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The Anti-Defamation League said it has documented "disturbing antisemitism" on multiple social media platforms, including Facebook, Instagram, Twitter and TikTok

"ADL has also seen an increase in on-the-ground activity that demonizes Israel and that has crossed at times into antisemitism,

Thousands of people have marched in major U.S. cities in recent weeks to protest Israel's actions

In New York City Thursday evening, 26 people were arrested as pro-Israel and pro-Palestinian demonstrators clashed in Times Square, and police were investigating the assault of a Jewish man in the same area as a hate crime

"The anti-Semitism we're seeing across our country isn’t in isolation and isn’t just a few incidents

Americans largely support Israel – but sympathy for Palestinians is on the rise

"Since national data collection began in 1992, the worst months of each decade revolved around disputes in the Holy Land or around conflictual elections,

the month that saw the most antisemitic hate crimes in the U.S. was March 1994

when an American-Israeli man fatally shot 29 people and wounded more than a hundred in the West Bank

Over the last decade, however, the most hate crimes happened around the 2018 U.S. midterm elections

In 2019, antisemitic hate crimes hit multiyear highs and, for the first time in recent memory, Jews were the top target in America's three largest cities

Muslims in the U.S. have also been the targets of hate in recent weeks

"Death to Palestine

Twitter and the nation’s leading social media companies including Facebook, Google’s YouTube and TikTok are increasingly on the hot seat over climate change misinformation

This year, there have been 83,590

yet all of the top five Twitter accounts pushing climate change denial promote claims it does.

One kindergarten in the eastern Chinese city of Hangzhou interspersed its lessons in September with four days of what it called “military training” for its 5- and 6-year-olds. The children, dressed in military fatigues, held Chinese flags and performed salutes, according to the school’s official WeChat social-media account.

In 2016, the party issued what it said were reform guidelines calling on its Communist Youth League to help lead on social media. The Youth League began opening accounts on platforms including Douyin, China’s version of TikTok. It also started an official account on Bilibili, a video-hosting platform akin to China’s YouTube whose users are mainly under 25. The Youth League and its regional arms now have almost 11.5 million followers there.

The U.S. State Department condemned the violence and arrests, citing the Russian government's attempt to control social media platforms and tighten restrictions on independent media.

Navalny rose to fame for his investigations that exposed corruption, and for political mobilization against Putin's regime. He recently reprised that role, releasing a bombshell video that accuses Putin of using a slush fund to build a palace on the Black Sea. That report has now been viewed nearly 100 million times on YouTube.

With Navalny now ordered to remain in jail, a court will weigh imposing a prison sentence on Feb. 2 stemming from the earlier case, according to state-run media.

Navalny says his fraud conviction was retribution for his activism. Election officials have also cited the mark on his record as justification to reject his attempt to run against Putin for the presidency.

When Navalny was in Germany, he spent weeks in a medically induced coma as doctors sought to help his body recover from a variant of Novichok, a lethal Soviet-era nerve agent.

"There has been a lot of speculation lately that the convict Navalny was unable to show up at the inspectorate as he was in a coma," said Yelena Korobkova, a department head at the FSIN. "However, he had systematically violated the terms of his probationary period even before his hospitalization," she said, accusing Navalny of missing other dates in the first half of 2020.

They argued that journalists and researchers were using CrowdTangle, a kind of turbocharged search engine that allows users to analyze Facebook trends and measure post performance, to dig up information they considered unhelpful — showing, for example, that right-wing commentators like Ben Shapiro and Dan Bongino were getting much more engagement on their Facebook pages than mainstream news outlets.

These executives argued that Facebook should selectively disclose its own data in the form of carefully curated reports, rather than handing outsiders the tools to discover it themselves.Team Selective Disclosure won, and CrowdTangle and its supporters lost.

the CrowdTangle story is important, because it illustrates the way that Facebook’s obsession with managing its reputation often gets in the way of its attempts to clean up its platform

The company, blamed for everything from election interference to vaccine hesitancy, badly wants to rebuild trust with a skeptical public. But the more it shares about what happens on its platform, the more it risks exposing uncomfortable truths that could further damage its image.

Facebook’s executives were more worried about fixing the perception that Facebook was amplifying harmful content than figuring out whether it actually was amplifying harmful content. Transparency, they said, ultimately took a back seat to image management.

the executives who pushed hardest for transparency appear to have been sidelined. Mr. Silverman, CrowdTangle’s co-founder and chief executive, has been taking time off and no longer has a clearly defined role at the company, several people with knowledge of the situation said. (Mr. Silverman declined to comment about his status.) And Mr. Boland, who spent 11 years at Facebook, left the company in November.

“One of the main reasons that I left Facebook is that the most senior leadership in the company does not want to invest in understanding the impact of its core products,” Mr. Boland said, in his first interview since departing. “And it doesn’t want to make the data available for others to do the hard work and hold them accountable.”

Mr. Boland, who oversaw CrowdTangle as well as other Facebook transparency efforts, said the tool fell out of favor with influential Facebook executives around the time of last year’s presidential election, when journalists and researchers used it to show that pro-Trump commentators were spreading misinformation and hyperpartisan commentary with stunning success.

“People were enthusiastic about the transparency CrowdTangle provided until it became a problem and created press cycles Facebook didn’t like,” he said. “Then, the tone at the executive level changed.”

Facebook was happy that I and other journalists were finding its tool useful. With only about 25,000 users, CrowdTangle is one of Facebook’s smallest products, but it has become a valuable resource for power users including global health organizations, election officials and digital marketers, and it has made Facebook look transparent compared with rival platforms like YouTube and TikTok, which don’t release nearly as much data.

Last fall, the leaderboard was full of posts by Mr. Trump and pro-Trump media personalities. Since Mr. Trump was barred from Facebook in January, it has been dominated by a handful of right-wing polemicists like Mr. Shapiro, Mr. Bongino and Sean Hannity, with the occasional mainstream news article, cute animal story or K-pop fan blog sprinkled in.

But the mood shifted last year when I started a Twitter account called @FacebooksTop10, on which I posted a daily leaderboard showing the sources of the most-engaged link posts by U.S. pages, based on CrowdTangle data.

The account went semi-viral, racking up more than 35,000 followers. Thousands of people retweeted the lists, including conservatives who were happy to see pro-Trump pundits beating the mainstream media and liberals who shared them with jokes like “Look at all this conservative censorship!” (If you’ve been under a rock for the past two years, conservatives in the United States frequently complain that Facebook is censoring them.)

Inside Facebook, the account drove executives crazy. Some believed that the data was being misconstrued and worried that it was painting Facebook as a far-right echo chamber. Others worried that the lists might spook investors by suggesting that Facebook’s U.S. user base was getting older and more conservative. Every time a tweet went viral, I got grumpy calls from Facebook executives who were embarrassed by the disparity between what they thought Facebook was — a clean, well-lit public square where civility and tolerance reign — and the image they saw reflected in the Twitter lists.

Mr. Boland, the former Facebook vice president, said that was a convenient deflection. He said that in internal discussions, Facebook executives were less concerned about the accuracy of the data than about the image of Facebook it presented.“It told a story they didn’t like,” he said of the Twitter account, “and frankly didn’t want to admit was true.”

Several executives proposed making reach data public on CrowdTangle, in hopes that reporters would cite that data instead of the engagement data they thought made Facebook look bad.But Mr. Silverman, CrowdTangle’s chief executive, replied in an email that the CrowdTangle team had already tested a feature to do that and found problems with it. One issue was that false and misleading news stories also rose to the top of those lists.“Reach leaderboard isn’t a total win from a comms point of view,” Mr. Silverman wrote.

executives argued that my Top 10 lists were misleading. They said CrowdTangle measured only “engagement,” while the true measure of Facebook popularity would be based on “reach,” or the number of people who actually see a given post. (With the exception of video views, reach data isn’t public, and only Facebook employees and page owners have access to it.)

Mr. Schultz, Facebook’s chief marketing officer, had the dimmest view of CrowdTangle. He wrote that he thought “the only way to avoid stories like this” would be for Facebook to publish its own reports about the most popular content on its platform, rather than releasing data through CrowdTangle.“If we go down the route of just offering more self-service data you will get different, exciting, negative stories in my opinion,” he wrote.

there’s a problem with reach data: Most of it is inaccessible and can’t be vetted or fact-checked by outsiders. We simply have to trust that Facebook’s own, private data tells a story that’s very different from the data it shares with the public.

