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"I remember the first time (Kasparov) was in jail, he didn't eat a thing because he was afraid that they'd poison him. And we all laughed at him! We thought he was paranoid. He is the only person I know who took any security measures."

Navalny's brilliant sting operation won't lead to an arrest and may only increase the chances he'll be targeted again with a less subtle method

Putin, who worked as a KGB officer before his political ascendance, once said himself that "there's no such thing as former KGB man." While he has always prioritized the security services during his two decades in power, the decay within Russia's intelligence agency is obvious as the country stagnates under dictatorship

But you don't have to be a master assassin when you can keep trying with impunity, even after being caught red-handed.

I don't fly with the state-owned airline Aeroflot, and I don't travel to countries where Putin might be able to put pressure on local authorities to do him a favor. But no one is untouchable in a world where criminals go unpunished.

The Kremlin has doubled down on its lies and denials, spreading a flood of contradictory stories by officials and in the state-run media. Putin himself was dismissive as usual, refusing to even mention Navalny by name when asked about the case. He denied the poisoning, saying, "If (FSB agents) wanted to, they would've probably finished it."

Even in the face of one of the worst cyberattacks in US history, Trump has refused to call out Russia as the culprit, even when his own secretary of state said, "We can say pretty clearly that it was the Russians that engaged in this activity."

Putin's henchmen are sloppy because they can afford to be. Just like their boss, they don't fear any repercussions

Meanwhile, the Trump administration is sending a clear message to all despots as it considers granting legal immunity for Saudi crown prince Mohammed bin Salman, who ordered the gruesome killing of journalist Jamal Khashoggi, according to the CIA

Yet, there is always talk about the need for more international engagement with these despots and thugs, not less. The dubious theory that globalization and closer economic ties will inevitably liberalize dictatorships has been refuted many times over. We see this with China's Xi Jinping, who has become more authoritarian and aggressive since the US welcomed China into the World Trade Organization. Instead, engagement -- or appeasement by another name -- reinforces their sense of impunity

Russia and some of Putin's oligarchs have already been under piecemeal sanctions since the 2014 invasion of Ukraine and annexation of Crimea. But these sanctions are merely a slap on the wrist, and it's clear they do not go far or high enough.

We must not ignore the threat of bad actors gaining access to these dangerous pathogens, which are the ultimate terror weapons, due to their potentially massive impact

In Germany, security services interdicted vast amounts of the toxin ricin, which, authorities said, a couple was planning to use in a biological attack in 2018

Instead of looking to weaponize a highly virulent pathogen like anthrax -- the spore-forming bacterium which was infamously mailed out to media outlets and politicians in a bio attack in 2001, killing five people and injuring 17 more -- bad actors are now likely considering the efficacy of a less virulent but highly transmissible pathogen like SARS-CoV-2, which has brought the world to its knees in the last year. This pathogen has shown that transmissibility -- rather than toxicity -- is a major factor when it comes to mass disruption.

The pandemic has also underscored the importance of manufacturing and stockpiling medical gear including personal protective equipment to avoid logjams in the supply chain and a reliance on other countries like China for these critical supplies. Providing accurate and accessible information to the public is also key; propaganda and disinformation must not be taken lightly.

However, it is poorly funded in comparison to other treaties like the Chemical Weapons Convention, and does not have a corresponding body like the Organization for the Prohibition of Chemical Weapons (OPCW) to police it.

The World Health Organization could also implement an early warning system to predict pandemics, showing its progress around the globe.

MCMs are products such as vaccines, biologics and pharmaceutical drugs that can diagnose, protect or treat the effects of a naturally occurring new disease or biological attack. In the future, it may be more cost effective to pay the pharmaceutical industry ahead of time to produce treatments and vaccines rather than wait for a pandemic to develop.

When it comes to policies that are already in place, there is the Biological and Toxic Weapons Convention (BTWC), a multilateral treaty that went into effect in 1975, which prohibits the development, production, acquisition and stockpiling of biological agents and toxins and any related delivery systems that have "no justification for prophylactic, protective or other peaceful purposes."

Going forward, we should treat biosecurity threats with the same urgency in the 21st century as world leaders approached atomic bombs in the 20th century.

A first step would be for the UN Security Council to fund and enforce the Biological and Toxic Weapons Convention.

they simply ask and networks organized online call volunteer lawyers, who drop what they are doing and proceed to the police station. When protesters need food, water or mobile phone data, they ask and food, water and money from an ever-growing fund of global donations is sent. And when they need ambulances or security guards to protect them from hired thugs, from the state itself, they ask, and private ambulance and security services are sent their way.

Don’t

SARS has come to resemble the armed thugs it supposedly combats

Hours before 9, armed soldiers began firing live rounds into the peaceful crowd of protesters, with fatal consequences.

These protests, which continue reinvigorated in other parts of the country, have become about challenging the legitimacy of a defunct political leadership

Who gave our so-called leaders the authority they think they have over us; if we are a democracy, who is really in charge?

imagine the brutality of the arms behind them.

legitimate authority finds its weight in motivating and persuading people without the need to lift a bullying finger.

“If we come together in love, they cannot destroy us.”

Both the novel and the film, which Greenlee produced with Dixon, concern an apparently docile Black C.I.A. employee with the allegorical name Dan Freeman. Recruited as a public relations gesture, Freeman plays the long game, using what he has learned at the agency to mastermind an guerrilla war in Chicago.

