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A social network is an idle, inactive system—a Rolodex of contacts, a notebook of sales targets, a yearbook of possible soul mates. But social media is active—hyperactive, really—spewing material across those networks instead of leaving them alone until needed.

As the original name suggested, social networking involved connecting, not publishing. By connecting your personal network of trusted contacts (or “strong ties,” as sociologists call them) to others’ such networks (via “weak ties”), you could surface a larger network of trusted contacts

The whole idea of social networks was networking: building or deepening relationships, mostly with people you knew. How and why that deepening happened was largely left to the users to decide.

That changed when social networking became social media around 2009, between the introduction of the smartphone and the launch of Instagram. Instead of connection—forging latent ties to people and organizations we would mostly ignore—social media offered platforms through which people could publish content as widely as possible, well beyond their networks of immediate contacts.

Social media turned you, me, and everyone into broadcasters (if aspirational ones). The results have been disastrous but also highly pleasurable, not to mention massively profitable—a catastrophic combination.

soon enough, all social networks became social media first and foremost. When groups, pages, and the News Feed launched, Facebook began encouraging users to share content published by others in order to increase engagement on the service, rather than to provide updates to friends. LinkedIn launched a program to publish content across the platform, too. Twitter, already principally a publishing platform, added a dedicated “retweet” feature, making it far easier to spread content virally across user networks.

The authors propose social media as a system in which users participate in “information exchange.” The network, which had previously been used to establish and maintain relationships, becomes reinterpreted as a channel through which to broadcast.

The toxicity of social media makes it easy to forget how truly magical this innovation felt when it was new. From 2004 to 2009, you could join Facebook and everyone you’d ever known—including people you’d definitely lost track of—was right there, ready to connect or reconnect. The posts and photos I saw characterized my friends’ changing lives, not the conspiracy theories that their unhinged friends had shared with them

Twitter, which launched in 2006, was probably the first true social-media site, even if nobody called it that at the time. Instead of focusing on connecting people, the site amounted to a giant, asynchronous chat room for the world. Twitter was for talking to everyone—which is perhaps one of the reasons journalists have flocked to it

on Twitter, anything anybody posted could be seen instantly by anyone else. And furthermore, unlike posts on blogs or images on Flickr or videos on YouTube, tweets were short and low-effort, making it easy to post many of them a week or even a day.

a “web 2.0” revolution in “user-generated content,” offering easy-to-use, easily adopted tools on websites and then mobile apps. They were built for creating and sharing “content,”

When we look back at this moment, social media had already arrived in spirit if not by name. RSS readers offered a feed of blog posts to catch up on, complete with unread counts. MySpace fused music and chatter; YouTube did it with video (“Broadcast Yourself”)

This is also why journalists became so dependent on Twitter: It’s a constant stream of sources, events, and reactions—a reporting automat, not to mention an outbound vector for media tastemakers to make tastes.

Other services arrived or evolved in this vein, among them Reddit, Snapchat, and WhatsApp, all far more popular than Twitter. Social networks, once latent routes for possible contact, became superhighways of constant content

Although you can connect the app to your contacts and follow specific users, on TikTok, you are more likely to simply plug into a continuous flow of video content that has oozed to the surface via algorithm.

In the social-networking era, the connections were essential, driving both content creation and consumption. But the social-media era seeks the thinnest, most soluble connections possible, just enough to allow the content to flow.

The ensuing disaster was multipar

“influencer” became an aspirational role, especially for young people for whom Instagram fame seemed more achievable than traditional celebrity—or perhaps employment of any kind.

social-media operators discovered that the more emotionally charged the content, the better it spread across its users’ networks. Polarizing, offensive, or just plain fraudulent information was optimized for distribution. By the time the platforms realized and the public revolted, it was too late to turn off these feedback loops.

When network connections become activated for any reason or no reason, then every connection seems worthy of traversing.

Rounding up friends or business contacts into a pen in your online profile for possible future use was never a healthy way to understand social relationships.

when social networking evolved into social media, user expectations escalated. Driven by venture capitalists’ expectations and then Wall Street’s demands, the tech companies—Google and Facebook and all the rest—became addicted to massive scale

Social media showed that everyone has the potential to reach a massive audience at low cost and high gain—and that potential gave many people the impression that they deserve such an audience.

On social media, everyone believes that anyone to whom they have access owes them an audience: a writer who posted a take, a celebrity who announced a project, a pretty girl just trying to live her life, that anon who said something afflictive

Facebook and all the rest enjoyed a massive rise in engagement and the associated data-driven advertising profits that the attention-driven content economy created. The same phenomenon also created the influencer economy, in which individual social-media users became valuable as channels for distributing marketing messages or product sponsorships by means of their posts’ real or imagined reach

people just aren’t meant to talk to one another this much. They shouldn’t have that much to say, they shouldn’t expect to receive such a large audience for that expression, and they shouldn’t suppose a right to comment or rejoinder for every thought or notion either.

From being asked to review every product you buy to believing that every tweet or Instagram image warrants likes or comments or follows, social media produced a positively unhinged, sociopathic rendition of human sociality.

That’s no surprise, I guess, given that the model was forged in the fires of Big Tech companies such as Facebook, where sociopathy is a design philosophy.

If change is possible, carrying it out will be difficult, because we have adapted our lives to conform to social media’s pleasures and torments. It’s seemingly as hard to give up on social media as it was to give up smoking en masse

Quitting that habit took decades of regulatory intervention, public-relations campaigning, social shaming, and aesthetic shifts. At a cultural level, we didn’t stop smoking just because the habit was unpleasant or uncool or even because it might kill us. We did so slowly and over time, by forcing social life to suffocate the practice. That process must now begin in earnest for social media.

Something may yet survive the fire that would burn it down: social networks, the services’ overlooked, molten core. It was never a terrible idea, at least, to use computers to connect to one another on occasion, for justified reasons, and in moderation

The problem came from doing so all the time, as a lifestyle, an aspiration, an obsession. The offer was always too good to be true, but it’s taken us two decades to realize the Faustian nature of the bargain.

when I first wrote about downscale, the ambition seemed necessary but impossible. It still feels unlikely—but perhaps newly plausible.