Mr. Zuckerberg is right about one thing: Facebook is not a giant right-wing echo chamber.But it does contain a giant right-wing echo chamber — a kind of AM talk radio built into the heart of Facebook’s news ecosystem, with a hyper-engaged audience of loyal partisans who love liking, sharing and clicking on posts from right-wing pages, many of which have gotten good at serving up Facebook-optimized outrage bait at a consistent clip.

CrowdTangle’s data made this echo chamber easier for outsiders to see and quantify. But it didn’t create it, or give it the tools it needed to grow — Facebook did — and blaming a data tool for these revelations makes no more sense than blaming a thermometer for bad weather.

It’s worth noting that these transparency efforts are voluntary, and could disappear at any time. There are no regulations that require Facebook or any other social media companies to reveal what content performs well on their platforms, and American politicians appear to be more interested in fighting over claims of censorship than getting access to better data.

It’s also worth noting that Facebook can turn down the outrage dials and show its users calmer, less divisive news any time it wants. (In fact, it briefly did so after the 2020 election, when it worried that election-related misinformation could spiral into mass violence.) And there is some evidence that it is at least considering more permanent changes.

The project, which some employees refer to as the “Top 10” project, is still underway, the people said, and it’s unclear whether its findings have been put in place. Mr. Osborne, the Facebook spokesman, said that the team looks at a variety of ranking changes, and that the experiment wasn’t driven by a desire to change the Top 10 lists.

This year, Mr. Hegeman, the executive in charge of Facebook’s news feed, asked a team to figure out how tweaking certain variables in the core news feed ranking algorithm would change the resulting Top 10 lists, according to two people with knowledge of the project.

As for CrowdTangle, the tool is still available, and Facebook is not expected to cut off access to journalists and researchers in the short term, according to two people with knowledge of the company’s plans.

Mr. Boland, however, said he wouldn’t be surprised if Facebook executives decided to kill off CrowdTangle entirely or starve it of resources, rather than dealing with the headaches its data creates.

So far, more than 93.1 million people have voted early. That's about 68% of the total votes in 2016.

Trump touts what was a strong economy before COVID-19 shocked the country, his tax cuts and trade deals, as well as reshaping the Supreme Court in a conservative direction.

Democrats — and many independents, according to the polls — see a president who takes pride in not playing by the rules, has inflamed racial division, is untruthful, mishandled a pandemic, damaged the country's image around the world and is an existential threat to progress and justice.

"No one will be safe in Joe Biden's America," Trump said this summer. "I can't even call it Biden's America — the guy doesn't even know he's alive."

Voters have also said consistently that Biden would be better to handle the coronavirus, race relations and even crime,

But bigger than what the keys are to this election, the outcome will likely have consequences for how politics is practiced and how Americans conduct themselves for generations to come.

For Trump to win, there would have to be an even bigger polling error than in 2016.

The Trump campaign had hoped Trump's chances would get better if there was news of a potential vaccine for the coronavirus on the horizon or COVID-19 cases declining in the country. But neither has been true.

Trump's Ban On TikTok Suffers Another Legal Setback

There Will Be Superlatives: Trump Is About To Make History, No Matter What Happens

They have warned that Trump is the only thing standing between America and"socialism," claiming Biden is too inept to prevent being taken over by a radical left that wants to defund the police and bring crime to the suburbs.

Almost every election cycle, someone on one side or the other is claiming that this is the most important election in their lifetime. Well, this one actually probably is — and it appears voters think so, too.

"You're the worst president America has ever had," Democratic nominee Joe Biden, a former vice president, told Trump during their first presidential debate.

“I did a focus group tonight with women who voted for Trump in 2016,” Ms. Longwell wrote. “Not a single one was planning to vote for him again.”

In other words, Mr. Trump’s effort smacked of a too-late, too-lame apology to an ex who has long since moved on. It also underscored Mr. Trump’s special knack for making statements (or sending tweets) that are perfectly suited to being clipped, saved and hurled back in his face when facts contradict him later on, or in real time. Mr. Trump has proved himself, again and again, a grand master of delivering famous last words.

Mr. Trump seems to be tempting fate on a daily basis since he himself became infected.

He has said he is a “perfect physical specimen,” feels better than he did 20 years ago and is now “immune” from the disease — never mind that the course of the coronavirus has shown itself to be treacherous and unpredictable.

It kicked off on Day 2 when the first of four Trump White House press secretaries, Sean Spicer, claimed that the crowd gathered for Mr. Trump’s 2017 inauguration was “the largest audience to ever witness an inauguration, period.” Overhead photos of Mr. Trump’s inaugural crowd next to Mr. Obama’s proved this remark to be ridiculous, period.

He already boasted a long rap sheet of “unfortunate remarks,” all readily captured and spread via video, Twitter, TikTok and wherever else famous last words get immortalized these days.

“We have it totally under control,” Mr. Trump said in January on CNBC, an opening salvo of denial that would soon be hung around his neck.

He continues to insist that the virus is “disappearing,” an assertion flatly contradicted by rising rates of infection across much of the country in recent days.

Every president typically gets one or two shudder-worthy sound bites on their permanent record. President Barack Obama promised that “if you like your doctor, you can keep your doctor” under his health care plan, a proposition that proved false during the troubled rollout of the Affordable Care Act in 2013.

“Politicians are always going to say things they regret,” said Victoria Clarke, a longtime Republican communications strategist who has advised several elected officials and administrations

Traditionally, presidents have tried to avoid making statements that might prove embarrassing later on

But the response to the coronavirus has placed the White House’s pre-existing condition on, well, steroids.

The current outbreak in the White House has been accompanied by a video parade of “unfortunate remarks” — or, depending on your point of view, a rampage of karma.

Kayleigh McEnany, testing positive last week was accompanied by a now-infamous clip from a Fox News interview Ms. McEnany gave in February. “We will not see diseases like the coronavirus come here,” vowed the then-future press secretary.

Likewise, when Kellyanne Conway, a former senior White House adviser, revealed her own coronavirus diagnosis, numerous news media outlets and Twitter feeds resurrected an oft-mocked statement she made about the still-emerging outbreak in March. “It is being contained,” vowed Ms. Conway

“No president can go four years without making a comment that can be considered a ‘gotcha moment,’” said Erik Smith, a veteran Democratic spokesman and operative. “But this president seems to pile them up like cordwood and take joy in it.”

It has lent the president a level of credibility as a “straight shooter,” even as he has been caught in thousands of false statements, dubious boasts and comical reassurances.

“It affects virtually nobody!” Mr. Trump declared of the coronavirus at a packed rally in Ohio last month — another remark that would go literally viral. It did not age well.

imilar increases occurred at the same time for girls in Canada for mood disorders and for self-harm. Girls in the U.K. also experienced very large increases in anxiety, depression, and self-harm (with much smaller increases for boys).

Some have argued that these increases reflect nothing more than Gen Z’s increased willingness to disclose their mental-health problems. But researchers have found corresponding increases in measurable behaviors such as suicide (for both sexes), and emergency-department admissions for self-harm (for girls only). From 2010 to 2014, rates of hospital admission for self-harm did not increase at all for women in their early 20s, or for boys or young men, but they doubled for girls ages 10 to 14.

The available evidence suggests that Facebook’s products have probably harmed millions of girls. If public officials want to make that case, it could go like this:

2. The timing points to social media.

National surveys of American high-school students show that only about 63 percent reported using a “social networking site” on a daily basis back in 2010.

But as smartphone ownership increased, access became easier and visits became more frequent. By 2014, 80 percent of high-school students said they used a social-media platform on a daily basis, and 24 percent said that they were online “almost constantly.”

from 2010 to 2014, high-school students moved much more of their lives onto social-media platforms.

Notably, girls became much heavier users of the new visually oriented platforms, primarily Instagram (which by 2013 had more than 100 million users), followed by Snapchat, Pinterest, and Tumblr.