Racial solidarity is the movie’s subject and the project’s DNA. Not only did Greenlee raise money from Black investors and get a fellow Chicagoan, Herbie Hancock, to write the score, he was able to use Gary, Ind., one of the first large American cities to elect a Black mayor, as a stand-in location for Chicago, thus enjoying the cooperation of the municipal authorities for powerful riot scenes.

The white characters (mainly male authority figures) are fools, brutes, knaves and patronizing liars. The Black ones are also stereotyped but given greater depth. The movie suggests a live-action animated cartoon in which the whites have two dimensions and the Blacks have three.

if “Spook” is a cartoon, it’s one animated by the ideas of the radical psychiatrist and champion of decolonization Frantz Fanon.

The movie is an analog to anti-imperialist films like “The Battle of Algiers,” albeit in the guise of a blaxploitation cheapster

after three weeks in release, during which F.B.I. agents hounded exhibitors to pull the film, UA withdrew it from circulation, citing poor box office grosses.

Spook” brought in $270,000 during its abortive run.)

White America was spooked. The movie was blamed for serving as a Black Panthers textbook and for inspiring the Symbionese Liberation Army

Historically, it can be bracketed with two earlier, highly successful independent productions — “Putney Swope,” a 1969 absurdist comedy by the white director Robert Downey in which an African-American takes charges of a Madison Avenue advertising agency, and “Sweet Sweetback’s Baadasssss Song,” Melvin Van Peebles’s groundbreaking celebration of a Black outlaw,

unlike “Swope,” “Spook” is something other than hip satire and, as opposed to “Sweetback,” it did not lend itself to recuperative commercialization.

“Spook” may be a eulogy, but the most shocking thing about this unquiet movie is how relevant it remains.

This shift has been occurring for years, but it could present Trump and Republicans with a perfect storm of problems at the same time that the state has become the center of the political universe with close races for president, Senate and governor.

"We realize that we have been infiltrated by other people that have more liberal views... than we do," Cheryl Miles, a Trump supporter,

Martin County, after twice voting for President Barack Obama, narrowly backed Trump in 2016, helping him cut into margins in the bigger metropolitan areas.

Christian conservatives who were somewhat skeptical of Trump four years ago are now fully behind the Republican leader.

"He stands for Christian values," Miles said. "I know that sometimes when he talks, he doesn't talk the way I would like for him to talk. But I like the stands that he takes. And sometimes you have to look beyond what the person is saying and (to) what he is doing."

The greater area around Raleigh, including college towns like Chapel Hill and Durham, is known as the research triangle, because of the topflight universities that are crammed into a relatively small area.

Those institutions have not only attracted hundreds of thousands of more liberal voters to North Carolina, but they have provided the intellectual capital to fuel a growing technology and health care industry that has led to thousands of new jobs just over the last few years.

The couple had been on green cards for decades, unable to vote in any election. But then Trump won, and the couple said shortly thereafter they became citizens almost expressly to vote against the President.

"I'll be honest with you: I really want to vote against Trump. That was the primary thing."

just two weeks before Election Day, North Carolina remains a toss-up, according to multiple recent polls that find Biden with the narrowest of margins.

Obama, the last Democrat to win the state in 2008, carried North Carolina because of overwhelming turnout from Black and young Americans. Biden's path, while similar, has some notable differences: In order to carry North Carolina next month, Biden will lean on a coalition that is Whiter, more suburban and older than the one that delivered the state to Obama 12 years ago.

"I've got a pretty good fix that most of the ones going to the Trump rally are probably voting for me," said Kidwell, whose signs tout him as the "most conservative" member of the North Carolina General Assembly.

"He is going to (need to) boost his numbers in rural counties to make up for what looks like an even bigger defeat in Raleigh, Charlotte," said Michael Bitzer, a professor at Catawba College and an expert on the state's politics. "I am just not sure how much more he can squeeze out of those rural areas."

Trump, on the other hand, can't solely count on the same turnout from Eastern and Western North Carolina, the two areas that propelled him to victory four years ago.

He is staunchly against wearing masks to combat the coronavirus and did not wear one when greeting voters in Washington.

"It worries me more on the statewide and national elections. ... But I think we are going to do well. North Carolina is, even if our metro areas are more liberal leaning, we still have a good number of people who are conservative."

Brian Buck said it is "concerning" that liberals are "coming from up north down to North Carolina" and he feared it would eventually "change us from a toss-up state to a blue state."

"The damn Democrats don't realize that he is just the President. He is not God," Brian Buck said. "What was he supposed to do? Go into the basement and go hocus pocus and make a damn treatment for it? No. So they blame him for it, but he had no more control over it getting here than I did."

"I believe he is more for the Christians than the Democrats," said Sawyer. "And that is one of the most important things."

"In 2016, President Trump brought out a lot of voters in the Eastern part of the state that previously voted for Barack Obama, or didn't vote, because he wasn't a stereotypical Republican," said Nick Trainer, Trump's director of battleground strategy. These voters "saw Barack Obama as a change agent and saw Donald Trump as a change agent."

"I really don't trust Donald Trump," he said, wearing a Desert Storm veteran hat, US Army mask and white veteran T-shirt. "It has been awhile since there has been this kind of unrest in politics in this country. ... It is best not to discuss politics because there is always going to be some friction involved."