To win the soul of social life, we must learn to muzzle it again, across the globe, among billions of people. To speak less, to fewer people and less often–and for them to do the same to you, and everyone else as well

We cannot make social media good, because it is fundamentally bad, deep in its very structure. All we can do is hope that it withers away, and play our small part in helping abandon it.

the power of networks has varied over time and that the relative importance of the tower and the square has ebbed and flowed. Nonetheless, Ferguson sees two specific periods as standing out as intensely “networked eras.” The first started in the late 15th century, after the introduction in Europe of the printing press, and lasted until the late 18th century. The second, “our own time,” began in the 1970s and is still going on.

from the late 1790s until the late 1960s, was terrible for networks. Ferguson writes that “hierarchical institutions re-established their control and successfully shut down or co-opted networks. The zenith of hierarchically organized power was in fact the mid-twentieth century — the era of totalitarian regimes and total war.”

“The Square and the Tower” will not disappoint readers who have come to expect from Ferguson ambition, erudition, originality and expansive historical panoramas. These often come mixed with telling anecdotes, illuminating minutiae, fun facts and even some facile one-liners that, while entertaining, don’t add much to the argument.

it is too much, and not all of it is illuminated by the “theoretical insights from myriad disciplines.” In fact, it is surprising how little Ferguson relies on the initial chapters on network theory to make his case.

In the remaining eight parts of the book, this network theory mostly disappears and the story is told in standard historical narrative.

its main unit of analysis, the social network, is too imprecise a concept to provide a solid foundation from which to launch the book’s epic theorizing. Most networks have some hierarchical features, and, as Ferguson notes, “a hierarchy is just a special kind of network

Nonetheless, the networks-and-hierarchies dichotomy does work as a narrative device that allows a gifted storyteller to take his readers on a fascinating tour of world history.

supply-chain attack

According to SolarWinds S.E.C. filings, the malware was on the software from March to June. The number of organizations that downloaded the corrupted update could be as many as 18,000, which includes most federal government unclassified networks and more than 425 Fortune 500 companies.

The magnitude of this ongoing attack is hard to overstate.

The Russians have had access to a considerable number of important and sensitive networks for six to nine months.

While the Russians did not have the time to gain complete control over every network they hacked, they most certainly did gain it over hundreds of them.

The logical conclusion is that we must act as if the Russian government has control of all the networks it has penetrated

The actual and perceived control of so many important networks could easily be used to undermine public and consumer trust in data, written communications and services.

hat should be done?On Dec. 13, the Cybersecurity and Infrastructure Security Agency, a division of the Department of Homeland Security — itself a victim — issued an emergency directive ordering federal civilian agencies to remove SolarWinds software from their networks.

It also is impractical. In 2017, the federal government was ordered to remove from its networks software from a Russian company, Kaspersky Lab, that was deemed too risky. It took over a year to get it off the networks.

The remediation effort alone will be staggering

Cyber threat hunters that are stealthier than the Russians must be unleashed on these networks to look for the hidden, persistent access controls.

The National Defense Authorization Act, which each year provides the Defense Department and other agencies the authority to perform its work, is caught up in partisan wrangling. Among other important provisions, the act would authorize the Department of Homeland Security to perform network hunting in federal networks.

The response must be broader than patching networks. While all indicators point to the Russian government, the United States, and ideally its allies, must publicly and formally attribute responsibility for these hacks. If it is Russia, President Trump must make it clear to Vladimir Putin that these actions are unacceptable. The U.S. military and intelligence community must be placed on increased alert; all elements of national power must be placed on the table.

President Trump is on the verge of leaving behind a federal government, and perhaps a large number of major industries, compromised by the Russian government. He must use whatever leverage he can muster to protect the United States and severely punish the Russians.President-elect Joe Biden must begin his planning to take charge of this crisis. He has to assume that communications about this matter are being read by Russia, and assume that any government data or email could be falsified.

“What Putin wants is to transform the world order” that evolved since World War II and the post-Cold War — where “the competition between nations was about who can be richer and who can help their people prosper the most . … Putin hates that world because he loses in that world — his system is a loser in a peaceful, global, wealth-enhancing paradigm. And so what he wants is to move us back to dog-eat-dog, to a 19th-century, great power competition, because he thinks he can, if not win, be more effective there. … Let’s not think that this is a Ukrainian problem; this is a problem for us all.”

These wars very much are our business — and now clearly inescapable, since we’re deeply entwined in both conflicts. What’s crucial to keep in mind about America — as the leader of the Inclusion Network — is that right now we’re fighting the war in Ukraine on our terms, but we’re fighting the war in the Middle East on Iran’s terms.

CNN recently described, per a source familiar with it, a declassified U.S. intelligence assessment provided to Congress saying that Russia had lost 87 percent of its preinvasion active-duty ground troops and two-thirds of its tanks that it had prior to its invasion of Ukraine. Putin can still inflict a lot of damage on Ukraine with missiles, but his dream of occupying the whole country and using it as a launching pad to threaten the Inclusion Network — particularly the NATO-protected European Union — is now out of reach. Thank you, Kyiv.

At a breakfast with NATO leaders devoted to the Ukraine issue at Davos this year, Canada’s deputy prime minister, Chrystia Freeland, noted that it is we, the West, who should be thanking the Ukrainians, not forcing them to beg us for more weapons.

China under President Xi Jinping straddles the two networks, along with much of what’s come to be called the global south. Their hearts, and often pocketbooks, are with the Resistors but their heads are with the Includers

the Resistance Network “is orchestrated by Iran, Islamists and jihadists” in a process they refer to as the “unity of battlefields.” This network, he noted, “seeks to bridge militias, rejectionists, religious sects and sectarian leaders,” creating an anti-Israel, anti-American, anti-Western axis that can simultaneously pressure Israel in Gaza, in the West Bank and on the Lebanon border — as well as America in the Red Sea, in Syria and in Iraq and Saudi Arabia from all directions.

