grown from 348,000 in 2019 to more than 3 million today — a tenfold increase.

The company paid its owner, the Ukrainian American venture capitalist Leonid Radvinsky, $338 million in dividends last year.)

portion of its creator base and 70 percent of its annual revenue

When Tim Stokely, a London-based operator of live-cam sex sites, founded OnlyFans with his brother in 2016, he framed it as a simple way to monetize the creators who were becoming the world’s new celebrities — the same online influencers, just with a payment button. In 2019, Stokely told Wired magazine that his site was like “a bolt-on to your existing social media,” in the same way “Uber is a bolt-on to your car.”

Before OnlyFans, pornography on the internet had been largely a top-down enterprise, with agents, producers, studios and other middlemen hoarding the profits of performers’ work. OnlyFans democratized that business model, letting the workers run the show: recording their own content, deciding their prices, selling it however they’d like and reaping the full reward.

The platform bans real-world prostitution, as well as extreme or illegal content, and requires everyone who shows up on camera to verify they’re 18 or older by sending in a video selfie showing them holding a government-issued ID.

OnlyFans operates as a neutral marketplace, with no ads, trending topics or recommendation algorithms, placing few limitations on what creators can sell but also making it necessary for them to market themselves or fade away.

After sending other creators’ agents their money over PayPal, Adams’s ad workers send suggestions over the messaging app Telegram on how Bryce should be marketed, depending on the clientele. OnlyFans models whose fans tend to prefer the “girlfriend experience,” for instance, are told to talk up her authenticity: “Bryce is a real, fit girl who wants to get to know you

Like most platforms, OnlyFans suffers from a problem of incredible pay inequality, with the bulk of the profits concentrated in the bank accounts of the lucky few.

the top 1 percent of accounts made 33 percent of the money, and that most accounts took home less than $145 a month

Watching their partner have sex with someone else sometimes sparked what they called “classic little jealousy issues,” which Adams said they resolved with “more communication, more growing up.” The money was just too good. And over time, they adopted a self-affirming ideology that framed everything as just business. Things that were tough to do but got easier with practice, like shooting a sex scene, they called, in gym terms, “reps.” Things one may not want to do at first, but require some mental work to approach, became “self-limiting beliefs.”

They started hiring workers through friends and family, and what was once just Adams became a team effort, in which everyone was expected to workshop caption and video ideas. The group evaluated content under what Brian, who is 31, called a “triangulation method” that factored their comfort level with a piece of content alongside its engagement potential and “brand match.” Bryce the person gave way to Bryce the brand, a commercialized persona drafted by committee and refined for maximum marketability.

One of the operation’s most subtly critical components is a piece of software known as “the Tool,” which they developed and maintain in-house. The Tool scrapes and compiles every “like” and view on all of Adams’s social network accounts, every OnlyFans “fan action” and transaction, and every text, sext and chat message — more than 20 million lines of text so far.

It houses reams of customer data and a library of preset messages that Adams and her chatters can send to fans, helping to automate their reactions and flirtations — “an 80 percent template for a personalized response,” she said.

And it’s linked to a searchable database, in which hundreds of sex scenes are described in detail — by price, total sales, participants and general theme — and given a unique “stock keeping unit,” or SKU, much like the scannable codes on a grocery store shelf. If a fan says they like a certain sexual scenario, a team member can instantly surface any relevant scenes for an easy upsell. “Classic inventory chain,” Adams said.

The systemized database is especially handy for the young women of Adams’s chat team, known as the “girlfriends,” who work at a bench of laptops in the gym’s upper loft. The Tool helped “supercharge her messaging, which ended up, like, 3X-ing her output,” Brian said, meaning it tripled.

Keeping men talking is especially important because the chat window is where Adams’s team sends out their mass-message sales promotions, and the girlfriends never really know what to expect. One girlfriend said she’s had as many as four different sexting sessions going at once.

Adams employs a small team that helps her pay other OnlyFans creators to give away codes fans can use for free short-term trials. The team tracks redemption rates and promotional effectiveness in a voluminous spreadsheet, looking for guys who double up on discount codes, known as “stackers,” as well as bad bets and outright fraud.

Many OnlyFans creators don’t offer anything explicit, and the site has pushed to spotlight its stable of chefs, comedians and mountain bikers on a streaming channel, OFTV. But erotic content on the platform is inescapable; even some outwardly conventional creators shed their clothes behind the paywall

Creators with a more hardcore fan base, meanwhile, are told to cut to the chase: “300+ sex tapes & counting”; “Bryce doesn’t say no, she’s the most wild, authentic girl you will ever find.”