One of those so-called Yankees would be Bridgette Hodges, an African-American grandmother who moved to the state from New Jersey around a year ago to be closer to her family, like Sanaa, her grandchild. The duo waited for over two hours on a recent rainy Friday so Hodges could not only vote for Biden, but register as a North Carolina voter for the first time.

"There are two groups we need to be focused on and that is turning out the African American vote and also suburban women," said Meredith Cuomo, the executive director of the North Carolina Democratic Party. "We have seen just a real shift in our demographics since 2016."

Turning out voters like Hodges and Puebla was the missing piece for Clinton in 2016, whose campaign went into Election Day believing she would win the state. But turnout was down among reliable Democratic voters and up with voters in Eastern and Western reaches of the state, delivering Trump the win.

"I don't think of myself as an anomaly, I think that younger Republican voters are more progressive... and it has now become a generational thing inside the party," said Plyler, his long red beard hanging out of his mask. "So, if Republicans are scared of these kinds of voters, then they are scared of Republicans. That's the shame of it."

he began a law career in Americus, an old Confederate cotton town and the seat of Sumter County, about 140 miles south of Atlanta. Sumter has for decades played an important role in liberal Georgia’s sense of possibility. A multiracial Christian commune, Koinonia Farm, was founded there in the 1940s. Jimmy Carter lives in the tiny town of Plains, and the nonprofit Habitat for Humanity, founded by a Koinonia family, is headquartered in Americus

Before it fell away, Mr. Calhoun’s white progressivism had a homegrown flavor, steeped in Georgia’s history, countercultural currents and higher education system. He preached criminal justice reform and broadcast his support for Hillary Clinton.

Then came his abrupt turn, and a headlong descent into some of the darkest places in Georgia history. He peppered his social media posts with racial slurs, referring to Vice President Kamala Harris as a “fake negro.” He saluted the Confederacy, and he seemed to thirst for civil war.

He was not an unlettered man: In his years at school, Mr. Calhoun had written a master’s thesis on the historiography of Napoleon’s peninsular war and had attended a law seminar in Belgium. His profile — a well-educated, white-collar white man — matched that of some of the other Georgians who stormed the U.S. Capitol on Jan. 6

The crowd that came from Georgia included a 53-year-old investment portfolio manager and a 65-year-old accountant. It included Cleveland Grover Meredith Jr., 51, a successful business owner who graduated from an elite Atlanta prep school, who was arrested in Washington the day after the riot with guns, hundreds of rounds of ammunition and a phone with his text messages about “putting a bullet” into Speaker Nancy Pelosi’s head.

Black residents in Sumter make up a reliable Democratic base, while whites are often divided, as one local put it, between liberal “come heres,” like Habitat employees, and conservative, locally raised, “been heres.”

while Mr. Calhoun’s politics had changed drastically, Mr. Lankford said, his personality had not.“He’s the same old banty rooster, just on the other side of the fence,” Mr. Lankford said.

After the 2016 election, an old friend, Bob Fortin, remembers Mr. Calhoun excoriating him for voting for Mr. Trump. “He cussed me out in his kitchen,” said Mr. Fortin, who said he later regretted his vote. “He made me feel like a complete ass.”

“I was a Democrat for 30 years,” he wrote in a recent social media post. The new gun control proposals changed that, he said. “I was called a white supremacist and a racist for defending the 2A,” he continued, using a shorthand for the Second Amendment. Given all that he had done as a lawyer for “justice,” he said, “that hurt my feelings a little. That’s when I became a Trump supporter.”

His conversion was total. By the fall of 2020 he was posting about a looming “domestic communist problem” and the “rioting BLM-Antifa crime wave.” Of Joe Biden, he wrote: “Hang the bastard.”

Old friends were baffled, and some grew nervous. “I’ll be slinging enough hot lead to stack you commies up like cordwood,” Mr. Calhoun wrote on Twitter in October. Then, a few days later: “Standing by, and when Trump makes the call, millions of heavily armed, pissed off patriots are coming to Washington.”

After the election, Mr. Calhoun held a small gun rights rally in town, and the violent posts continued, with talk of civil war, mounting heads on pikes and showing the Democratic congresswoman Ilhan Omar “what the bottom of the river looks like.” In December, a reporter for The Globe and Mail, a Canadian newspaper, found Mr. Calhoun buying a Confederate flag outside a Trump rally. “This is about independence and freedom,” Mr. Calhoun told the reporter, describing Trumpism and Southern secession as similarly justified fights against tyranny.

On Jan. 6, Mr. Calhoun’s posts showed he had made his way inside the U.S. Capitol with the mob. “The first of us who got upstairs kicked in Nancy Pelosi’s office door,” he wrote in one post. “Crazy Nancy probably would have been torn into little pieces, but she was nowhere to be seen.”

A week later, federal agents arrested him at his sister’s house in Macon, Ga., where he had stockpiled two AR-15-style assault rifles, two shotguns, a handgun, brass knuckles and hundreds of rounds of ammunition, according to the testimony of an F.B.I. agent.

Rev. Wright suggested that the racism deep at the root of Georgia’s history was still very much alive, even if white people, including some of those who saw themselves as progressive, did not want to admit it. “What President Trump did was allow it to bud and to grow,” he said. “A lot of people who had been suppressing it no longer felt that they had to suppress it.”

