Group items tagged

In fact, “public health has actively participated in its own marginalization,” Daniel Goldberg, a historian of medicine at the University of Colorado, told me. As the 20th century progressed, the field moved away from the idea that social reforms were a necessary part of preventing disease and willingly silenced its own political voice. By swimming along with the changing currents of American ideology, it drowned many of the qualities that made it most effective.

Germ theory offered a seductive new vision for defeating disease: Although the old public health “sought the sources of infectious disease in the surroundings of man; the new finds them in man himself,” wrote Hibbert Hill in The New Public Health in 1913

“They didn’t have to think of themselves as activists,” Rosner said. “It was so much easier to identify individual victims of disease and cure them than it was to rebuild a city.”

As public health moved into the laboratory, a narrow set of professionals associated with new academic schools began to dominate the once-broad field. “It was a way of consolidating power: If you don’t have a degree in public health, you’re not public health,”

Mastering the new science of bacteriology “became an ideological marker,” sharply differentiating an old generation of amateurs from a new one of scientifically minded professionals,

Hospitals, meanwhile, were becoming the centerpieces of American health care, and medicine was quickly amassing money and prestige by reorienting toward biomedical research

Public health began to self-identify as a field of objective, outside observers of society instead of agents of social change. It assumed a narrower set of responsibilities that included data collection, diagnostic services for clinicians, disease tracing, and health education.

Assuming that its science could speak for itself, the field pulled away from allies such as labor unions, housing reformers, and social-welfare organizations that had supported city-scale sanitation projects, workplace reforms, and other ambitious public-health projects.

That left public health in a precarious position—still in medicine’s shadow, but without the political base “that had been the source of its power,”

After World War II, biomedicine lived up to its promise, and American ideology turned strongly toward individualism.

Seeing poor health as a matter of personal irresponsibility rather than of societal rot became natural.

Even public health began to treat people as if they lived in a social vacuum. Epidemiologists now searched for “risk factors,” such as inactivity and alcohol consumption, that made individuals more vulnerable to disease and designed health-promotion campaigns that exhorted people to change their behaviors, tying health to willpower in a way that persists today.

Public health is now trapped in an unenviable bind. “If it conceives of itself too narrowly, it will be accused of lacking vision … If it conceives of itself too expansively, it will be accused of overreaching,

“epidemiology isn’t a field of activists saying, ‘God, asbestos is terrible,’ but of scientists calculating the statistical probability of someone’s death being due to this exposure or that one.”

In 1971, Paul Cornely, then the president of the APHA and the first Black American to earn a Ph.D. in public health, said that “if the health organizations of this country have any concern about the quality of life of its citizens, they would come out of their sterile and scientific atmosphere and jump in the polluted waters of the real world where action is the basis for survival.”

a new wave of “social epidemiologists” once again turned their attention to racism, poverty, and other structural problems.

The biomedical view of health still dominates, as evidenced by the Biden administration’s focus on vaccines at the expense of masks, rapid tests, and other “nonpharmaceutical interventions.”

Public health has often been represented by leaders with backgrounds primarily in clinical medicine, who have repeatedly cast the pandemic in individualist terms: “Your health is in your own hands,” said the CDC’s director, Rochelle Walensky, in May

the pandemic has proved what public health’s practitioners understood well in the late 19th and early 20th century: how important the social side of health is. People can’t isolate themselves if they work low-income jobs with no paid sick leave, or if they live in crowded housing or prisons.

This approach appealed, too, to powerful industries with an interest in highlighting individual failings rather than the dangers of their products.

“Public health gains credibility from its adherence to science, and if it strays too far into political advocacy, it may lose the appearance of objectivity,”

In truth, public health is inescapably political, not least because it “has to make decisions in the face of rapidly evolving and contested evidence,” Fairchild told me. That evidence almost never speaks for itself, which means the decisions that arise from it must be grounded in values.

Those values, Fairchild said, should include equity and the prevention of harm to others, “but in our history, we lost the ability to claim these ethical principles.”