In stark contrast, Koteich said, stands the Inclusion Network, one that’s focused on “weaving together” global and regional markets instead of battlefronts, business conferences, news organizations, elites, hedge funds, tech incubators and major trade routes. This inclusion network, he added, “transcends traditional boundaries, creating a web of economic and technological interdependence that has the potential to redefine power structures and create new paradigms of regional stability.”

things are different in the Middle East. There, it is Iran that is sitting back comfortably — indirectly at war with Israel and America, and sometimes Saudi Arabia, by fighting through Tehran’s proxies: Hamas in Gaza, the Houthis in Yemen, Hezbollah in Lebanon and Syria, and Shiite militias in Iraq.

Iran is reaping all the benefits and paying virtually no cost for the work of its proxies, and the U.S., Israel and their tacit Arab allies have not yet manifested the will or the way to pressure Iran back — without getting into a hot war, which they all want to avoid.

The members of the Resistance Network are great at tearing down and breaking stuff, but, unlike the Inclusion Network, they have shown no capacity to build any government or society to which anyone would want to emigrate, let alone emulate

For all of these reasons, this is a moment of great peril as well as great opportunity — especially for Israel. The competition between the Resistance Network and the Inclusion Network means that the region has never been more hostile or more hospitable to accepting a Jewish state.

Joe Peyronnin, a professor of journalism at N.Y.U., was an early president of Fox News, in the mid-nineties. “I’ve never seen anything like it before,” he says of Fox. “It’s as if the President had his own press organization. It’s not healthy.”

Kristol contends that Shine’s White House appointment is a scandal. “It’s been wildly under-covered,” he said. “It’s astounding that Shine—the guy who covered up Ailes’s horrible behavior—is the deputy chief of staff!”

Jennifer Rubin, another conservative Never Trumper, used to appear on the network, but wouldn’t do so now. “Fox was begun as a good-faith effort to counter bias, but it’s morphed into something that is not even news,” she says. “It’s simply a mouthpiece for the President, repeating what the President says, no matter how false or contradictory.

Sean Hannity has told colleagues that he speaks to the President virtually every night, after his show ends, at 10 P.M. According to the Washington Post, White House advisers have taken to calling Hannity the Shadow Chief of Staff. A Republican political expert who has a paid contract with Fox News told me that Hannity has essentially become a “West Wing adviser,” attributing this development, in part, to the “utter breakdown of any normal decision-making in the White House.” The expert added, “The place has gone off the rails. There is no ordinary policy-development system.” As a result, he said, Fox’s on-air personalities “are filling the vacuum.”

Trump has told confidants that he has ranked the loyalty of many reporters, on a scale of 1 to 10. Bret Baier, Fox News’ chief political anchor, is a 6; Hannity a solid 10. Steve Doocy, the co-host of “Fox & Friends,” is so adoring that Trump gives him a 12.

Kushner now has an almost filial status with Murdoch, who turns eighty-eight this month, and numerous sources told me that they communicate frequently. “Like, every day,” one said.

Ailes told Murdoch, “Trump gets great ratings, but if you’re not careful he’s going to end up totally controlling Fox News.”

In private, Murdoch regarded Trump with disdain, seeing him as a real-estate huckster and a shady casino operator. But, for all their differences, the two men had key traits in common. They both inherited and expanded family enterprises—an Australian newspaper; an outer-borough New York City real-estate firm—but felt looked down upon by people who were richer and closer to the centers of power.

both men have tapped into anti-élitist resentment to connect with the public and to increase their fortunes. Trump and Murdoch also share a transactional approach to politics, devoid of almost any ideology besides self-interest.

In 1994, Murdoch laid out an audacious plan to Reed Hundt, the chairman of the Federal Communications Commission under President Bill Clinton

Murdoch led him outside to take in the glittering view of the Los Angeles Basin, and confided that he planned to launch a radical new television network. Unlike the three established networks, which vied for the same centrist viewers, his creation would follow the unapologetically lowbrow model of the tabloids that he published in Australia and England, and appeal to a narrow audience that would be entirely his. His core viewers, he said, would be football fans; with this aim in mind, he had just bought the rights to broadcast N.F.L. games. Hundt told me, “What he was really saying was that he was going after a working-class audience. He was going to carve out a base—what would become the Trump base.

he had entered our country and was saying, ‘I’m going to break up the three-party oligopoly that has governed the most important medium of communication for politics and policy in this country since the Second World War.’ It was like a scene from ‘Faust.’ What came to mind was Mephistopheles.”

“Fox’s great insight wasn’t necessarily that there was a great desire for a conservative point of view.” More erudite conservatives, he says, such as William F. Buckley, Jr., and Bill Kristol, couldn’t have succeeded as Fox has. Levin observes, “The genius was seeing that there’s an attraction to fear-based, anger-based politics that has to do with class and race.”

In 1996, Murdoch hired Roger Ailes to create a conservative TV news outlet. Ailes, who died in 2017, was a master of attack politics and wedge issues, having been a media consultant on several of America’s dirtiest and most divisive campaigns, including those of Richard Nixon. Ailes invented programming, Levin argues, “that confirmed all your worst instincts—Fox News’ fundamental business model is driving fear.

As Hundt sees it, “Murdoch didn’t invent Trump, but he invented the audience. Murdoch was going to make a Trump exist. Then Trump comes along, sees all these people, and says, ‘I’ll be the ringmaster in your circus!’ ”

Until then, the network had largely mocked birtherism as a conspiracy theory. O’Reilly called its promoters “unhinged,” and Glenn Beck, who at the time also hosted a Fox show, called them “idiots.” But Trump gave birtherism national exposure, and, in a sign of things to come, Hannity fanned the flames. Hannity began saying that, although he thought that Obama had been born in the United States, the circumstances surrounding his birth certificate were “odd.”

In certain instances, however, Fox executives enforced journalistic limits.

Such niceties no longer apply. In November, Hannity joined Trump onstage at a climactic rally for the midterm elections. Afterward, Fox issued a limp statement saying that it didn’t “condone any talent participating in campaign events” and that the “unfortunate distraction” had “been addressed.”