At Mr. Calhoun’s Jan. 21 court hearing in Macon, Charles H. Weigle, the federal magistrate judge, ruled that there was probable cause to believe that Mr. Calhoun had committed crimes when he stormed the Capitol.

A man who had committed such “extreme violence,” the judge said — who believed that it was his patriotic duty to take up arms and fight in a new civil war — constituted a danger to the community.The judge sent Mr. Calhoun back to jail.

President Trump returned to the White House on Monday night, staging a defiant, made-for-television moment in which he ripped off his face mask and then urged the nation to put aside the risks of the deadly coronavirus that has swept through his own staff and sent him to the hospital for three days.

Trump climbed into a hermetically sealed, armored Chevy Suburban with at least two Secret Service agents so the president could wave to supporters outside Walter Reed National Military Medical Center in Bethesda, Md., where he was hospitalized from Friday to Monday.

Medical experts said the move put agents at risk.

But the fate of southern Black Americans changed in 1916 when news of better jobs and conditions up North started spreading in rural communities. Black newspapers, like The Chicago Defender, ran stories about opportunities for African Americans in steels mills and factories and encouraged them to leave the South.

"They actually interfered with the U.S. Mail to prevent the Defender from being distributed,” says James Grossman, executive director of the American Historical Association and author of Land of Hope: Chicago, Black Southerners and the Great Migration.

“They believed, incorrectly, that what was really happening was Black people were being stirred up by labor agents from northern industries coming South to round up Black workers.

Black Americans who fled racial oppression either returned to retrieve the rest of their family or sent train tickets back home. In response, as white southerners observed train platforms packed with African Americans, several cities passed ordinances that made it illegal for trains to accept pre-paid tickets.

“Police literally went up to the platforms and rounded people up,” says Grossman, to dissuade Black people from traveling. And the intimidation tactic worked.

A common belief among white southerners was that Black people were intellectually inferior and would not think to move to the North in search of better opportunities.

African American field workers waiting to be paid near Homestead, Florida, 1939.Photo 12/Universal Images Group via Getty Image

Although there were instances of African Americans being recruited to work as Pullman porters on railways and seasonally on tobacco farms in Connecticut, the true northern labor agents were African Americans themselves, says Grossman.

Still, the Great Migration powered on. With a promise of a better life, more dignity and employment, African Americans began to leave from a train station further away, so they wouldn’t be recognized by locals or police officers.

White southerners, anticipating more labor shortages, utilized the mechanical cotton picker more in the 1940s, often evicting Black sharecroppers from their land, who in turn migrated elsewhere in search of work. These developments cemented the African American pilgrimage from the South until the 1970s.

“Security and privacy have long been top companywide priorities at Twitter,” said Twitter spokeswoman Rebecca Hahn. She said that Zatko’s allegations appeared to be “riddled with inaccuracies” and that Zatko “now appears to be opportunistically seeking to inflict harm on Twitter, its customers, and its shareholders.” Hahn said that Twitter fired Zatko after 15 months “for poor performance and leadership.” Attorneys for Zatko confirmed he was fired but denied it was for performance or leadership.

the whistleblower document alleges the company prioritized user growth over reducing spam, though unwanted content made the user experience worse. Executives stood to win individual bonuses of as much as $10 million tied to increases in daily users, the complaint asserts, and nothing explicitly for cutting spam.

Chief executive Parag Agrawal was “lying” when he tweeted in May that the company was “strongly incentivized to detect and remove as much spam as we possibly can,” the complaint alleges.

Zatko described his decision to go public as an extension of his previous work exposing flaws in specific pieces of software and broader systemic failings in cybersecurity. He was hired at Twitter by former CEO Jack Dorsey in late 2020 after a major hack of the company’s systems.

“I felt ethically bound. This is not a light step to take,” said Zatko, who was fired by Agrawal in January. He declined to discuss what happened at Twitter, except to stand by the formal complaint. Under SEC whistleblower rules, he is entitled to legal protection against retaliation, as well as potential monetary rewards.

A person familiar with Zatko’s tenure said the company investigated Zatko’s security claims during his time there and concluded they were sensationalistic and without merit. Four people familiar with Twitter’s efforts to fight spam said the company deploys extensive manual and automated tools to both measure the extent of spam across the service and reduce it.

In 1998, Zatko had testified to Congress that the internet was so fragile that he and others could take it down with a half-hour of concentrated effort. He later served as the head of cyber grants at the Defense Advanced Research Projects Agency, the Pentagon innovation unit that had backed the internet’s invention.

Overall, Zatko wrote in a February analysis for the company attached as an exhibit to the SEC complaint, “Twitter is grossly negligent in several areas of information security. If these problems are not corrected, regulators, media and users of the platform will be shocked when they inevitably learn about Twitter’s severe lack of security basics.”

Zatko’s complaint says strong security should have been much more important to Twitter, which holds vast amounts of sensitive personal data about users. Twitter has the email addresses and phone numbers of many public figures, as well as dissidents who communicate over the service at great personal risk.

This month, an ex-Twitter employee was convicted of using his position at the company to spy on Saudi dissidents and government critics, passing their information to a close aide of Crown Prince Mohammed bin Salman in exchange for cash and gifts.