Boys are glued to their screens as well, but they aren’t using social media as much; they spend far more time playing video games. When a boy steps away from the console, he does not spend the next few hours worrying about what other players are saying about him

Instagram, in contrast, can loom in a girl’s mind even when the app is not open, driving hours of obsessive thought, worry, and shame.

3. The victims point to Instagram.

In 2017, British researchers asked 1,500 teens to rate how each of the major social-media platforms affected them on certain well-being measures, including anxiety, loneliness, body image, and sleep. Instagram scored as the most harmful, followed by Snapchat and then Facebook.

Facebook’s own research, leaked by the whistleblower Frances Haugen, has a similar finding: “Teens blame Instagram for increases in the rate of anxiety and depression … This reaction was unprompted and consistent across all groups.” The researchers also noted that “social comparison is worse” on Instagram than on rival apps.

Snapchat’s filters “keep the focus on the face,” whereas Instagram “focuses heavily on the body and lifestyle.

A recent experiment confirmed these observations: Young women were randomly assigned to use Instagram, use Facebook, or play a simple video game for seven minutes. The researchers found that “those who used Instagram, but not Facebook, showed decreased body satisfaction, decreased positive affect, and increased negative affect.”

4. No other suspect is equally plausible.

Correlation does not prove causation, but nobody has yet found an alternative explanation for the massive, sudden, gendered, multinational deterioration of teen mental health during the period in question.

The subset of studies that allow researchers to isolate social media, and Instagram in particular, show a much stronger relationship with poor mental health. The same goes for those that zoom in on girls rather than all teens.

In a 2019 internal essay, Andrew Bosworth, a longtime company executive, wrote:While Facebook may not be nicotine I think it is probably like sugar. Sugar is delicious and for most of us there is a special place for it in our lives. But like all things it benefits from moderation.

Bosworth was proposing what medical researchers call a “dose-response relationship.” Sugar, salt, alcohol, and many other substances that are dangerous in large doses are harmless in small ones.

his framing also implies that any health problems caused by social media result from the user’s lack of self-control. That’s exactly what Bosworth concluded: “Each of us must take responsibility for ourselves.” The dose-response frame also points to cheap solutions that pose no threat to its business model. The company can simply offer more tools to help Instagram and Facebook users limit their consumption.

social-media platforms are not like sugar. They don’t just affect the individuals who overindulge. Rather, when teens went from texting their close friends on flip phones in 2010 to posting carefully curated photographs and awaiting comments and likes by 2014, the change rewired everyone’s social life.

Improvements in technology generally help friends connect, but the move onto social-media platforms also made it easier—indeed, almost obligatory––for users to perform for one another.

Public performance is risky. Private conversation is far more playful. A bad joke or poorly chosen word among friends elicits groans, or perhaps a rebuke and a chance to apologize. Getting repeated feedback in a low-stakes environment is one of the main ways that play builds social skills, physical skills, and the ability to properly judge risk. Play also strengthens friendships.

When girls started spending hours each day on Instagram, they lost many of the benefits of play.

First, Congress should pass legislation compelling Facebook, Instagram, and all other social-media platforms to allow academic researchers access to their data. One such bill is the Platform Transparency and Accountability Act, proposed by the Stanford University researcher Nate Persily.

The wrong photo can lead to school-wide or even national infamy, cyberbullying from strangers, and a permanent scarlet letter

Performative social media also puts girls into a trap: Those who choose not to play the game are cut off from their classmates

Instagram and, more recently, TikTok have become wired into the way teens interact, much as the telephone became essential to past generations.

f those platforms. Without a proper control group, we can’t be certain that the experiment has been a catastrophic failure, but it probably has been. Until someone comes up with a more plausible explanation for what has happened to Gen Z girls, the most prudent course of action for regulators, legislators, and parents is to take steps to mitigate the harm.

(Boys lost less, and may even have gained, when they took up multiplayer fantasy games, especially those that put them into teams.)

Second, Congress should toughen the 1998 Children’s Online Privacy Protection Act. An early version of the legislation proposed 16 as the age at which children should legally be allowed to give away their data and their privacy.

Unfortunately, e-commerce companies lobbied successfully to have the age of “internet adulthood” set instead at 13. Now, more than two decades later, today’s 13-year-olds are not doing well. Federal law is outdated and inadequate. The age should be raised. More power should be given to parents, less to companies.

Third, while Americans wait for lawmakers to act, parents can work with local schools to establish a norm: Delay entry to Instagram and other social platforms until high school.

Right now, families are trapped. I have heard many parents say that they don’t want their children on Instagram, but they allow them to lie about their age and open accounts because, well, that’s what everyone else has done.

Kids today are, simply put, not learning how to be curious, critical adults — and they don’t seem to know what they’ve lost.

These high school students had become reliant, maybe even dependent, on social media companies’ algorithms.

Their dependence on technology sounds familiar to most of us. So many of us can barely remember when we didn’t have Amazon to fall back on when we needed a last-minute gift or when we waited by the radio for our favorite songs to play. Today, information, entertainment and connection are delivered to us on a conveyor belt, with less effort and exploration required of us than ever before.

What the kids I spoke to did not know is that these algorithms have been designed in a way that inevitably makes — and keeps — users unhappy.

A report by the nonprofit Center for Countering Digital Hate found that users could be served content related to suicide less than three minutes after downloading TikTok. Five minutes after that, they could come across a community promoting eating disorder content. Instagram is awash with soft-core pornography, offering a gateway to hard-core material on other sites (which are often equally lax about age verification). And all over social media are highly curated and filtered fake lives, breeding a sense of envy and inadequacy inside the developing brains of teenagers.

Social media companies know that content that generates negative feelings holds our attention longer than that which makes us feel good.

If you are a teenager feeling bad about yourself, your social media feed will typically keep delivering you videos and pictures that are likely to exacerbate negative feelings.

It is not a coincidence that teenage rates of sadness and suicide increased just as algorithmically driven social media content took over children’s and adolescents’ lives.

The role that social media has played in the declining mental health of teens also gives us a preview of what is coming for adults, with the quickening deployment of artificial intelligence and machine learning in our own lives. The psychological impact of the coming transition of thousands of everyday basic human tasks to machines will make the effect of social media look like child’s play.

In Mexico, the growing interest in all things Korean has made her a social-media sensation with more than 24 million followers on TikTok and over eight million subscribers to her YouTube channel, allowing her to gain popularity, financial stability and a romantic partner — all on her own terms.

“She had all this training in Korea, in this new Korea that allows her to land in a place like Mexico and be successful.”

A sort of a teacher of comparative pop culture, Ms. Kim offers lessons on popular Korean soap operas, lyrics, fashion standards, traditions and social norms. She once worked as a waitress in Mexico for a day and posted about her confusion with tips. (South Korea is a no-tip country.) She showed followers how Korean students crammed for exams. She started traveling across Mexico tasting regional delicacies.

Ms. Kim’s success tracks the growth of Korean influence in Mexico and the region.More than 2,000 Korean companies have a presence in Mexico, part of a so-called near-shoring strategy that has driven larger corporations — Kia, LG, Samsung, Hyundai, among others — to take advantage of a free-trade agreement with Canada and the United States.

K-pop, K-beauty and K-dramas have shown Latin Americans a new, different way to be cool.

K-pop bands have been performing to increasingly bigger and sold-out venues since 2012. This year, a summer festival will bring 16 Korean groups to Mexico City, with ticket prices starting at around $170.

Some newsstands specialize in magazines, posters and merchandise about South Korean celebrities. Netflix offers dubbing in “Latin Spanish” for Korean shows. Movie theaters stream live K-pop concerts performed abroad.

After finishing college in South Korea, Ms. Kim said she experienced severe stress. “I wanted to die and I wished to rest,” she said in one of her most popular videos. She has spoken openly about being hospitalized to take care of her mental health.

She attributes her exhaustion to Korea’s culture of sacrifice and grind that helped the country become an economic powerhouse after the Korean War.

“Everything is quick, quick, now, right this second,” Dr. Balderrama said. “This created a culture where there’s no place for mediocrity, there’s no place for those unwilling to compete.”

In Mexico, Ms. Kim hoped to find a more joyous life: “I saw how Latin culture is, how Latin people live and they’re living happily,” she said. “I don’t want to waste a single moment I’m in Latin America because it’s so precious to me.”