For all of Ailes’s faults, Van Susteren argues, he exerted a modicum of restraint. She believes that he would have insisted on at least some distance from President Trump, if only to preserve the appearance of journalistic respectability embodied in the motto Ailes devised for Fox: “Fair and Balanced.

Fox News was hardly fair and balanced under his leadership. Gabriel Sherman, in his biography, “The Loudest Voice in the Room,” reports that Ailes was so obsessed with bringing down Obama in 2012 that he declared to colleagues, “I want to elect the next President.”

Don’t kid yourself about his support for immigration,” she said of Murdoch. “Rupert is first about the bottom line. They’re all going out to play to their crowd, whether it’s Fox or MSNBC.” (After leaving Fox, Van Susteren was for a short time a host on MSNBC.) Fox’s mile-by-mile coverage of the so-called “migrant caravan” was an enormous hit: ratings in October, 2018, exceeded those of October, 2016—the height of the Presidential campaign.

Ailes and Trump were friendly. “They spoke all the time,” a former Fox executive says. They had lunch shortly before Trump announced his candidacy, and Ailes gave Trump political tips during the primaries. Ken LaCorte contends that Ailes took note of “Trump’s crazy behavior”; but Trump’s growing political strength was also obvious. According to the former Fox executive, Trump made Ailes “nervous”: “He thought Trump was a wild card. Someone Ailes could not bully or intimidate.”

in 2016 that the network’s executives “made a business decision” to give on-air stars “slack” to choose their candidates. Hannity was an early Trump supporter; O’Reilly was neutral; Megyn Kelly remained skeptical

Kelly kept pressing Trump: “You once told a contestant on ‘Celebrity Apprentice’ it would be a pretty picture to see her on her knees. Does that sound to you like the temperament of a man we should elect President?” But he’d already won over Republican viewers. (Fox received a flood of e-mails, almost all of them anti-Kelly.) The showdown helped shape Trump’s image as shamelessly unsinkable.

Fox, however, may have given Trump a little help. A pair of Fox insiders and a source close to Trump believe that Ailes informed the Trump campaign about Kelly’s question. Two of those sources say that they know of the tipoff from a purported eyewitness. In addition, a former Trump campaign aide says that a Fox contact gave him advance notice of a different debate question, which asked the candidates whether they would support the Republican nominee, regardless of who won. The former aide says that the heads-up was passed on to Trump, who was the only candidate who said that he wouldn’t automatically support the Party’s nominee—a position that burnished his image as an outsider.

Ailes, meanwhile, joined Trump’s debate team, further erasing the line between Fox and conservative politicians. Ailes also began developing a plan to go into business with Trump. The Sunday before the election, Ailes called Steve Bannon, Trump’s campaign chairman, and said that he’d been talking with Trump about launching Trump TV, a nationalist competitor to Fox. Ailes was so excited that he was willing to forfeit his severance payment from Fox, which was attached to a non-compete agreement. He asked Bannon to join the venture and to start planning it as soon as Trump lost the election.

Any hopes that Fox would clean house after Ailes’s departure vanished on August 12, 2016, when Fox named two Ailes loyalists as co-presidents: Jack Abernethy, an executive who managed Fox’s local stations, and Bill Shine. The opinion side of Fox News, which Shine had run, had won out, as had his friend Sean Hannity.

For years, Ailes had been the focus of liberal complaints, and so when Fox pushed him out many people thought that the channel would change. They were right. The problem, Fox’s critics say, is that it’s become a platform for Trump’s authoritarianism. “I know Roger Ailes was reviled,” Charlie Black, the lobbyist, said. “But he did produce debates of both sides. Now Fox is just Trump, Trump, Trump.” Murdoch may find this development untroubling: in 1995, he told this magazine, “The truth is—and we Americans don’t like to admit it—that authoritarian societies can work.

News of Trump’s payoffs to silence Daniels, and Cohen’s criminal attempts to conceal them as legal fees, remained unknown to the public until the Wall Street Journal broke the story, a year after Trump became President.

Murdoch “was gone a lot,” adding, “He’s old. He likes the idea that he’s running it, but the lunatics took over the asylum.”

Falzone’s story didn’t run—it kept being passed off from one editor to the next. After getting one noncommittal answer after another from her editors, Falzone at last heard from LaCorte, who was then the head of FoxNews.com. Falzone told colleagues that LaCorte said to her, “Good reporting, kiddo. But Rupert wants Donald Trump to win. So just let it go.” LaCorte denies telling Falzone this, but one of Falzone’s colleagues confirms having heard her account at the time.

” The celebrity opinion-show hosts who drive the ratings became unbridled and unopposed. Hannity, as the network’s highest-rated and highest-paid star, was especially empowered—and, with him, so was Trump.

Richie told me, “Fox News was culpable. I voted for Trump, and I like Fox, but they did their own ‘catch and kill’ on the story to protect him.” He said that he’d worked closely with Falzone on the article, and that “she did her homework—she had it.” He says he warned her that Fox would never run it, but “when they killed it she was devastated.” Richie believes that the story “would have swayed the election.

Shine became “an expert in collecting and enforcing soft power,” adding, “He was responsible for on-air contributors to programs, so ultimately you were auditioning for Bill Shine. He was the one who would give you the lucrative contract. He controlled the narrative that way.

some people at Fox called him Bill the Butler, because he was so subservient to Ailes. A former Fox co-host says, “He’s perfect for the White House job. He’s a yes-man.” Another Fox alumnus said, “His only talent was following orders, sucking up to power, and covering up for people.”

Ailes and a small group kept a close eye on internal talent. “We had a file on pretty much everyone,” the former Fox executive said, adding that Ailes talked about “putting hits” in the media on anyone who “got out of line.”

If a woman complained about being sexually harassed, he said, Shine or other supervisors intimidated her into silence, reduced her air time, or discontinued her contract. The former executive recalls, “Shine would talk to the woman with a velvet glove, saying, ‘Don’t worry about it’—and, if that didn’t work, he’d warn her it would ruin her career.”

Judd Burstein, an attorney whose client was interviewed by prosecutors, told me, “I don’t think someone can be a serial sexual abuser in a large organization without enablers like Shine.”