“Sick-leave policies, health-insurance coverage, the importance of housing … these things are outside the ability of public health to implement, but we should raise our voices about them,” said Mary Bassett, of Harvard, who was recently appointed as New York’s health commissioner. “I think we can get explicit.”

The future might lie in reviving the past, and reopening the umbrella of public health to encompass people without a formal degree or a job at a health department.

What if, instead, we thought of the Black Lives Matter movement as a public-health movement, the American Rescue Plan as a public-health bill, or decarceration, as the APHA recently stated, as a public-health goal? In this way of thinking, too, employers who institute policies that protect the health of their workers are themselves public-health advocates.

“We need to re-create alliances with others and help them to understand that what they are doing is public health,

Noting that other countries had taken steps to restrict access to the site, the lawmakers also asked about removing it from search results in the United States.

Members of the site are anonymous, but The Times identified 45 people who had spent time on the site and then killed themselves in the United States, the United Kingdom, Italy, Canada and Australia. Most of them were under 30, including several teenagers. The Times also found that more than 500 members of the site wrote so-called goodbye threads announcing how and when they planned to end their lives, and then never posted again.

And the new administrator made the site private, meaning that the content — including discussions about suicide methods, messages of support and thumbs-up emojis to those sharing plans to take their lives, and even real-time posts written by members narrating their attempts — is now visible only to members and not the public.

The site draws six million page views a month, and nearly half of all traffic is driven by online searches, according to data from Similarweb, a web analytics company.

Citing The Times’s reporting, Mr. Blumenthal wrote in his letter, addressed to Google’s chief executive, Sundar Pichai, that the content on the suicide site “makes the world a dark place for too many,” and that Google had the ability and legal authority to steer “people who are struggling away from this dangerous website.”

Google’s hands are not tied, and it has a responsibility to act,

The operators of the suicide site have long used Cloudflare, an American firm that provides cyberprotections, to obscure the names of its web host, making it difficult or impossible to know what company is providing those services.

After the article was published, on Dec. 9, Marquis announced on the site that he was resigning as an administrator, permanently deleting his account and turning over operation of the site to someone using the online name RainAndSadness.

In Uruguay, where assisting suicide is a crime, the Montevideo police have begun an inquiry in collaboration with a local prosecutor’s office in response to The Times’s investigation, said Javier Benech, a communications director for the office.

In the United States, while many states have laws against assisting suicide, they are often vague, do not explicitly address online activity and are rarely enforced.

Members of the suicide site who post instructions on how to die by suicide, or encouragement to follow through with it, could be vulnerable to criminal charges depending on the jurisdiction. But so far, no American law enforcement officials have pursued such cases in connection with the website. Federal law typically protects website operators from liability for users’ posts.

Haugen filed at least eight complaints with the Securities and Exchange Commission alleging that the company is hiding research about its shortcomings from investors and the public.

Haugen, who started at Facebook in 2019 after previously working for other tech giants like Google (GOOGL GOOGLE) and Pinterest (PINS), is set to testify on Tuesday before the Senate Subcommittee on Consumer Protection, Product Safety, and Data Security.

Facebook has aggressively pushed back against the reports, calling many of the claims "misleading" and arguing that its apps do more good than harm.

Lena Pietsch said in a statement to CNN Business immediately following the "60 Minutes" interview. "We continue to make significant improvements to tackle the spread of misinformation and harmful content. To suggest we encourage bad content and do nothing is just not true."

Pietsch released a more than 700-word statement laying out what it called "missing facts" from the segment

Haugen said she believes Facebook Founder and CEO Mark Zuckerberg "never set out to make a hateful platform, but he has allowed choices to be made where the side effects of those choices are that hateful and polarizing content gets more distribution and more reach."

Haugen said she was recruited by Facebook in 2019 and took the job to work on addressing misinformation. But after the company decided to dissolve its civic integrity team shortly after the 2020 Presidential Election, her feelings about the company started to change.

The social media company's algorithm that's designed to show users content that they're most likely to engage with is responsible for many of its problems

Haugen said that while "no one at Facebook is malevolent ... the incentives are misaligned."

the more anger that they get exposed to, the more they interact and the more they consume."