The $18 an hour she makes on the ad team, however, is increasingly dwarfed by the money Leigh makes from her personal OnlyFans account, where she sells sex scenes with her boyfriend for $10 a month. Leigh made $92,000 in gross sales in July, thanks largely to revenue from new fans who found her through Adams or the bikini videos Leigh posts to her 170,000-follower TikTok account

“This is a real job. You dedicate your time to it every single day. You’re always learning, you’re always doing new things,” she said. “I’d never thought I’d be good at business, but learning all these business tactics really empowers you. I have my own LLC; I don’t know any other 20-year-old right now that has their own LLC.”

The team is meeting all traffic goals, per their internal dashboard, which showed that through the day on a recent Thursday they’d gained 2,221,835 video plays, 19,707 landing-page clicks, 6,372 new OnlyFans subscribers and 9,024 new social-network followers. And to keep in shape, Adams and her boyfriend are abiding by a rigorous daily diet and workout plan

They eat the same Chick-fil-A salad at every lunch, track every calorie and pay a gym assistant to record data on every rep and weight of their exercise.

But the OnlyFans business is competitive, and it does not always feel to the couple like they’ve done enough. Their new personal challenge, they said, is to go viral on the other platforms as often as possible, largely through jokey TikTok clips and bikini videos that don’t give away too much.

the host told creators this sales-funnel technique was key to helping build the “cult of you”: “Someone’s fascination will become infatuation, which will make you a lot of money.”

Adams’s company has worked to reverse engineer the often-inscrutable art of virality, and Brian now estimates Adams makes about $5,000 in revenue for every million short-form video views she gets on TikTok.

Her team has begun ranking each platform by the amount of money they expect they can get from each viewer there, a metric they call “fan lifetime value.” (Subscribers who click through to her from Facebook tend to spend the most, the data show. Facebook declined to comment.)

The younger workers said they see the couple as mentors, and the two are constantly reminding them that the job of a creator is not a “lottery ticket” and requires a persistent grind. Whenever one complains about their lack of engagement, Brian said he responds, “When’s the last time you posted 60 different videos, 60 days in a row, on your Instagram Reels?”

But some have taken to it quite naturally. Rayna Rose, 19, was working last year at a hair salon, sweeping floors for $12 an hour, when an old high school classmate who worked with Adams asked whether she wanted to try OnlyFans and make $500 a video.

Rose started making videos and working as a chatter for $18 an hour but recently renegotiated her contract with Adams to focus more on her personal OnlyFans account, where she has nearly 30,000 fans, many of whom pay $10 a month.

One recent evening this summer, Adams was in the farm’s gym when her boyfriend told her he was headed to their guest room to record a collab with Rose, who was wearing a blue bikini top and braided pigtails.

“Go have fun,” Adams told them as they walked away. “Make good content.” The 15-minute video has so far sold more than 1,400 copies and accounted for more than $30,000 in sales.

Rose said she has lost friends due to her “lifestyle,” with one messaging her recently, “Can you imagine how successful you would be if you studied regularly and spent your time wisely?”

The message stung but, in Rose’s eyes, they didn’t understand her at all. She feels, for the first time, like she has a sense of purpose: She wants to be a full-time influencer. She expects to clear $200,000 in earnings this year and is now planning to move out of her parents’ house.

“I had no idea what I wanted to do with my life. And now I know,” she said. “I want to be big. I want to be, like, mainstream.”

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Adam Tooze is a professor of history at Columbia University

it may simply be because it’s not our internet anymore. It belongs to zoomers now.

we’ve grown used to an internet whose form and culture was significantly shaped by and molded to our preferences. The American internet of the 2010s was an often stupid and almost always embarrassing internet — but it was a millennial internet. There were no social networks on which we felt uncomfortable; no culture developments we didn’t engender; no image macros we didn’t understand.

There was a time in my life when it was trivial to sign up to a new social network and pick up its patterns and mores on the fly. Now, I feel exhausted by the prospect.

millennials’ screen time has been on a steady decline for years. Only 42 percent of 30- to 49-year-olds say they’re online “almost constantly,” compared to 49 percent of 18- to 29-year-olds. We’re no longer the earliest adopters, even: 18- to 29-year-olds are more likely to have used ChatGPT than 30- to 49-year-olds — though maybe only because we’re no longer being assigned homework.

The heaviest users and most engaged American audience on the internet are no longer millennials but our successors in Generation Z

Frankly, that should be freeing. Being extremely online, on an internet geared to your interests (in the same way that heroin is geared to your brain), is not exactly a quality conducive to personal happiness

I suspect there is another factor driving the alienation and discomfort felt by many of the people who feel as though the internet is dying before our eyes: We’re getting old.