Two months after Shine left Fox, Hannity became a matchmaker, arranging a dinner with the President at the White House, attended by himself, Shine, and Scaramucci, at that time Trump’s communications director. Hannity proposed Shine as a top communications official, or even as a deputy chief of staff. A year later, Shine was both.

Murdoch appears to have been wise in securing a rapprochement. Telecommunications is a highly regulated industry, and under Trump the government has consistently furthered Murdoch’s business interests, to the detriment of his rivals. Hundt, the former F.C.C. chairman, told me that “there have been three moves that have taken place in the regulatory and antitrust world” involving telecommunications “that are extremely unusual, and the only way to explain them is that they’re pro-Fox, pro-Fox, and pro-Fox.”

Last June, after only six months of deliberation, the Trump Administration approved Fox’s bid to sell most of its entertainment assets to Disney, for seventy-one billion dollars. The Murdoch family will receive more than two billion dollars in the deal, and will become a major stockholder in the combined company

In July, the F.C.C. blocked Sinclair Broadcast Group, a conservative rival to Fox, from combining with the Tribune Media Company. The F.C.C. argued that the deal would violate limits on the number of TV stations one entity can own, upending Sinclair’s hope of becoming the next Fox.

The Justice Department, meanwhile, went to court in an effort to stop A. T. & T.’s acquisition of Time Warner, which owns CNN

“There may be innocent explanations.” But, he adds, “Trump famously said you’re going to get sick and tired of winning, and that may not be true for the rest of America, but it sure is true of Murdoch.” He says of Murdoch, “He’s an incredibly cunning political player. He leaves no fingerprints. He’s been in the game of influencing government behavior to his benefit longer than most of us have been alive.”

Ann Coulter, who has been feuding with Trump over his immigration policy, said that the President told her that “Murdoch calls me every day.” She recalled that, “back when Trump was still speaking to me,” she complained to him that Fox was no longer inviting her to appear. She said that Trump told her, “Do you want me to call Murdoch and tell him to put you on?” Coulter accepted Trump’s offer. He may have called Hannity, not Murdoch, she says, but in any case she was invited back on Fox “within twelve hours.”

“Fox’s most important role since the election has been to keep Trump supporters in line.” The network has provided a non-stop counternarrative in which the only collusion is between Hillary Clinton and Russia; Robert Mueller, the special counsel, is perpetrating a “coup” by the “deep state”; Trump and his associates aren’t corrupt, but America’s law-enforcement officials and courts are; illegal immigration isn’t at a fifteen-year low, it’s “an invasion”; and news organizations that offer different perspectives are “enemies of the American people.”

Benkler’s assessment is based on an analysis of millions of American news stories that he and two co-authors, Robert Faris and Hal Roberts, undertook for their 2018 book, “Network Propaganda: Manipulation, Disinformation and Radicalization in American Politics.” Benkler told me that he and his co-authors had expected to find “symmetric polarization” in the left-leaning and the right-leaning media outlets. Instead, they discovered that the two poles of America’s media ecosystem function very differently. “It’s not the right versus the left,” Benkler says. “It’s the right versus the rest.”

Most American news outlets try to adhere to facts. When something proves erroneous, they run corrections, or, as Benkler and his co-authors write, “they check each other.” Far-left Web sites post as many bogus stories as far-right ones do, but mainstream and liberal news organizations tend to ignore suspiciously extreme material.

Conservative media outlets, however, focus more intently on confirming their audience’s biases, and are much more susceptible to disinformation, propaganda, and outright falsehoods (as judged by neutral fact-checking organizations such as PolitiFact). Case studies conducted by the authors show that lies and distortions on the right spread easily from extremist Web sites to mass-media outlets such as Fox, and only occasionally get corrected

Sometimes such pushback has a salutary effect. Recently, Chris Wallace told Sarah Sanders that her claim that “nearly four thousand known or suspected terrorists come into our country illegally” every year was wildly inaccurate. Showing Fox’s clout, the White House has dropped the talking point.

Unlike Glenn Beck, Hannity has been allowed to spew baseless conspiracy theories with impunity. For more than a year, Hannity and other hosts spread the lie that the hacking of Democratic Party e-mails during the 2016 campaign was an inside job. Hannity claimed that the hacking had been committed not by Russian cyber-warfare agents, as the U.S. intelligence community concluded, but by a Democratic staffer named Seth Rich, who had been murdered by unknown assailants on a D.C. street. Benkler and his co-authors studied Fox’s coverage, and found that not only did the channel give the Seth Rich lie a national platform; it also used the conspiracy story as a distraction, deploying it as a competing narrative when developments in Mueller’s investigation showed Trump in a bad light. In 2017, after Rich’s parents demanded an apology and advertisers began shunning the network, Fox finally ran a retraction, and Hannity dropped the story.

By then, Fox hosts had begun pushing a different conspiracy: the “Uranium One” story, which Hannity called “the biggest scandal ever involving Russia.” On an October, 2017, broadcast, Hannity claimed that Hillary Clinton, when she was Secretary of State, had given “to Vladimir Putin and Russia twenty per cent of America’s uranium, which is the foundational material to make nuclear weapons.” Ostensibly, the deal was in exchange for giant payments to the Clinton Foundation. Hannity also claimed that “the corrupt, lying mainstream media” was withholding this “bombshell” from Americans, because it was “complicit” in a “huge coverup.”

other reporting had poked holes in it, revealing that multiple government agencies had approved the deal, and that the quantity of uranium was insignificant. Yet Fox kept flogging it as the real national-security scandal involving Russia.

Alisyn Camerota was a co-host on “Fox & Friends” for years before joining CNN, in 2014

 ‘Fox & Friends’ was a fun show, but it was not a news show,” she says. “It regularly broke the rules of journalism. It was basically Roger’s id on TV. He’d wake up in the morning with some bee in his bonnet, spout it off to Bill Shine, and Shine would tell us to put it on TV.” She says that the show’s producers would “cull far-right, crackpot Web sites” for content, and adds, “Never did I hear anyone worry about getting a second source. The single phrase I heard over and over was ‘This is going to outrage the audience!’ You inflame the viewers so that no one will turn away. Those were the standards.”