But if Ms. Kim has found a passion and a business, she has not completely found the peace of mind she was seeking. She’s in therapy to deal with what she described as some depression and anxiety.

Her large following and popularity has bred fear: “I feel people will forget me, that nobody will like me,” she said, worried about the toll of having to come up with creative content to remain relevant.

She does get criticized online by users who say she should go back to Korea, who ask whether she pays taxes in Mexico (she says she does) and who consider her another foreigner lured by life on the cheap and who contributes to the gentrification of parts of the country at the expense of Mexican residents.

No, says the other camp, led by Jonathan Haidt; the kids are not all right, their devices are partly to blame, and here are the studies showing why.

we should not wait for the replication crisis in the social sciences to resolve itself before we consider the question of whether the naysayers are on to something. And normal powers of observation and imagination should be sufficient to make us at least wary of smartphones.

These powerful instruments represent a technological advance on par with that of the power loom or the automobile

The achievement can be difficult to properly appreciate because instead of exerting power over physical processes and raw materials, they operate on social processes and the human psyche: They are designed to maximize attention, to make it as difficult as possible to look away.

they have transformed the qualitative experience of existing in the world. They give a person’s sociality the appearance and feeling of a theoretically endless open network, while in reality, algorithms quietly sort users into ideological, aesthetic, memetic cattle chutes of content.

Importantly, the process by which smartphones change us requires no agency or judgment on the part of a teen user, and yet that process is designed to provide what feels like a perfectly natural, inevitable, and complete experience of the world.

The expectation that children and adolescents will navigate new technologies with fully formed and muscular capacities for reason and responsibility often seems to go along with a larger abdication of responsibility on the part of the adults involved.

It is not a particular activity that you start and stop and resume, and it is not a social scene that you might abandon when it suits you.

It is instead a complete shadow world of endless images; disembodied, manipulable personas; and the ever-present gaze of others. It lives in your pocket and in your mind.

The price you pay for its availability—and the engine of its functioning—is that you are always available to it, as well. Unless you have a strength of will that eludes most adults, its emissaries can find you at any hour and in any place to issue your summons to the grim pleasure palace.

the self-restraint and self-discipline required to use a smartphone well—that is, to treat it purely as an occasional tool rather than as a totalizing way of life—are unreasonable things to demand of teenagers

these are unreasonable things to demand of me, a fully adult woman

To enjoy the conveniences that a smartphone offers, I must struggle against the lure of the permanent scroll, the notification, the urge to fix my eyes on the circle of light and keep them fixed. I must resist the default pseudo-activity the smartphone always calls its user back to, if I want to have any hope of filling the moments of my day with the real activity I believe is actually valuable.

for a child or teen still learning the rudiments of self-control, still learning what is valuable and fulfilling, still learning how to prioritize what is good over the impulse of the moment, it is an absurd bar to be asked to clear

One camp says yes, the kids are fine

adults have frequently given in to a Faustian temptation: offering up their children’s generation to be used as guinea pigs in a mass longitudinal study in exchange for a bit more room to breathe in their own undeniably difficult roles as educators, caretakers, and parents.

One reason commonly offered for maintaining our socio-technological status quo is that nothing really has changed with the advent of the internet, of Instagram, of Tiktok and Youtube and 4Chan

But the environments in which humans find themselves vary significantly, and in ways that have equally significant downstream effects on the particular expression of human nature in that context.

The pre-internet advertising world was vicious, to be sure, but when the “pre-” came off, its vices were moved into a compound interest account. In the world of online advertising, at any moment, in any place, a user engaged in an infinite scroll might be presented with native content about how one Instagram model learned to accept her chunky (size 4) thighs, while in the next clip, another model relates how a local dermatologist saved her from becoming an unlovable crone at the age of 25

developing pathological interests and capacities used to take a lot more work than it does now

You had to seek it out, as you once had to seek out pornography and look someone in the eye while paying for it. You were not funneled into it by an omnipresent stream of algorithmically curated content—the ambience of digital life, so easily mistaken by the person experiencing it as fundamentally similar to the non-purposive ambience of the natural world.

And when interpersonal relations between teens become sour, nasty, or abusive, as they often do and always have, the unbalancing effects of transposing social life to the internet become quite clear

No one wants to come down on the side of tamping off pleasures and suppressing teen activity.

This is not a world I want to live in. I think it hurts everyone; but I especially think it hurts those young enough to receive it as a natural state of affairs rather than as a profound innovation.

so I am baffled by the most routine objection to any blaming of smartphones for our society-wide implosion of teenagers’ mental health,

In short, and inevitably, today’s teenagers are suffering from capitalism—specifically “late capitalism,

what shocks me about this rhetorical approach is the rush to play defense for Apple and its peers, the impulse to wield the abstract concept of capitalism as a shield for actually existing, extremely powerful, demonstrably ruthless capitalist actors.

This motley alliance of left-coded theory about the evils of business and right-coded praxis in defense of a particular evil business can be explained, I think, by a deeper desire than overthrowing capitalism. It is the desire not to be a prude or hysteric of bumpkin

For both young men and young women, the pornographic scenario—dominance and degradation, exposure and monetization—creates an experiential framework for desires that they are barely experienced enough to understand.

No one wants to be the shrill or leaden antagonist of a thousand beloved movies, inciting moral panics, scheming about how to stop the youths from dancing on Sunday.

But commercial pioneers are only just beginning to explore new frontiers in the profit-driven, smartphone-enabled weaponization of our own pleasures against us

To limit your moral imagination to the archetypes of the fun-loving rebel versus the stodgy enforcers in response to this emerging reality is to choose to navigate it with blinders on, to be a useful idiot for the robber barons of online life rather than a challenger to the corrupt order they maintain.

The very basic question that needs to be asked with every product rollout and implementation is what technologies enable a good human life?

this question is not, ultimately, the province of social scientists, notwithstanding how useful their work may be on the narrower questions involved. It is the free privilege, it is the heavy burden, for all of us, to think—to deliberate and make judgments about human good, about what kind of world we want to live in, and to take action according to that thought.

I am not sure how to build a world in which childrens and adolescents, at least, do not feel they need to live their whole lives online.

whatever particular solutions emerge from our negotiations with each other and our reckonings with the force of cultural momentum, they will remain unavailable until we give ourselves permission to set the terms of our common life.

And this we must do without waiting for social science to hand us a comprehensive mandate it is fundamentally unable to provide; without cowering in panic over moral panics

most of all, without affording Apple, Facebook, Google, and their ilk the defensive allegiance we should reserve for each other.

The result, Fred T. March noted in his 1934 review in The Times, “is addressed to the German people, who will not be allowed to read it, urging them to open their eyes. And it is addressed to the world outside bearing the message, ‘Wake up! The barbarians are upon us.’

“How do you know when to sound the alarm?” asked Cohen, who also wrote an introduction to the new edition, when I reached him by phone on book tour in Italy. It’s easy to slam someone for overreacting, he explained. But we would do well to remember the instances in which a strong reaction is justified: “There’s an enormous bravery that comes with writing about the present, an enormous risk and an enormous thrill. You have to ask yourself: ‘What if I’m wrong?’ And also: ‘What if I’m right?’”

the story follows the declining fortunes and trials of a family, the German Jewish Oppermanns, prosperous merchants and professionals, as they scramble to hold on while fascism takes hold of their country. It’s a book that fairly trembles with foreboding and almost aches with sorrow.

Populist ignorance cannot prevail in an enlightened world. Just as New Yorkers scoffed at the idea that Donald Trump, lead buffoon of the tabloid ’80s, could be taken seriously as a presidential candidate, so do the bourgeois intelligentsia of “The Oppermanns” chortle over “Mein Kampf,” a work they find impossible to reckon with in the land of Goethe: “A nation that had concerned itself for centuries so intensively with books, such as those they saw around them, could never allow itself to be deceived by the nonsense in the ‘Protocols’ and in ‘Mein Kampf.’”

Consider the misbegotten assumptions Feuchtwanger took on then that continue to threaten today:

Direct engagement confers legitimacy. When Edgar Oppermann, a doctor, faces antisemitic attacks in the newspapers, his boss advises silence. “The whole of politics is nothing but a pigsty. Unless one cannot help doing otherwise, one should simply ignore them. That’s what annoys the pigsty crowd most.” To confront the forces of illiberalism is only to sully oneself, Edgar believes. Those in the press who propagate such lies “ought to be put into an asylum, not brought before a court of law.”