Zatko’s complaint says he believed the Indian government had forced Twitter to put one of its agents on the payroll, with access to user data at a time of intense protests in the country. The complaint said supporting information for that claim has gone to the National Security Division of the Justice Department and the Senate Select Committee on Intelligence. Another person familiar with the matter agreed that the employee was probably an agent.

“Take a tech platform that collects massive amounts of user data, combine it with what appears to be an incredibly weak security infrastructure and infuse it with foreign state actors with an agenda, and you’ve got a recipe for disaster,” Charles E. Grassley (R-Iowa), the top Republican on the Senate Judiciary Committee,

Many government leaders and other trusted voices use Twitter to spread important messages quickly, so a hijacked account could drive panic or violence. In 2013, a captured Associated Press handle falsely tweeted about explosions at the White House, sending the Dow Jones industrial average briefly plunging more than 140 points.

After a teenager managed to hijack the verified accounts of Obama, then-candidate Joe Biden, Musk and others in 2020, Twitter’s chief executive at the time, Jack Dorsey, asked Zatko to join him, saying that he could help the world by fixing Twitter’s security and improving the public conversation, Zatko asserts in the complaint.

The complaint — filed last month with the Securities and Exchange Commission and the Department of Justice, as well as the FTC — says thousands of employees still had wide-ranging and poorly tracked internal access to core company software, a situation that for years had led to embarrassing hacks, including the commandeering of accounts held by such high-profile users as Elon Musk and former presidents Barack Obama and Donald Trump.

But at Twitter Zatko encountered problems more widespread than he realized and leadership that didn’t act on his concerns, according to the complaint.

Twitter’s difficulties with weak security stretches back more than a decade before Zatko’s arrival at the company in November 2020. In a pair of 2009 incidents, hackers gained administrative control of the social network, allowing them to reset passwords and access user data. In the first, beginning around January of that year, hackers sent tweets from the accounts of high-profile users, including Fox News and Obama.

Several months later, a hacker was able to guess an employee’s administrative password after gaining access to similar passwords in their personal email account. That hacker was able to reset at least one user’s password and obtain private information about any Twitter user.

Twitter continued to suffer high-profile hacks and security violations, including in 2017, when a contract worker briefly took over Trump’s account, and in the 2020 hack, in which a Florida teen tricked Twitter employees and won access to verified accounts. Twitter then said it put additional safeguards in place.

This year, the Justice Department accused Twitter of asking users for their phone numbers in the name of increased security, then using the numbers for marketing. Twitter agreed to pay a $150 million fine for allegedly breaking the 2011 order, which barred the company from making misrepresentations about the security of personal data.

After Zatko joined the company, he found it had made little progress since the 2011 settlement, the complaint says. The complaint alleges that he was able to reduce the backlog of safety cases, including harassment and threats, from 1 million to 200,000, add staff and push to measure results.

But Zatko saw major gaps in what the company was doing to satisfy its obligations to the FTC, according to the complaint. In Zatko’s interpretation, according to the complaint, the 2011 order required Twitter to implement a Software Development Life Cycle program, a standard process for making sure new code is free of dangerous bugs. The complaint alleges that other employees had been telling the board and the FTC that they were making progress in rolling out that program to Twitter’s systems. But Zatko alleges that he discovered that it had been sent to only a tenth of the company’s projects, and even then treated as optional.

“If all of that is true, I don’t think there’s any doubt that there are order violations,” Vladeck, who is now a Georgetown Law professor, said in an interview. “It is possible that the kinds of problems that Twitter faced eleven years ago are still running through the company.”

“Agrawal’s Tweets and Twitter’s previous blog posts misleadingly imply that Twitter employs proactive, sophisticated systems to measure and block spam bots,” the complaint says. “The reality: mostly outdated, unmonitored, simple scripts plus overworked, inefficient, understaffed, and reactive human teams.”

One current and one former employee recalled that incident, when failures at two Twitter data centers drove concerns that the service could have collapsed for an extended period. “I wondered if the company would exist in a few days,” one of them said.

The current and former employees also agreed with the complaint’s assertion that past reports to various privacy regulators were “misleading at best.”

For example, they said the company implied that it had destroyed all data on users who asked, but the material had spread so widely inside Twitter’s networks, it was impossible to know for sure

As the head of security, Zatko says he also was in charge of a division that investigated users’ complaints about accounts, which meant that he oversaw the removal of some bots, according to the complaint. Spam bots — computer programs that tweet automatically — have long vexed Twitter. Unlike its social media counterparts, Twitter allows users to program bots to be used on its service: For example, the Twitter account @big_ben_clock is programmed to tweet “Bong Bong Bong” every hour in time with Big Ben in London. Twitter also allows people to create accounts without using their real identities, making it harder for the company to distinguish between authentic, duplicate and automated accounts.

In the complaint, Zatko alleges he could not get a straight answer when he sought what he viewed as an important data point: the prevalence of spam and bots across all of Twitter, not just among monetizable users.

Zatko cites a “sensitive source” who said Twitter was afraid to determine that number because it “would harm the image and valuation of the company.” He says the company’s tools for detecting spam are far less robust than implied in various statements.