Fox co-host Kimberly Guilfoyle often prepared for “The Five” by relying on information provided to her by an avid fan: a viewer from Georgia named David Townsend, who had no affiliation either with Fox News or with journalism.

Aki Peritz, a former C.I.A. analyst who is an adjunct professor at American University, has written that Fox News has become an inviting target for foreign spy agencies, because “it’s what the President sees.

a source who spoke to me about Guilfoyle and Townsend says, “It’s even worse than a conspiracy of the dark Web, or something trying to manipulate Fox. It was just a guy in his underwear in Georgia who had influence over Fox News! And Fox News influences the President!”

Judging from the timing of Trump’s tweets, Gertz believes that the President records “Fox & Friends” and views it from the beginning, often with a slight delay. As Trump watches, he frequently posts about points that he agrees with. Since August, 2018, Media Matters has tallied more than two hundred instances of Trump disseminating Fox News items to his fifty-eight million Twitter followers. “Trump serves as a carnival barker for Fox,” Levin says, giving invaluable promotional help to the channel.

Fox hosts sometimes reverse their opinions in order to toe the Trump line: Hannity, who in the Obama era called negotiations with North Korea “disturbing,” now calls such efforts a “huge foreign-policy win.” But Gertz has come to believe that Fox drives Trump more than Trump drives Fo

White House aides confirm that Trump has repeatedly walked away from compromises at the last moment because Fox hosts and guests opposed the deals.

According to a Senate staffer, one high-profile Republican senator claims that his preferred way of getting the President’s ear is by going on Fox. He calls a friendly host and offers to appear on the air; usually, before he’s taken his makeup off in the greenroom Trump is calling him

Fox hosts played a key part in driving Trump’s recent shutdown of the government and his declaration of a national emergency on the southern border. Hannity and Dobbs urged Trump nightly on their shows to make these moves; according to press reports, they also advised Trump personally to do so.

For the next thirty-five days, Hannity and the other Fox hosts kept cheering Trump on, even as polls showed that the American public was increasingly opposed to the shutdown. Oliver Darcy, of CNN, says that Democrats, rather than negotiating with Trump, “might as well call Sean Hannity and get him on the phone,” adding, “It seems we sort of elected Sean Hannity when we elected Trump.”

“The President’s world view is being specifically shaped by what he sees on Fox News, but Fox’s goals are ratings and money, which they get by maximizing rage. It’s not a message that is going to serve the rest of the country.

Trump and Fox are employing the same risky model: inflaming the base and intensifying its support, rather than building a broader coalition. Narrowcasting may generate billions of dollars for a cable channel, but as a governing strategy it inevitably alienates the majority. The problem for Trump, as one former Fox host puts it, is that “he can’t afford to lose Fox, because it’s all he’s got.”

Similarly, Fox has a financial incentive to make Trump look good. Cable ratings at both Fox and MSNBC dip when the news is bad for their audience’s side. Van Susteren likens the phenomenon to audiences turning away when their sports team is losing

A source close to Trump says that the President has been complaining that Shine hasn’t been aggressive enough. Late last year, Trump told the source, “Shine promised me my press coverage would get better, but it’s gotten worse.” The source says, “Trump thought he was getting Roger Ailes but instead he got Roger Ailes’s gofer.”

Shine has practically ended White House press briefings. Trump prefers to be his own spokesman. “He always thought he did it the best,” a former senior White House official says. “But the problem is that you lose deniability. It’s become a trapeze act with no net, 24/7. The shutdown messaging was a crisis. There was no exit strategy.”

“It was always clear that this wasn’t just another news organization,” Rosenberg told me. “But when Ailes departed, and Trump was elected, the network changed. They became more combative, and started treating me like an enemy, not an opponent.” With Shine joining Trump at the White House, he said, “it’s as if the on-air talent at Fox now have two masters—the White House and the audience.” In his view, the network has grown so allied with the White House in the demonization of Trump’s critics that “Fox is no longer conservative—it’s anti-democratic.”

For two years, the network has been priming its viewers to respond with extraordinary anger should the country’s law-enforcement authorities close in on the President. According to Media Matters, in the first year after Mueller was appointed Hannity alone aired four hundred and eighty-six segments attacking the federal criminal investigation into Russian interference in the 2016 election; thirty-eight per cent of those segments claimed that law-enforcement officials had broken the law.

Hannity has spoken of “a coup,” and a guest on Laura Ingraham’s program, the lawyer Joseph diGenova, declared, “It’s going to be total war. And, as I say to my friends, I do two things—I vote and I buy guns.”

“In a hypothetical world without Fox News, if President Trump were to be hit hard by the Mueller report, it would be the end of him. But, with Fox News covering his back with the Republican base, he has a fighting chance, because he has something no other President in American history has ever had at his disposal—a servile propaganda operation.”

This shift, combined with business-friendly tax and regulatory policy, ushered in a period of mergers and acquisitions that created megacorporations

In the past 20 years, more than 75 percent of American industries, from airlines to pharmaceuticals, have experienced increased concentration, and the average size of public companies has tripled. The results are a decline in entrepreneurship, stalled productivity growth, and higher prices and fewer choices for consumers.

Because Facebook so dominates social networking, it faces no market-based accountability. This means that every time Facebook messes up, we repeat an exhausting pattern: first outrage, then disappointment and, finally, resignation.

Over a decade later, Facebook has earned the prize of domination. It is worth half a trillion dollars and commands, by my estimate, more than 80 percent of the world’s social networking revenue. It is a powerful monopoly, eclipsing all of its rivals and erasing competition from the social networking category.

Facebook’s monopoly is also visible in its usage statistics. About 70 percent of American adults use social media, and a vast majority are on Facebook products

Over two-thirds use the core site, a third use Instagram, and a fifth use WhatsApp.