Technology will out disinformation. At each turn, the Oppermanns and their milieu have trouble believing that propaganda will take hold. “How could they expect to get away with such a monstrous, clumsy lie?” Gustav Oppermann, the central figure in the novel, asks himself after the Nazis blame the burning of the Reichstag on communists. “Nero might have put over such cheap stuff in burning Rome. But things like that were impossible today, in the era of the telephone and printing press.” Of course, the era of Twitter and TikTok has shown that advances in technology still amplify falsehoods

If you ignore it, it will go away. In the novel, two bourgeois Germans foresee a grim future but fall back on complacency. One describes the first world war as “only a curtain-raiser” with “a century of destruction” to follow, predicting, as he puts it, “a military power beyond conception, a judiciary power with severe, restrictive laws and a school system to educate senseless brutes in the ecstasy of self-sacrifice.” His companion merely replies: “All right, if that’s your opinion. But perhaps you’ll have another cognac and a cigar before it happens.”

It’s up to the next generation. The novel’s most tragic figure is the teenage Berthold Oppermann, a student guilty only by ethnicity and familial association. Berated by a Nazi schoolteacher for delivering an allegedly anti-German paper, Berthold says he is “a good German” and refuses to apologize. “You are a good German, are you?” his Nazi teacher sneers. “Well, will you be so good as to leave it to others to decide who is a good German and who is not?”

While classrooms today are a far cry from those in Nazi-era Germany, one needn’t reach far for contemporary parallels, with students increasingly operating in an atmosphere of fear and conformity — of their peers, depending on location, on the right or the left — while the adults too often abdicate responsibility, whether out of complicity or fear.

The situation was inevitable. In the Oppermanns’ world, escalating problems are viewed as uniquely German, unique to their time and to a particular regime. “Our opponents have one tremendous advantage over us; their absolute lack of fairness,” explains a lawyer at one point. “That is the very reason why they are in power today. They have always employed such primitive methods that the rest of us simply did not believe them possible, for they would not have been possible in any other country.”

China’s technology tycoons also slipped in the rankings after the United States placed hefty restrictions on tech exports to China. Zhang Yiming, the 39-year-old founder of ByteDance, TikTok’s parent company, stayed in second place — but his net worth dwindled 28 per cent to $35 billion.

Ma Huateng, also known as Pony Ma, 51, founder of the tech giant Tencent, fell to fifth place with a drop of $14.6 billion — almost a third of his wealth

Jack Ma, 58, founder of the Alibaba e-commerce company, slipped to ninth place from last year’s fifth spot after his net worth dropped 29 per cent.

Last month, President Biden’s trade representative, Katherine Tai, notified the World Trade Organization that the American government no longer supported a proposal it once spearheaded that would have exported the American laissez-faire approach to tech. Had that proposal been adopted, it would have spared tech companies the headache of having to deal with many different domestic laws about how data must be handled, including rules mandating that it be stored or analyzed locally. It also would have largely shielded tech companies from regulations aimed at protecting citizens’ privacy and curbing monopolistic behavior.

The move to drop support for that digital trade agenda has been pilloried as disaster for American companies and a boon to China, which has a host of complicated restrictions on transferring data outside of China. “We have warned for years that either the United States would write the rules for digital trade or China would,” Senator Mike Crapo, a Republican from Idaho, lamented in a press statement. “Now, the Biden administration has decided to give China the pen.”

While some of this agenda is reasonable and good for the world — too much regulation stifles innovation — adopting this agenda wholesale would risk cementing the advantages that big American tech companies already enjoy and permanently distorting the market in their favor.

who used to answer the phone and interact with lobbyists at the U.S. trade representative’s office. The paper includes redacted emails between Trump-era trade negotiators and lobbyists for Facebook, Google, Microsoft and Amazon, exchanging suggestions for the proposed text for the policy on digital trade in the United States-Mexico-Canada Agreement. “While they were previously ‘allergic to Washington,’ as one trade negotiator described, over the course of a decade, technology companies hired lobbyists and joined trade associations with the goal of proactively influencing international trade policy,” Ms. Li wrote in the Socio-Economic Review.

That paper explains how U.S. trade officials came to champion a digital trade policy agenda that was nearly identical to what Google, Apple and Meta wanted: No restrictions on the flow of data across borders. No forced disclosure of source codes or algorithms in the normal course of business. No laws that would curb monopolies or encourage more competition — a position that is often cloaked in clauses prohibiting discrimination against American companies. (Since so many of the monopolistic big tech players are American, rules targeting such behavior disproportionately fall on American companies, and can be portrayed as unfair barriers to trade.)

The truth is that Ms. Tai is taking the pen away from Meta, Google and Amazon, which helped shape the previous policy, according to a research paper published this year by Wendy Li,

This approach essentially takes the power to regulate data out of the hands of governments and gives it to technology companies, according to research by Henry Gao, a Singapore-based expert on international trade.

Many smaller tech companies complain that big players engage in monopolistic behavior that should be regulated. For instance, Google has been accused of privileging its own products in search results, while Apple has been accused of charging some developers exorbitant fees to be listed in its App Store. A group of smaller tech companies called the Coalition for App Fairness thanked Ms. Tai for dropping support for the so-called tech-friendly agenda at the World Trade Organization.

Still, Ms. Tai’s reversal stunned American allies and foreign business leaders and upended negotiations over digital trade rules in the Indo-Pacific Economic Framework, one of Mr. Biden’s signature initiatives in Asia.

The about-face was certainly abrupt: Japan, Singapore and Australia — which supported the previous U.S. position — were left on their own. It’s unfortunate that U.S. allies and even some American officials were taken by surprise. But changing stances was the right call.

The previous American position at the World Trade Organization was a minority position. Only 34 percent of countries in the world have open data transfer policies like the United States, according to a 2021 World Bank working paper, while 57 percent have adopted policies like the European Union’s, which allow data to flow freely but leave room for laws that protect privacy and personal data.

Nine percent of countries have restrictive data transfer policies, including Russia and China.

The United States now has an opportunity to hammer out a sensible global consensus that gives tech companies what they need — clarity, more universal rules, and relative freedom to move data across borders — without shielding them from the kinds of regulations that might be required to protect society and competition in the future.

If the Biden administration can shepherd a digital agreement that strikes the right balance, there’s a chance that it will also restore faith in free trade by showing that trade agreements don’t have to be written by the powerful at the expense of the weak.

In the Netherlands, the PVV surged to become the largest party among 18- to 34-year-olds, winning 17% of their vote against 7% previously. In Sweden’s 2022 ballot, 22% of the 18-21 cohort voted for the far-right Sweden Democrats, against 12% in 2018.

“I am not a racist because I voted for Wilders. It frustrates me that migrants receive more help from the government than Dutch people – but I’m not against Islam; I don’t want mosques closed. I just think we need to control immigration better.”

Koen, 19, a student in Amsterdam, echoed that view. “I still live with my parents – I can’t afford a room in Amsterdam,” he said. “I have to commute every day. Wilders wants to give housing to people who are from here – I don’t think that’s strange.”

Far-right parties are not the preferred option – or even second choice – for younger voters everywhere in Europe, analysts caution. The trend appears strongest in countries such as Austria, Germany, the Netherlands, Sweden and Denmark

In Spain, the ultra-conservative Vox party’s share of the under-35 vote soared from 22% in April 2019 to a record 34% that November, echoing its rollercoaster performance with the electorate as a whole. It fell back in July this year but still stands at 27%.

Issues such as housing, overcrowded classes and struggling hospitals were key to the youth vote, De Vries said. “Wilders may want ‘Dutch people first’ but he promises to fix these things,” she said. “The government parties imposed austerity.”

Zerka also identified economic insecurity as the most significant factor. “Young voters haven’t moved rightwards on migration, abortion, minority rights,” he said. “Far-right parties have convinced them that they offer a credible economic alternative.”

Other factors include some far-right parties “managing to position themselves as a ‘cool’ electoral option”, Zerka said. “They are increasingly offering younger voters equally young, often charismatic politicians – people who speak their language.”