The complaint also alleges that Zatko warned the board early in his tenure that overlapping outages in the company’s data centers could leave it unable to correctly restart its servers. That could have left the service down for months, or even have caused all of its data to be lost. That came close to happening in 2021, when an “impending catastrophic” crisis threatened the platform’s survival before engineers were able to save the day, the complaint says, without providing further details.

The four people familiar with Twitter’s spam and bot efforts said the engineering and integrity teams run software that samples thousands of tweets per day, and 100 accounts are sampled manually.

Some employees charged with executing the fight agreed that they had been short of staff. One said top executives showed “apathy” toward the issue.

Zatko’s complaint likewise depicts leadership dysfunction, starting with the CEO. Dorsey was largely absent during the pandemic, which made it hard for Zatko to get rulings on who should be in charge of what in areas of overlap and easier for rival executives to avoid collaborating, three current and former employees said.

For example, Zatko would encounter disinformation as part of his mandate to handle complaints, according to the complaint. To that end, he commissioned an outside report that found one of the disinformation teams had unfilled positions, yawning language deficiencies, and a lack of technical tools or the engineers to craft them. The authors said Twitter had no effective means of dealing with consistent spreaders of falsehoods.

Dorsey made little effort to integrate Zatko at the company, according to the three employees as well as two others familiar with the process who spoke on the condition of anonymity to describe sensitive dynamics. In 12 months, Zatko could manage only six one-on-one calls, all less than 30 minutes, with his direct boss Dorsey, who also served as CEO of payments company Square, now known as Block, according to the complaint. Zatko allegedly did almost all of the talking, and Dorsey said perhaps 50 words in the entire year to him. “A couple dozen text messages” rounded out their electronic communication, the complaint alleges.

Faced with such inertia, Zatko asserts that he was unable to solve some of the most serious issues, according to the complaint.

Some 30 percent of company laptops blocked automatic software updates carrying security fixes, and thousands of laptops had complete copies of Twitter’s source code, making them a rich target for hackers, it alleges.

A successful hacker takeover of one of those machines would have been able to sabotage the product with relative ease, because the engineers pushed out changes without being forced to test them first in a simulated environment, current and former employees said.

“It’s near-incredible that for something of that scale there would not be a development test environment separate from production and there would not be a more controlled source-code management process,” said Tony Sager, former chief operating officer at the cyberdefense wing of the National Security Agency, the Information Assurance divisio

Sager is currently senior vice president at the nonprofit Center for Internet Security, where he leads a consensus effort to establish best security practices.

The complaint says that about half of Twitter’s roughly 7,000 full-time employees had wide access to the company’s internal software and that access was not closely monitored, giving them the ability to tap into sensitive data and alter how the service worked. Three current and former employees agreed that these were issues.

“A best practice is that you should only be authorized to see and access what you need to do your job, and nothing else,” said former U.S. chief information security officer Gregory Touhill. “If half the company has access to and can make configuration changes to the production environment, that exposes the company and its customers to significant risk.”

The complaint says Dorsey never encouraged anyone to mislead the board about the shortcomings, but that others deliberately left out bad news.

When Dorsey left in November 2021, a difficult situation worsened under Agrawal, who had been responsible for security decisions as chief technology officer before Zatko’s hiring, the complaint says.

An unnamed executive had prepared a presentation for the new CEO’s first full board meeting, according to the complaint. Zatko’s complaint calls the presentation deeply misleading.

The presentation showed that 92 percent of employee computers had security software installed — without mentioning that those installations determined that a third of the machines were insecure, according to the complaint.

Another graphic implied a downward trend in the number of people with overly broad access, based on the small subset of people who had access to the highest administrative powers, known internally as “God mode.” That number was in the hundreds. But the number of people with broad access to core systems, which Zatko had called out as a big problem after joining, had actually grown slightly and remained in the thousands.

The presentation included only a subset of serious intrusions or other security incidents, from a total Zatko estimated as one per week, and it said that the uncontrolled internal access to core systems was responsible for just 7 percent of incidents, when Zatko calculated the real proportion as 60 percent.

Zatko stopped the material from being presented at the Dec. 9, 2021 meeting, the complaint said. But over his continued objections, Agrawal let it go to the board’s smaller Risk Committee a week later.

Agrawal didn’t respond to requests for comment. In an email to employees after publication of this article, obtained by The Post, he said that privacy and security continues to be a top priority for the company, and he added that the narrative is “riddled with inconsistences” and “presented without important context.”

On Jan. 4, Zatko reported internally that the Risk Committee meeting might have been fraudulent, which triggered an Audit Committee investigation.

Agarwal fired him two weeks later. But Zatko complied with the company’s request to spell out his concerns in writing, even without access to his work email and documents, according to the complaint.

Since Zatko’s departure, Twitter has plunged further into chaos with Musk’s takeover, which the two parties agreed to in May. The stock price has fallen, many employees have quit, and Agrawal has dismissed executives and frozen big projects.

Zatko said he hoped that by bringing new scrutiny and accountability, he could improve the company from the outside.

“I still believe that this is a tremendous platform, and there is huge value and huge risk, and I hope that looking back at this, the world will be a better place, in part because of this.”

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

“This is normal for my generation, you know?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Even if only a little of it comes true in the next 10 or 20 years, the most generous redistribution schemes may not ease the ensuing dislocations.