The war in the Pacific was “begun in revenge and complicated by bitter racism,

The fall of Saigon in 1975 may have temporarily hobbled the American strut of exceptionalism and invincibility, but the end of the Cold War and the beginning of Operation Desert Storm worked to restore some American confidence.

she also shows how Hollywood was quick to overwhelm the culture with its “habitual optimism.” The 1947 movie “The Hucksters,” for instance, begins with a veteran returning to the advertising business only to find himself feeling disgusted by it; the happily-ever-after ending comes not with him rejecting the industry but with his resolve to “sell good things, things that people should have, and sell them with dignity and taste.”

Surveying the records of the era, Samet contrasts this dehumanization with the portrayal of European fascists, who were more typically described as “gangsters.”

She ends with a chapter on the old Lost Cause mythology of the Civil War, which we have turned into “a kind of theme park,” suffused with symbolism and nostalgia, ignoring the expansionist wars this mythology later enabled. The country’s imperialist ambitions in the late-19th and early-20th centuries were promoted as a nationalist project that would finally unite the North and South against a foreign enemy.

traditionally “masculine” virtues are not exclusively male. Women who successfully model these attributes are all around us

Rudyard Kipling’s famous poem “If—” is one of the purest distillations of restraint as a traditional manly virtue. It begins with the words “If you can keep your head when all about you / Are losing theirs and blaming it on you.” The entire work speaks of the necessity of calmness and courage.

Stoicism carried to excess can become a dangerous form of emotional repression, a stifling of necessary feelings. But the fact that the kind of patience and perseverance that marks stoicism can be taken too far is not to say that we should shun it. In times of conflict and crisis, it is the calm man or woman who can see clearly.

Hysteria plus cruelty is a recipe for violence. And that brings us back to Mr. Hawley. For all of its faults when taken to excess, the traditional masculinity of which he claims to be a champion would demand that he stand firm against a howling mob. Rather, he saluted it with a raised fist — and then ran from it when it got too close and too unruly.

Catastrophic rhetoric is omnipresent on the right. Let’s go back to the “groomer” smear. It’s a hallmark of right-wing rhetoric that if you disagree with the new right on any matter relating to sex or sexuality, you’re not just wrong; you’re a “groomer” or “soft on pedos.

But conservative catastrophism is only one part of the equation. The other is meanspirited pettiness

Traditional masculinity says that people should meet a challenge with a level head and firm convictions. Right-wing culture says that everything is an emergency, and is to be combated with relentless trolling and hyperbolic insults.

Jonah Goldberg wrote an important piece cataloging the sheer pettiness of the young online right. “Everywhere I look these days,” he wrote, “I see young conservatives believing they should behave like jerks.” As Jonah noted, there are those who now believe it shows “courage and strength to be coarse or bigoted.”

If you spend much time at all on right-wing social media — especially Twitter these days — or listening to right-wing news outlets, you’ll be struck by the sheer hysteria of the rhetoric, the hair-on-fire sense of emergency that seems to dominate all discourse.

American men are in desperate need of virtuous purpose.

I reject the idea that traditional masculinity, properly understood, is, “on the whole, harmful.” I recognize that it can be abused, but it is good to confront life with a sense of proportion, with calm courage and conviction.

One of the best pieces of advice I’ve ever received reflects that wisdom. Early in my legal career, a retired federal judge read a brief that I’d drafted and admonished me to “write with regret, not outrage.”

Husband your anger, he told me. Have patience. Gain perspective. So then, when something truly is terrible, your outrage will mean something. It was the legal admonition against crying wolf.

“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.”

starting in the mid-2010s, those beloved blue skies began to disappear. First, the smoke came in occasional bursts, from wildfires in Canada or California or Siberia, and blew away when the wind changed direction. Within a few summers, though, it was coming in thicker, from more directions at once, and lasting longer.

Sometimes there were weeks when you were advised not to open your windows or exercise outside. Sometimes there were long stretches where you weren’t supposed to breathe the outside air at all.