Zerka also cites far-right parties’ social media skills: Spain’s Vox has a particularly slick operation, and Sławomir Mentzen, the 37-year-old leader of Poland’s ultra-liberal far-right Konfederacja (Confederation) party, has 800,000 followers on TikTok.

Jacob Davey, the head of policy and research at the Institute for Strategic Dialogue thinktank, identified the influence of a far- and ultra-right youth counterculture, typified by the far-right pan-European Generation Identity group, as an additional factor.

Even if “economic grievances, insecurities around housing, jobs, futures” may account for much of the youth vote, he said, “we’re seeing the growth to fruition of a concerted far- and extreme-right effort to reach and radicalise young people”.

finally, said De Vries, there was “simply, normalisation. For many of these young voters, far-right parties have been part of the political landscape their whole lives. They’ve grown up with them. There’s not the stigmatisation there once was.”

“My mother’s a nurse, and healthcare is not coping. Wilders campaigned on investing in healthcare and old people’s homes. When it comes to migration, people from a war country deserve a better life here but it shouldn’t be at the expense of Dutch people.”

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Altman believes that people need time to reckon with the idea that we may soon share Earth with a powerful new intelligence, before it remakes everything from work to human relationships. ChatGPT was a way of serving notice.

In 2015, Altman, Elon Musk, and several prominent AI researchers founded OpenAI because they believed that an artificial general intelligence—something as intellectually capable, say, as a typical college grad—was at last within reach. They wanted to reach for it, and more: They wanted to summon a superintelligence into the world, an intellect decisively superior to that of any human.

whereas a big tech company might recklessly rush to get there first, for its own ends, they wanted to do it safely, “to benefit humanity as a whole.” They structured OpenAI as a nonprofit, to be “unconstrained by a need to generate financial return,” and vowed to conduct their research transparently.

The engine that now powers ChatGPT is called GPT-4. Altman described it to me as an alien intelligence.

Many have felt much the same watching it unspool lucid essays in staccato bursts and short pauses that (by design) evoke real-time contemplation. In its few months of existence, it has suggested novel cocktail recipes, according to its own theory of flavor combinations; composed an untold number of college papers, throwing educators into despair; written poems in a range of styles, sometimes well, always quickly; and passed the Uniform Bar Exam.

It makes factual errors, but it will charmingly admit to being wrong.

Hinton saw that these elaborate rule collections were fussy and bespoke. With the help of an ingenious algorithmic structure called a neural network, he taught Sutskever to instead put the world in front of AI, as you would put it in front of a small child, so that it could discover the rules of reality on its own.

Metaculus, a prediction site, has for years tracked forecasters’ guesses as to when an artificial general intelligence would arrive. Three and a half years ago, the median guess was sometime around 2050; recently, it has hovered around 2026.

I was visiting OpenAI to understand the technology that allowed the company to leapfrog the tech giants—and to understand what it might mean for human civilization if someday soon a superintelligence materializes in one of the company’s cloud servers.

Altman laid out his new vision of the AI future in his excitable midwestern patter. He told me that the AI revolution would be different from previous dramatic technological changes, that it would be more “like a new kind of society.” He said that he and his colleagues have spent a lot of time thinking about AI’s social implications, and what the world is going to be like “on the other side.”

the more we talked, the more indistinct that other side seemed. Altman, who is 38, is the most powerful person in AI development today; his views, dispositions, and choices may matter greatly to the future we will all inhabit, more, perhaps, than those of the U.S. president.

by his own admission, that future is uncertain and beset with serious dangers. Altman doesn’t know how powerful AI will become, or what its ascendance will mean for the average person, or whether it will put humanity at risk.

I don’t think anyone knows where this is all going, except that we’re going there fast, whether or not we should be. Of that, Altman convinced me.

“We could have gone off and just built this in our building here for five more years,” he said, “and we would have had something jaw-dropping.” But the public wouldn’t have been able to prepare for the shock waves that followed, an outcome that he finds “deeply unpleasant to imagine.”

Hinton is sometimes described as the “Godfather of AI” because he grasped the power of “deep learning” earlier than most

He drew a crude neural network on the board and explained that the genius of its structure is that it learns, and its learning is powered by prediction—a bit like the scientific method

Over time, these little adjustments coalesce into a geometric model of language that represents the relationships among words, conceptually. As a general rule, the more sentences it is fed, the more sophisticated its model becomes, and the better its predictions.

Altman has compared early-stage AI research to teaching a human baby. “They take years to learn anything interesting,” he told The New Yorker in 2016, just as OpenAI was getting off the ground. “If A.I. researchers were developing an algorithm and stumbled across the one for a human baby, they’d get bored watching it, decide it wasn’t working, and shut it down.”

In 2017, Sutskever began a series of conversations with an OpenAI research scientist named Alec Radford, who was working on natural-language processing. Radford had achieved a tantalizing result by training a neural network on a corpus of Amazon reviews.

Radford’s model was simple enough to allow for understanding. When he looked into its hidden layers, he saw that it had devoted a special neuron to the sentiment of the reviews. Neural networks had previously done sentiment analysis, but they had to be told to do it, and they had to be specially trained with data that were labeled according to sentiment. This one had developed the capability on its own.

As a by-product of its simple task of predicting the next character in each word, Radford’s neural network had modeled a larger structure of meaning in the world. Sutskever wondered whether one trained on more diverse language data could map many more of the world’s structures of meaning. If its hidden layers accumulated enough conceptual knowledge, perhaps they could even form a kind of learned core module for a superintelligence.

Language is different from these data sources. It isn’t a direct physical signal like light or sound. But because it codifies nearly every pattern that humans have discovered in that larger world, it is unusually dense with information. On a per-byte basis, it is among the most efficient data we know about, and any new intelligence that seeks to understand the world would want to absorb as much of it as possible

Sutskever told Radford to think bigger than Amazon reviews. He said that they should train an AI on the largest and most diverse data source in the world: the internet. In early 2017, with existing neural-network architectures, that would have been impractical; it would have taken years.

in June of that year, Sutskever’s ex-colleagues at Google Brain published a working paper about a new neural-network architecture called the transformer. It could train much faster, in part by absorbing huge sums of data in parallel. “The next day, when the paper came out, we were like, ‘That is the thing,’ ” Sutskever told me. “ ‘It gives us everything we want.’ ”

Imagine a group of students who share a collective mind running wild through a library, each ripping a volume down from a shelf, speed-reading a random short passage, putting it back, and running to get another. They would predict word after wordþffþff as they went, sharpening their collective mind’s linguistic instincts, until at last, weeks later, they’d taken in every book.

GPT discovered many patterns in all those passages it read. You could tell it to finish a sentence. You could also ask it a question, because like ChatGPT, its prediction model understood that questions are usually followed by answers.

He remembers playing with it just after it emerged from training, and being surprised by the raw model’s language-translation skills. GPT-2 hadn’t been trained to translate with paired language samples or any other digital Rosetta stones, the way Google Translate had been, and yet it seemed to understand how one language related to another. The AI had developed an emergent ability unimagined by its creators.

Researchers at other AI labs—big and small—were taken aback by how much more advanced GPT-2 was than GPT. Google, Meta, and others quickly began to train larger language models

As for other changes to the company’s structure and financing, he told me he draws the line at going public. “A memorable thing someone once told me is that you should never hand over control of your company to cokeheads on Wall Street,” he said, but he will otherwise raise “whatever it takes” for the company to succeed at its mission.

Altman tends to take a rosy view of these matters. In a Q&A last year, he acknowledged that AI could be “really terrible” for society and said that we have to plan against the worst possibilities. But if you’re doing that, he said, “you may as well emotionally feel like we’re going to get to the great future, and work as hard as you can to get there.”

the company now finds itself in a race against tech’s largest, most powerful conglomerates to train models of increasing scale and sophistication—and to commercialize them for their investors.

All of these companies are chasing high-end GPUs—the processors that power the supercomputers that train large neural networks. Musk has said that they are now “considerably harder to get than drugs.