America today is torn apart, culturally and politically, by the continuing legacy of deindustrialization, and material deprivation is only one reason. The displaced manufacturing workers in the Rust Belt and elsewhere did find new jobs, in the main. But many of them seem to derive less meaning from filling orders in an Amazon warehouse or driving for Uber than their forebears had when they were building cars and forging steel—work that felt more central to the grand project of civilization.

It’s hard to imagine how a corresponding crisis of meaning might play out for the professional class, but it surely would involve a great deal of anger and alienation.

Even if we avoid a revolt of the erstwhile elite, larger questions of human purpose will linger. If AI does the most difficult thinking on our behalf, we all may lose agency—at home, at work (if we have it), in the town square—becoming little more than consumption machines, like the well-cared-for human pets in WALL-E

Altman has said that many sources of human joy and fulfillment will remain unchanged—basic biological thrills, family life, joking around, making things—and that all in all, 100 years from now, people may simply care more about the things they cared about 50,000 years ago than those they care about today

In its own way, that too seems like a diminishment, but Altman finds the possibility that we may atrophy, as thinkers and as humans, to be a red herring. He told me we’ll be able to use our “very precious and extremely limited biological compute capacity” for more interesting things than we generally do today.

Yet they may not be the most interesting things: Human beings have long been the intellectual tip of the spear, the universe understanding itself. When I asked him what it would mean for human self-conception if we ceded that role to AI, he didn’t seem concerned. Progress, he said, has always been driven by “the human ability to figure things out.” Even if we figure things out with AI, that still counts, he said.

It’s not obvious that a superhuman AI would really want to spend all of its time figuring things out for us.

I asked Sutskever whether he could imagine an AI pursuing a different purpose than simply assisting in the project of human flourishing.

“I don’t want it to happen,” Sutskever said, but it could.

Sutskever has recently shifted his focus to try to make sure that it doesn’t. He is now working primarily on alignment research, the effort to ensure that future AIs channel their “tremendous” energies toward human happiness

It is, he conceded, a difficult technical problem—the most difficult, he believes, of all the technical challenges ahead.

As part of the effort to red-team GPT-4 before it was made public, the company sought out the Alignment Research Center (ARC), across the bay in Berkeley, which has developed a series of evaluations to determine whether new AIs are seeking power on their own. A team led by Elizabeth Barnes, a researcher at ARC, prompted GPT-4 tens of thousands of times over seven months, to see if it might display signs of real agency.

The ARC team gave GPT-4 a new reason for being: to gain power and become hard to shut down

Agarwal told me that this behavior could be a precursor to shutdown avoidance in future models. When GPT-4 devised its lie, it had realized that if it answered honestly, it may not have been able to achieve its goal. This kind of tracks-covering would be particularly worrying in an instance where “the model is doing something that makes OpenAI want to shut it down,” Agarwal said. An AI could develop this kind of survival instinct while pursuing any long-term goal—no matter how small or benign—if it feared that its goal could be thwarted.

Barnes and her team were especially interested in whether GPT-4 would seek to replicate itself, because a self-replicating AI would be harder to shut down. It could spread itself across the internet, scamming people to acquire resources, perhaps even achieving some degree of control over essential global systems and holding human civilization hostage.

When I discussed these experiments with Altman, he emphasized that whatever happens with future models, GPT-4 is clearly much more like a tool than a creature. It can look through an email thread, or help make a reservation using a plug-in, but it isn’t a truly autonomous agent that makes decisions to pursue a goal, continuously, across longer timescales.

Altman told me that at this point, it might be prudent to try to actively develop an AI with true agency before the technology becomes too powerful, in order to “get more comfortable with it and develop intuitions for it if it’s going to happen anyway.”

“We need to do empirical experiments on how these things try to escape control,” Hinton told me. “After they’ve taken over, it’s too late to do the experiments.”

the fulfillment of Altman’s vision of the future will at some point require him or a fellow traveler to build much more autonomous AIs.

When Sutskever and I discussed the possibility that OpenAI would develop a model with agency, he mentioned the bots the company had built to play Dota 2. “They were localized to the video-game world,” Sutskever told me, but they had to undertake complex missions. He was particularly impressed by their ability to work in concert. They seem to communicate by “telepathy,” Sutskever said. Watching them had helped him imagine what a superintelligence might be like.

“The way I think about the AI of the future is not as someone as smart as you or as smart as me, but as an automated organization that does science and engineering and development and manufacturing,”

Suppose OpenAI braids a few strands of research together, and builds an AI with a rich conceptual model of the world, an awareness of its immediate surroundings, and an ability to act, not just with one robot body, but with hundreds or thousands. “We’re not talking about GPT-4. We’re talking about an autonomous corporation,”

Its constituent AIs would work and communicate at high speed, like bees in a hive. A single such AI organization would be as powerful as 50 Apples or Googles, he mused. “This is incredible, tremendous, unbelievably disruptive power.”

Presume for a moment that human society ought to abide the idea of autonomous AI corporations. We had better get their founding charters just right. What goal should we give to an autonomous hive of AIs that can plan on century-long time horizons, optimizing billions of consecutive decisions toward an objective that is written into their very being?