The celebrities are unrecognizable (Kai Cenat???); the slang is impenetrable (gyatt???); the formats are new (GRWM???). Austerely tasteful overhead shots of meticulously arranged food posted on Instagram have been replaced with garishly lit minute-long videos of elaborate restaurant meals posted on TikTok. Glibly chatty blog posts about the news have been replaced with videos of recording sessions for podcasts

the creative expression and exuberant sociality that made the internet so “fun” to me a decade ago are booming among 20- somethings on TikTok, Instagram, Discord, Twitch and even X. “Skibidi Toilet,” “Fanum tax,” “the rizzler”

True, the fun I’m talking about is co-opted and exploited by a small handful of powerful and wealthy platform businesses

When you drill down, what mostly seems to have changed about the web over the last few years isn’t the structural dynamics but the cultural signifiers.

Perhaps what frustrated, alienated and aging internet users like me are experiencing here is not only the fruits of an enjunkified internet but also the loss of the cognitive elasticity, sense of humor and copious amounts of free time necessary to navigate all that confusing junk nimbly and cheerfully.

Zoomer internet is, at least on the surface, quite different than ours.

The more alienating the mass internet is to me, the more likely I will put to good use the hours I previously spent messing around

Or, at least, the more likely it is I will find corners — group chats, message boards and elsewhere — geared to my specific interests rather than the general engagement bait that otherwise dominates.

Had the wealth siphoned off by Haiti’s national bank stayed in the country, it would have added at least $1.7 billion to Haiti’s economy over the years — more than all of the government’s revenues in 2021.

“Isn’t it funny,” the Haitian politician and economist Edmond Paul wrote of the national bank in 1880, “that a bank that claims to come to the rescue of a depleted public treasury begins not by depositing money but by withdrawing everything of value?”

But while Haitians themselves were poor, Haiti could make you rich. As a British diplomat, Spenser St. John, wrote in 1884: “No country possesses greater capabilities, or a better geographical position, or more variety of soil, of climate, or of production.”

Slaveholders had taken that wealth for themselves, first with the whip, then with a flotilla of French warships, demanding compensation for plantations, land and what France considered its other lost property: the Haitian people. It was the first and only instance in which generations of free people had to pay the descendants of their former slave masters.

Beyond bricks and steel, Haiti earmarked about 20 percent of the French loan to pay off the last of the debt linked to France’s original ransom, according to the loan contract. “The country will finally come out of its malaise,” the Haitian government’s annual report predicted that year. “Our finances will prosper.”

None of that happened. Right off the top, French bankers took 40 percent of the loan in commissions and fees. The rest paid off old debts, or disappeared into the pockets of corrupt Haitian politicians.

The 1875 loan from Crédit Industriel and its partner left two major legacies. First is what the economist Thomas Piketty called the transition from “brutal colonialism” to “neocolonialism through debt.”

Haiti took on millions in new interest, hoping to finally shed the burden of paying its former slave masters. In that way, the loan helped prolong the misery of Haiti’s financial indentureship to France. Long after the former slaveholding families considered the debt settled, Haiti would still be paying — only now to Crédit Industriel.

And it undercut the first-day assessment by Texas Gov. Greg Abbott, who praised law enforcement for their "quick response" to the attack, which he said saved lives.

Reports since then reveal a grisly, wrenching scene, where terrified students waited for help as the shooter, armed with an assault rifle, continued his rampage. One student told of laying on top of a classmate, smearing her blood on her so both would appear dead, to save them both. The girl who was injured died at the hospital from her injuries, raising questions about whether she would have survived if the reaction had been quicker.Abbott, a vociferous gun rights proponent who last year signed a law allowing people to own guns without a license or training, was originally scheduled to speak at the NRA convention. Thursday night, his office said the governor would instead head to Uvalde, supplying a video speech to show at the NRA meeting.

Well-known sports figures decried the gun violence and what they called inaction by elected officials to address it. During Thursday evening's baseball game between the New York Yankees and the Tampa Bay Rays, both teams abandoned their usual game-update tweets for a series of tweets on gun violence."The devastating events that took place in Uvalde, Buffalo and countless other communities across our nation are tragedies that are intolerable," the Yankees said on the team's official Twitter account, referring to the racist-motivated murder of 10 Black shoppers in Buffalo on May 16.

Moscow, which in 2016 banned the Mejlis, a body representing Crimean Tatars, rejected the report's findings. It says a March 2014 referendum legitimised its "incorporation" of Crimea.The Crimea battalion performed reconnaissance against Russian forces around Yasnohorodka, a village 25km west of Kyiv, and later in nearby Motyzhyn, Akayev said."The residents here were initially very scared when they saw us because they didn't know who we were. We had to shout 'we are Ukrainian'... then people started slowly coming out of their homes and they gave us tea."

"We wanted to buy this place, to build a Crimean Tatar school and a mosque here... It didn’t come to anything, and then this happened," Akayev said, gesturing at the building’s charred remains which he said was the result of Russian shelling."I (still) dream about this project, but really I just want to return home to Crimea."

a Bloomberg reporter saw only three semis among the vehicles blocking the Ambassador Bridge, which were mainly pickup trucks and private cars; photos taken Saturday also show very few commercial trucks.