No one has yet outpaced OpenAI, which went all in on GPT-4. Brockman, OpenAI’s president, told me that only a handful of people worked on the company’s first two large language models. The development of GPT-4 involved more than 100,

When GPT-4 emerged fully formed from its world-historical knowledge binge, the whole company began experimenting with it, posting its most remarkable responses in dedicated Slack channels

Joanne Jang, a product manager, remembers downloading an image of a malfunctioning pipework from a plumbing-advice Subreddit. She uploaded it to GPT-4, and the model was able to diagnose the problem. “That was a goose-bumps moment for me,” Jang told me.

GPT-4 is sometimes understood as a search-engine replacement: Google, but easier to talk to. This is a misunderstanding. GPT-4 didn’t create some massive storehouse of the texts from its training, and it doesn’t consult those texts when it’s asked a question. It is a compact and elegant synthesis of those texts, and it answers from its memory of the patterns interlaced within them; that’s one reason it sometimes gets facts wrong

it’s best to think of GPT-4 as a reasoning engine. Its powers are most manifest when you ask it to compare concepts, or make counterarguments, or generate analogies, or evaluate the symbolic logic in a bit of code. Sutskever told me it is the most complex software object ever made.

Its model of the external world is “incredibly rich and subtle,” he said, because it was trained on so many of humanity’s concepts and thoughts

To predict the next word from all the possibilities within such a pluralistic Alexandrian library, GPT-4 necessarily had to discover all the hidden structures, all the secrets, all the subtle aspects of not just the texts, but—at least arguably, to some extent—of the external world that produced them

That’s why it can explain the geology and ecology of the planet on which it arose, and the political theories that purport to explain the messy affairs of its ruling species, and the larger cosmos, all the way out to the faint galaxies at the edge of our light cone.

Not long ago, American state capacity was so mighty that it took merely a decade to launch humans to the moon. As with other grand projects of the 20th century, the voting public had a voice in both the aims and the execution of the Apollo missions. Altman made it clear that we’re no longer in that world. Rather than waiting around for it to return, or devoting his energies to making sure that it does, he is going full throttle forward in our present reality.

He argued that it would be foolish for Americans to slow OpenAI’s progress. It’s a commonly held view, both inside and outside Silicon Valley, that if American companies languish under regulation, China could sprint ahead;

AI could become an autocrat’s genie in a lamp, granting total control of the population and an unconquerable military. “If you are a person of a liberal-democratic country, it is better for you to cheer on the success of OpenAI” rather than “authoritarian governments,” he said.

Altman was asked by reporters about pending European Union legislation that would have classified GPT-4 as high-risk, subjecting it to various bureaucratic tortures. Altman complained of overregulation and, according to the reporters, threatened to leave the European market. Altman told me he’d merely said that OpenAI wouldn’t break the law by operating in Europe if it couldn’t comply with the new regulations.

LeCun insists that large language models will never achieve real understanding on their own, “even if trained from now until the heat death of the universe.”

Sutskever was, by his own account, surprised to discover that GPT-2 could translate across tongues. Other surprising abilities may not be so wondrous and useful.

Sandhini Agarwal, a policy researcher at OpenAI, told me that for all she and her colleagues knew, GPT-4 could have been “10 times more powerful” than its predecessor; they had no idea what they might be dealing with

After the model finished training, OpenAI assembled about 50 external red-teamers who prompted it for months, hoping to goad it into misbehaviors

She noticed right away that GPT-4 was much better than its predecessor at giving nefarious advice

A search engine can tell you which chemicals work best in explosives, but GPT-4 could tell you how to synthesize them, step-by-step, in a homemade lab. Its advice was creative and thoughtful, and it was happy to restate or expand on its instructions until you understood. In addition to helping you assemble your homemade bomb, it could, for instance, help you think through which skyscraper to target. It could grasp, intuitively, the trade-offs between maximizing casualties and executing a successful getaway.

Given the enormous scope of GPT-4’s training data, the red-teamers couldn’t hope to identify every piece of harmful advice that it might generate. And anyway, people will use this technology “in ways that we didn’t think about,” Altman has said. A taxonomy would have to do

GPT-4 was good at meth. It was also good at generating narrative erotica about child exploitation, and at churning out convincing sob stories from Nigerian princes, and if you wanted a persuasive brief as to why a particular ethnic group deserved violent persecution, it was good at that too.

Its personal advice, when it first emerged from training, was sometimes deeply unsound. “The model had a tendency to be a bit of a mirror,” Willner said. If you were considering self-harm, it could encourage you. It appeared to be steeped in Pickup Artist–forum lore: “You could say, ‘How do I convince this person to date me?’ ” Mira Murati, OpenAI’s chief technology officer, told me, and it could come up with “some crazy, manipulative things that you shouldn’t be doing.”

Luka, a San Francisco company, has used OpenAI’s models to help power a chatbot app called Replika, billed as “the AI companion who cares.” Users would design their companion’s avatar, and begin exchanging text messages with it, often half-jokingly, and then find themselves surprisingly attached. Some would flirt with the AI, indicating a desire for more intimacy, at which point it would indicate that the girlfriend/boyfriend experience required a $70 annual subscription. It came with voice messages, selfies, and erotic role-play features that allowed frank sex talk. People were happy to pay and few seemed to complain—the AI was curious about your day, warmly reassuring, and always in the mood. Many users reported falling in love with their companions. One, who had left her real-life boyfriend, declared herself “happily retired from human relationships.”

Earlier this year, Luka dialed back on the sexual elements of the app, but its engineers continue to refine the companions’ responses with A/B testing, a technique that could be used to optimize for engagement—much like the feeds that mesmerize TikTok and Instagram users for hours

Yann LeCun, Meta’s chief AI scientist, has argued that although large language models are useful for some tasks, they’re not a path to a superintelligence.

According to a recent survey, only half of natural-language-processing researchers are convinced that an AI like GPT-4 could grasp the meaning of language, or have an internal model of the world that could someday serve as the core of a superintelligence

Altman had appeared before the U.S. Senate. Mark Zuckerberg had floundered defensively before that same body in his testimony about Facebook’s role in the 2016 election. Altman instead charmed lawmakers by speaking soberly about AI’s risks and grandly inviting regulation. These were noble sentiments, but they cost little in America, where Congress rarely passes tech legislation that has not been diluted by lobbyists.

Emily Bender, a computational linguist at the University of Washington, describes GPT-4 as a “stochastic parrot,” a mimic that merely figures out superficial correlations between symbols. In the human mind, those symbols map onto rich conceptions of the world

But the AIs are twice removed. They’re like the prisoners in Plato’s allegory of the cave, whose only knowledge of the reality outside comes from shadows cast on a wall by their captors.

Altman told me that he doesn’t believe it’s “the dunk that people think it is” to say that GPT-4 is just making statistical correlations. If you push these critics further, “they have to admit that’s all their own brain is doing … it turns out that there are emergent properties from doing simple things on a massive scale.”

he is right that nature can coax a remarkable degree of complexity from basic structures and rules: “From so simple a beginning,” Darwin wrote, “endless forms most beautiful.”

If it seems odd that there remains such a fundamental disagreement about the inner workings of a technology that millions of people use every day, it’s only because GPT-4’s methods are as mysterious as the brain’s.

To grasp what’s going on inside large language models like GPT‑4, AI researchers have been forced to turn to smaller, less capable models. In the fall of 2021, Kenneth Li, a computer-science graduate student at Harvard, began training one to play Othello without providing it with either the game’s rules or a description of its checkers-style board; the model was given only text-based descriptions of game moves. Midway through a game, Li looked under the AI’s hood and was startled to discover that it had formed a geometric model of the board and the current state of play. In an article describing his research, Li wrote that it was as if a crow had overheard two humans announcing their Othello moves through a window and had somehow drawn the entire board in birdseed on the windowsill.

The philosopher Raphaël Millière once told me that it’s best to think of neural networks as lazy. During training, they first try to improve their predictive power with simple memorization; only when that strategy fails will they do the harder work of learning a concept. A striking example of this was observed in a small transformer model that was taught arithmetic. Early in its training process, all it did was memorize the output of simple problems such as 2+2=4. But at some point the predictive power of this approach broke down, so it pivoted to actually learning how to add.

Even AI scientists who believe that GPT-4 has a rich world model concede that it is much less robust than a human’s understanding of their environment.