If the AI’s goal is even slightly off-kilter from ours, it could be a rampaging force that would be very hard to constrain

We know this from history: Industrial capitalism is itself an optimization function, and although it has lifted the human standard of living by orders of magnitude, left to its own devices, it would also have clear-cut America’s redwoods and de-whaled the world’s oceans. It almost did.

one of its principal challenges will be making sure that the objectives we give to AIs stick

We can program a goal into an AI and reinforce it with a temporary period of supervised learning, Sutskever explained. But just as when we rear a human intelligence, our influence is temporary. “It goes off to the world,”

That’s true to some extent even of today’s AIs, but it will be more true of tomorrow’s.

He compared a powerful AI to an 18-year-old heading off to college. How will we know that it has understood our teachings? “Will there be a misunderstanding creeping in, which will become larger and larger?”

Divergence may result from an AI’s misapplication of its goal to increasingly novel situations as the world changes

Or the AI may grasp its mandate perfectly, but find it ill-suited to a being of its cognitive prowess. It might come to resent the people who want to train it to, say, cure diseases. “They want me to be a doctor,” Sutskever imagines an AI thinking. “I really want to be a YouTuber.”

If AIs get very good at making accurate models of the world, they may notice that they’re able to do dangerous things right after being booted up. They might understand that they are being red-teamed for risk, and hide the full extent of their capabilities.

hey may act one way when they are weak and another way when they are strong, Sutskever said

We would not even realize that we had created something that had decisively surpassed us, and we would have no sense for what it intended to do with its superhuman powers.

That’s why the effort to understand what is happening in the hidden layers of the largest, most powerful AIs is so urgent. You want to be able to “point to a concept,” Sutskever said. You want to be able to direct AI toward some value or cluster of values, and tell it to pursue them unerringly for as long as it exists.

we don’t know how to do that; indeed, part of his current strategy includes the development of an AI that can help with the research. If we are going to make it to the world of widely shared abundance that Altman and Sutskever imagine, we have to figure all this out.

This is why, for Sutskever, solving superintelligence is the great culminating challenge of our 3-million-year toolmaking tradition. He calls it “the final boss of humanity.”

“First of all, I think that whether the chance of existential calamity is 0.5 percent or 50 percent, we should still take it seriously,”

. “I don’t have an exact number, but I’m closer to the 0.5 than the 50.”

As to how it might happen, he seems most worried about AIs getting quite good at designing and manufacturing pathogens, and with reason: In June, an AI at MIT suggested four viruses that could ignite a pandemic, then pointed to specific research on genetic mutations that could make them rip through a city more quickly

Around the same time, a group of chemists connected a similar AI directly to a robotic chemical synthesizer, and it designed and synthesized a molecule on its own.

Altman worries that some misaligned future model will spin up a pathogen that spreads rapidly, incubates undetected for weeks, and kills half its victims. He worries that AI could one day hack into nuclear-weapons systems too. “There are a lot of things,” he said, and these are only the ones we can imagine.

Altman told me that he doesn’t “see a long-term happy path” for humanity without something like the International Atomic Energy Agency for global oversight of AI

In San Francisco, Agarwal had suggested the creation of a special license to operate any GPU cluster large enough to train a cutting-edge AI, along with mandatory incident reporting when an AI does something out of the ordinary

Other experts have proposed a nonnetworked “Off” switch for every highly capable AI; on the fringe, some have even suggested that militaries should be ready to perform air strikes on supercomputers in case of noncompliance

Sutskever thinks we will eventually want to surveil the largest, most powerful AIs continuously and in perpetuity, using a team of smaller overseer AIs.

Safety rules for a new technology usually accumulate over time, like a body of common law, in response to accidents or the mischief of bad actors. The scariest thing about genuinely powerful AI systems is that humanity may not be able to afford this accretive process of trial and error. We may have to get the rules exactly right at the outset.

Several years ago, Altman revealed a disturbingly specific evacuation plan he’d developed. He told The New Yorker that he had “guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur” he could fly to in case AI attacks.

if the worst-possible AI future comes to pass, “no gas mask is helping anyone.”

but he told me that he can’t really be sure how AI will stack up. “I just have to build the thing,” he said. He is building fast

Altman insisted that they had not yet begun GPT-5’s training run. But when I visited OpenAI’s headquarters, both he and his researchers made it clear in 10 different ways that they pray to the god of scale. They want to keep going bigger, to see where this paradigm leads. After all, Google isn’t slackening its pace; it seems likely to unveil Gemini, a GPT-4 competitor, within months. “We are basically always prepping for a run,

To think that such a small group of people could jostle the pillars of civilization is unsettling. It’s fair to note that if Altman and his team weren’t racing to build an artificial general intelligence, others still would be

Altman’s views about the likelihood of AI triggering a global class war, or the prudence of experimenting with more autonomous agent AIs, or the overall wisdom of looking on the bright side, a view that seems to color all the rest—these are uniquely his

No single person, or single company, or cluster of companies residing in a particular California valley, should steer the kind of forces that Altman is imagining summoning.

AI may well be a bridge to a newly prosperous era of greatly reduced human suffering. But it will take more than a company’s founding charter—especially one that has already proved flexible—to make sure that we all share in its benefits and avoid its risks. It will take a vigorous new politics.

I don’t think the general public has quite awakened to what’s happening. A global race to the AI future has begun, and it is largely proceeding without oversight or restraint. If people in America want to have some say in what that future will be like, and how quickly it arrives, we would be wise to speak up soon.