As a result of all this, would-be competitors can’t raise the money to take on Facebook. Investors realize that if a company gets traction, Facebook will copy its innovations, shut it down or acquire it for a relatively modest sum

Facebook’s dominance is not an accident of history. The company’s strategy was to beat every competitor in plain view, and regulators and the government tacitly — and at times explicitly — approved

The F.T.C.’s biggest mistake was to allow Facebook to acquire Instagram and WhatsApp. In 2012, the newer platforms were nipping at Facebook’s heels because they had been built for the smartphone, where Facebook was still struggling to gain traction. Mark responded by buying them, and the F.T.C. approved.

Neither Instagram nor WhatsApp had any meaningful revenue, but both were incredibly popular. The Instagram acquisition guaranteed Facebook would preserve its dominance in photo networking, and WhatsApp gave it a new entry into mobile real-time messaging.

When it hasn’t acquired its way to dominance, Facebook has used its monopoly position to shut out competing companies or has copied their technology.

In 2014, the rules favored curiosity-inducing “clickbait” headlines. In 2016, they enabled the spread of fringe political views and fake news, which made it easier for Russian actors to manipulate the American electorate.

As markets become more concentrated, the number of new start-up businesses declines. This holds true in other high-tech areas dominated by single companies, like search (controlled by Google) and e-commerce (taken over by Amazon)

I don’t blame Mark for his quest for domination. He has demonstrated nothing more nefarious than the virtuous hustle of a talented entrepreneur

It’s on our government to ensure that we never lose the magic of the invisible hand. How did we allow this to happen

a narrow reliance on whether or not consumers have experienced price gouging fails to take into account the full cost of market domination

It doesn’t recognize that we also want markets to be competitive to encourage innovation and to hold power in check. And it is out of step with the history of antitrust law. Two of the last major antitrust suits, against AT&T and IBM in the 1980s, were grounded in the argument that they had used their size to stifle innovation and crush competition.

It is a disservice to the laws and their intent to retain such a laserlike focus on price effects as the measure of all that antitrust was meant to do.”

Facebook is the perfect case on which to reverse course, precisely because Facebook makes its money from targeted advertising, meaning users do not pay to use the service. But it is not actually free, and it certainly isn’t harmless.

We pay for Facebook with our data and our attention, and by either measure it doesn’t come cheap.

The choice is mine, but it doesn’t feel like a choice. Facebook seeps into every corner of our lives to capture as much of our attention and data as possible and, without any alternative, we make the trade.

The vibrant marketplace that once drove Facebook and other social media companies to compete to come up with better products has virtually disappeared. This means there’s less chance of start-ups developing healthier, less exploitative social media platforms. It also means less accountability on issues like privacy.

The most problematic aspect of Facebook’s power is Mark’s unilateral control over speech. There is no precedent for his ability to monitor, organize and even censor the conversations of two billion people.

Facebook engineers write algorithms that select which users’ comments or experiences end up displayed in the News Feeds of friends and family. These rules are proprietary and so complex that many Facebook employees themselves don’t understand them.

What started out as lighthearted entertainment has become the primary way that people of all ages communicate online.

In January 2018, Mark announced that the algorithms would favor non-news content shared by friends and news from “trustworthy” sources, which his engineers interpreted — to the confusion of many — as a boost for anything in the category of “politics, crime, tragedy.”

As if Facebook’s opaque algorithms weren’t enough, last year we learned that Facebook executives had permanently deleted their own messages from the platform, erasing them from the inboxes of recipients; the justification was corporate security concerns.

No one at Facebook headquarters is choosing what single news story everyone in America wakes up to, of course. But they do decide whether it will be an article from a reputable outlet or a clip from “The Daily Show,” a photo from a friend’s wedding or an incendiary call to kill others.

Mark knows that this is too much power and is pursuing a twofold strategy to mitigate it. He is pivoting Facebook’s focus toward encouraging more private, encrypted messaging that Facebook’s employees can’t see, let alone control

Second, he is hoping for friendly oversight from regulators and other industry executives.

In an op-ed essay in The Washington Post in March, he wrote, “Lawmakers often tell me we have too much power over speech, and I agree.” And he went even further than before, calling for more government regulation — not just on speech, but also on privacy and interoperability, the ability of consumers to seamlessly leave one network and transfer their profiles, friend connections, photos and other data to another.

I don’t think these proposals were made in bad faith. But I do think they’re an attempt to head off the argument that regulators need to go further and break up the company. Facebook isn’t afraid of a few more rules. It’s afraid of an antitrust case and of the kind of accountability that real government oversight would bring.

We don’t expect calcified rules or voluntary commissions to work to regulate drug companies, health care companies, car manufacturers or credit card providers. Agencies oversee these industries to ensure that the private market works for the public good. In these cases, we all understand that government isn’t an external force meddling in an organic market; it’s what makes a dynamic and fair market possible in the first place. This should be just as true for social networking as it is for air travel or pharmaceuticals.

Just breaking up Facebook is not enough. We need a new agency, empowered by Congress to regulate tech companies. Its first mandate should be to protect privacy.

First, Facebook should be separated into multiple companies. The F.T.C., in conjunction with the Justice Department, should enforce antitrust laws by undoing the Instagram and WhatsApp acquisitions and banning future acquisitions for several years.

How would a breakup work? Facebook would have a brief period to spin off the Instagram and WhatsApp businesses, and the three would become distinct companies, most likely publicly traded.

Facebook is indeed more valuable when there are more people on it: There are more connections for a user to make and more content to be shared. But the cost of entering the social network business is not that high. And unlike with pipes and electricity, there is no good argument that the country benefits from having only one dominant social networking company.

others worry that the breakup of Facebook or other American tech companies could be a national security problem. Because advancements in artificial intelligence require immense amounts of data and computing power, only large companies like Facebook, Google and Amazon can afford these investments, they say. If American companies become smaller, the Chinese will outpace us.

The American government needs to do two things: break up Facebook’s monopoly and regulate the company to make it more accountable to the American people.

But the biggest winners would be the American people. Imagine a competitive market in which they could choose among one network that offered higher privacy standards, another that cost a fee to join but had little advertising and another that would allow users to customize and tweak their feeds as they saw fit

The cost of breaking up Facebook would be next to zero for the government, and lots of people stand to gain economically. A ban on short-term acquisitions would ensure that competitors, and the investors who take a bet on them, would have the space to flourish. Digital advertisers would suddenly have multiple companies vying for their dollars.