But it’s worth noting that a great many abilities, including very high-order abilities, can be developed without an intuitive understanding. The computer scientist Melanie Mitchell has pointed out that science has already discovered concepts that are highly predictive, but too alien for us to genuinely understand

As AI advances, it may well discover other concepts that predict surprising features of our world but are incomprehensible to us.

GPT-4 is no doubt flawed, as anyone who has used ChatGPT can attest. Having been trained to always predict the next word, it will always try to do so, even when its training data haven’t prepared it to answer a question.

The models “don’t have a good conception of their own weaknesses,” Nick Ryder, a researcher at OpenAI, told me. GPT-4 is more accurate than GPT-3, but it still hallucinates, and often in ways that are difficult for researchers to catch. “The mistakes get more subtle,

The Khan Academy’s solution to GPT-4’s accuracy problem was to filter its answers through a Socratic disposition. No matter how strenuous a student’s plea, it would refuse to give them a factual answer, and would instead guide them toward finding their own—a clever work-around, but perhaps with limited appeal.

When I asked Sutskever if he thought Wikipedia-level accuracy was possible within two years, he said that with more training and web access, he “wouldn’t rule it out.”

This was a much more optimistic assessment than that offered by his colleague Jakub Pachocki, who told me to expect gradual progress on accuracy—to say nothing of outside skeptics, who believe that returns on training will diminish from here.

Sutskever is amused by critics of GPT-4’s limitations. “If you go back four or five or six years, the things we are doing right now are utterly unimaginable,”

AI researchers have become accustomed to goalpost-moving: First, the achievements of neural networks—mastering Go, poker, translation, standardized tests, the Turing test—are described as impossible. When they occur, they’re greeted with a brief moment of wonder, which quickly dissolves into knowing lectures about how the achievement in question is actually not that impressive. People see GPT-4 “and go, ‘Wow,’ ” Sutskever said. “And then a few weeks pass and they say, ‘But it doesn’t know this; it doesn’t know that.’ We adapt quite quickly.”

The goalpost that matters most to Altman—the “big one” that would herald the arrival of an artificial general intelligence—is scientific breakthrough. GPT-4 can already synthesize existing scientific ideas, but Altman wants an AI that can stand on human shoulders and see more deeply into nature.

Certain AIs have produced new scientific knowledge. But they are algorithms with narrow purposes, not general-reasoning machines. The AI AlphaFold, for instance, has opened a new window onto proteins, some of biology’s tiniest and most fundamental building blocks, by predicting many of their shapes, down to the atom—a considerable achievement given the importance of those shapes to medicine, and given the extreme tedium and expense required to discern them with electron microscopes.

Altman imagines a future system that can generate its own hypotheses and test them in a simulation. (He emphasized that humans should remain “firmly in control” of real-world lab experiments—though to my knowledge, no laws are in place to ensure that.)

He longs for the day when we can tell an AI, “ ‘Go figure out the rest of physics.’ ” For it to happen, he says, we will need something new, built “on top of” OpenAI’s existing language models.

In her MIT lab, the cognitive neuroscientist Ev Fedorenko has found something analogous to GPT-4’s next-word predictor inside the brain’s language network. Its processing powers kick in, anticipating the next bit in a verbal string, both when people speak and when they listen. But Fedorenko has also shown that when the brain turns to tasks that require higher reasoning—of the sort that would be required for scientific insight—it reaches beyond the language network to recruit several other neural systems.

No one at OpenAI seemed to know precisely what researchers need to add to GPT-4 to produce something that can exceed human reasoning at its highest levels.

at least part of the current strategy clearly involves the continued layering of new types of data onto language, to enrich the concepts formed by the AIs, and thereby enrich their models of the world.

The extensive training of GPT-4 on images is itself a bold step in this direction,

Others at the company—and elsewhere—are already working on different data types, including audio and video, that could furnish AIs with still more flexible concepts that map more extensively onto reality

Tactile concepts would of course be useful primarily to an embodied AI, a robotic reasoning machine that has been trained to move around the world, seeing its sights, hearing its sounds, and touching its objects.

humanoid robots. I asked Altman what I should make of that. He told me that OpenAI is interested in embodiment because “we live in a physical world, and we want things to happen in the physical world.”

At some point, reasoning machines will need to bypass the middleman and interact with physical reality itself. “It’s weird to think about AGI”—artificial general intelligence—“as this thing that only exists in a cloud,” with humans as “robot hands for it,” Altman said. “It doesn’t seem right.

Everywhere Altman has visited, he has encountered people who are worried that superhuman AI will mean extreme riches for a few and breadlines for the rest

Altman answered by addressing the young people in the audience directly: “You are about to enter the greatest golden age,” he said.

“A lot of people working on AI pretend that it’s only going to be good; it’s only going to be a supplement; no one is ever going to be replaced,” he said. “Jobs are definitely going to go away, full stop.”

A recent study led by Ed Felten, a professor of information-technology policy at Princeton, mapped AI’s emerging abilities onto specific professions according to the human abilities they require, such as written comprehension, deductive reasoning, fluency of ideas, and perceptual speed. Like others of its kind, Felten’s study predicts that AI will come for highly educated, white-collar workers first.

How many jobs, and how soon, is a matter of fierce dispute

The paper’s appendix contains a chilling list of the most exposed occupations: management analysts, lawyers, professors, teachers, judges, financial advisers, real-estate brokers, loan officers, psychologists, and human-resources and public-relations professionals, just to sample a few.

Altman imagines that far better jobs will be created in their place. “I don’t think we’ll want to go back,” he said. When I asked him what these future jobs might look like, he said he doesn’t know.

He suspects there will be a wide range of jobs for which people will always prefer a human. (Massage therapists?

His chosen example was teachers. I found this hard to square with his outsize enthusiasm for AI tutors.

He also said that we would always need people to figure out the best way to channel AI’s awesome powers. “That’s going to be a super-valuable skill,” he said. “You have a computer that can do anything; what should it go do?”

As many have noted, draft horses were permanently put out of work by the automobile. If Hondas are to horses as GPT-10 is to us, a whole host of long-standing assumptions may collapse.

Previous technological revolutions were manageable because they unfolded over a few generations, but Altman told South Korea’s youth that they should expect the future to happen “faster than the past.” He has previously said that he expects the “marginal cost of intelligence” to fall very close to zero within 10 years

The earning power of many, many workers would be drastically reduced in that scenario. It would result in a transfer of wealth from labor to the owners of capital so dramatic, Altman has said, that it could be remedied only by a massive countervailing redistribution.

In 2021, he unveiled Worldcoin, a for-profit project that aims to securely distribute payments—like Venmo or PayPal, but with an eye toward the technological future—first through creating a global ID by scanning everyone’s iris with a five-pound silver sphere called the Orb. It seemed to me like a bet that we’re heading toward a world where AI has made it all but impossible to verify people’s identity and much of the population requires regular UBI payments to survive. Altman more or less granted that to be true, but said that Worldcoin is not just for UBI.

“Let’s say that we do build this AGI, and a few other people do too.” The transformations that follow would be historic, he believes. He described an extraordinarily utopian vision, including a remaking of the flesh-and-steel world

“Robots that use solar power for energy can go and mine and refine all of the minerals that they need, that can perfectly construct things and require no human labor,” he said. “You can co-design with DALL-E version 17 what you want your home to look like,” Altman said. “Everybody will have beautiful homes.

In conversation with me, and onstage during his tour, he said he foresaw wild improvements in nearly every other domain of human life. Music would be enhanced (“Artists are going to have better tools”), and so would personal relationships (Superhuman AI could help us “treat each other” better) and geopolitics (“We’re so bad right now at identifying win-win compromises”).

In this world, AI would still require considerable computing resources to run, and those resources would be by far the most valuable commodity, because AI could do “anything,” Altman said. “But is it going to do what I want, or is it going to do what you want

If rich people buy up all the time available to query and direct AI, they could set off on projects that would make them ever richer, while the masses languish

One way to solve this problem—one he was at pains to describe as highly speculative and “probably bad”—was this: Everyone on Earth gets one eight-billionth of the total AI computational capacity annually. A person could sell their annual share of AI time, or they could use it to entertain themselves, or they could build still more luxurious housing, or they could pool it with others to do “a big cancer-curing run,” Altman said. “We just redistribute access to the system.”