The Europeans have made headway on privacy with the General Data Protection Regulation, a law that guarantees users a minimal level of protection. A landmark privacy bill in the United States should specify exactly what control Americans have over their digital information, require clearer disclosure to users and provide enough flexibility to the agency to exercise effective oversight over time

The agency should also be charged with guaranteeing basic interoperability across platforms.

Finally, the agency should create guidelines for acceptable speech on social media

We will have to create similar standards that tech companies can use. These standards should of course be subject to the review of the courts, just as any other limits on speech are. But there is no constitutional right to harass others or live-stream violence.

These are difficult challenges. I worry that government regulators will not be able to keep up with the pace of digital innovation

I worry that more competition in social networking might lead to a conservative Facebook and a liberal one, or that newer social networks might be less secure if government regulation is weak

Professor Wu has written that this “policeman at the elbow” led IBM to steer clear “of anything close to anticompetitive conduct, for fear of adding to the case against it.”

Finally, an aggressive case against Facebook would persuade other behemoths like Google and Amazon to think twice about stifling competition in their own sectors, out of fear that they could be next.

The alternative is bleak. If we do not take action, Facebook’s monopoly will become even more entrenched. With much of the world’s personal communications in hand, it can mine that data for patterns and trends, giving it an advantage over competitors for decades to come.

This movement of public servants, scholars and activists deserves our support. Mark Zuckerberg cannot fix Facebook, but our government can.

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.

after using ThinkUp for about six months, I’ve found it to be an indispensable guide to how I navigate social networks.

“The goal is to make you act like less of a jerk online,” Ms. Trapani said. “The big goal is to create mindfulness and awareness, and also behavioral change.”

people often tweet and update without any perspective about themselves. That’s because Facebook and Twitter, as others have observed, have a way of infecting our brains.

Because social networks often suggest a false sense of intimacy, they tend to lower people’s self-control.

Like a drug or perhaps a parasite, they worm into your devices, your daily habits and your every free moment, and they change how you think.Continue reading the main story Continue reading the main story

For those of us most deeply afflicted, myself included, every mundane observation becomes grist for a 140-character quip, and every interaction a potential springboard into an all-consuming, emotionally wrenching flame battle.

One of the biggest dangers is saying something off the cuff that might make sense in a particular context, but that sounds completely off the rails to the wider public. The problem, in other words, is acting without thinking — being caught up in the moment, without pausing to reflect on the long-term consequences. You’re never more than a few taps away from an embarrassment that might ruin your career, or at least your reputation, for years to come.

More basically, though, it’s helped me pull back from social networks. Each week, ThinkUp tells me how often I’ve tweeted. Sometimes that number is terribly high — a few weeks ago it was more than 800 times — and I realize I’m probably overtaxing my followers

getting a daily reminder from ThinkUp that there are good ways and bad ways to behave online — has a tendency to focus the mind.

even though “never tweet” became a popular, ironic thing to tweet this year, actually never tweeting, and never being on Facebook, is becoming nearly impossible for many people.

ThinkUp charges $5 a month for each social network you connect to it. Is it worth it? After all, there’s a better, more surefire way of avoiding any such long-term catastrophe caused by social media: Just stop using social networks.

your online profile plays an important role in how you’re perceived by potential employers. In a recent survey commissioned by the job-hunting site CareerBuilder, almost half of companies said they perused job-seekers’ social networking profiles to look for red flags and to see what sort of image prospective employees portrayed online.

The main issue constraining growth, the founders say, is that it has been difficult to explain to people why they might need ThinkUp.

That may change as more people falter on social networks, either by posting unthinking comments that end up damaging their careers, or simply by annoying people to the point that their online presence becomes a hindrance to their real-life prospects.

Over time, the same network efficiencies that had given them their great advantages would become the instrument of their failures.

In the financial services industry, it led to the financial crisis

In the case of Wal-Mart, its adoption of technology to manage its supply chain at first reaped great benefits, but over time it cost competitors and suppliers hundreds of thousands of jobs, thus “gradually impoverishing its own customer base,”

The N.S.A.? It developed computer technology that could monitor the entire world — and, in the process, lost control of the contractors it employed.

“Networks need a great number of people to participate in them to generate significant value. But when they have them, only a small number of people get paid. This has the net effect of centralizing wealth and limiting overall economic growth.” Thus, in Lanier’s view, is income inequality also partly a consequence of the digital economy.

His great example here is Kodak and Instagram. At its height, writes Lanier “Kodak employed more than 140,000 people.” Yes, Kodak made plenty of mistakes, but look at what is replacing it: “When Instagram was sold to Facebook for a billion dollars in 2012, it employed only 13 people.”

the value of these new companies comes from us. “Instagram isn’t worth a billion dollars just because those 13 employees are extraordinary,” he writes. “Instead, its value comes from the millions of users who contribute to the network without being paid for it.”

There are two additional components to Lanier’s thesis. The first is that the digital economy has done as much as any single thing to hollow out the middle class

It is Lanier’s radical idea that people should get paid whenever their information is used. He envisions a different kind of digital economy, in which creators of content — whether a blog post or a Facebook photograph — would receive micropayments whenever that content was used

A digital economy that appears to give things away for free — in return for being able to invade the privacy of its customers for commercial gain — isn’t free at all, he argues.

Lanier wants to create a dynamic where digital networks expand the pie rather than shrink it, and rebuild the middle class instead of destroying it.

Lulewicz' findings suggest that the ruling elites drew their power from social networks created by the masses.

"That is, even though elite interests and political strategies waxed and waned and collapsed and flourished, very basic relationships and networks were some of the strongest, most durable aspects of society."

"Because these very basic networks were so durable, they allowed these societies -- especially common people -- to buffer against and mediate the uncertainties associated with major political and economic change. They may have said, 'You go live on top of that huge mound and do your sacred rituals, and we will go about life as usual for the most part.' These communication networks served as a social constant for these people and allowed their cultures to persist for thousands of years even across transformations that could have been catastrophic."