Now lots of Bryant’s clients wanted to talk about climate change. They wanted to talk about how strange and disorienting and scary this new reality felt, about what the future might be like and how they might face it, about how to deal with all the strong feelings — helplessness, rage, depression, guilt — being stirred up inside them.

As a therapist, Bryant found himself unsure how to respond

while his clinical education offered lots of training in, say, substance abuse or family therapy, there was nothing about environmental crisis, or how to treat patients whose mental health was affected by it

Bryant immersed himself in the subject, joining and founding associations of climate-concerned therapists

eventually started a website, Climate & Mind, to serve as a sort of clearing house for other therapists searching for resources. Instead, the site became an unexpected window into the experience of would-be patients: Bryant found himself receiving messages from people around the world who stumbled across it while looking for help.

Over and over, he read the same story, of potential patients who’d gone looking for someone to talk to about climate change and other environmental crises, only to be told that they were overreacting — that their concern, and not the climate, was what was out of whack and in need of treatment.

“You come in and talk about how anxious you are that fossil-fuel companies continue to pump CO2 into the air, and your therapist says, ‘So, tell me about your mother.’”

In many of the messages, people asked Bryant for referrals to climate-focused therapists in Houston or Canada or Taiwan, wherever it was the writer lived.

his practice had shifted to reflect a new reality of climate psychology. His clients didn’t just bring up the changing climate incidentally, or during disconcerting local reminders; rather, many were activists or scientists or people who specifically sought out Bryant because of their concerns about the climate crisis.

could now turn to resources like the list maintained by the Climate Psychology Alliance North America, which contains more than 100 psychotherapists around the country who are what the organization calls “climate aware.”

But treating those fears also stirred up lots of complicated questions that no one was quite sure how to answer. The traditional focus of his field, Bryant said, could be oversimplified as “fixing the individual”: treating patients as separate entities working on their personal growth

It had been a challenging few years, Bryant told me when I first called to talk about his work. There were some ways in which climate fears were a natural fit in the therapy room, and he believed the field had coalesced around some answers that felt clear and useful

Climate change, by contrast, was a species-wide problem, a profound and constant reminder of how deeply intertwined we all are in complex systems — atmospheric, biospheric, economic — that are much bigger than us. It sometimes felt like a direct challenge to old therapeutic paradigms — and perhaps a chance to replace them with something better.

In one of climate psychology’s founding papers, published in 2011, Susan Clayton and Thomas J. Doherty posited that climate change would have “significant negative effects on mental health and well-being.” They described three broad types of possible impacts: the acute trauma of living through climate disasters; the corroding fear of a collapsing future; and the psychosocial decay that could damage the fabric of communities dealing with disruptive changes

All of these, they wrote, would make the climate crisis “as much a psychological and social phenomenon as a matter of biodiversity and geophysics.”

Many of these predictions have since been borne out

Studies have found rates of PTSD spiking in the wake of disasters, and in 2017 the American Psychological Association defined “ecoanxiety” as “a chronic fear of environmental doom.”

Climate-driven migration is on the rise, and so are stories of xenophobia and community mistrust.

According to a 2022 survey by Yale and George Mason University, a majority of Americans report that they spend time worrying about climate change.

Many say it has led to symptoms of depression or anxiety; more than a quarter make an active effort not to think about it.

There was little or no attention to the fact that living through, or helping to cause, a collapse of nature can also be mentally harmful.

In June, the Yale Journal of Biology and Medicine published a paper cautioning that the world at large was facing “a psychological condition of ‘systemic uncertainty,’” in which “difficult emotions arise not only from experiencing the ecological loss itself,” but also from the fact that our lives are inescapably embedded in systems that keep on making those losses worse.

Climate change, in other words, surrounds us with constant reminders of “ethical dilemmas and deep social criticism of modern society. In its essence, climate crisis questions the relationship of humans with nature and the meaning of being human in the Anthropocene.”

This is not an easy way to live.

Living within a context that is obviously unhealthful, he wrote, is painful: “a dimly intuited ‘fall’ from which we spend our lives trying to recover, a guilt we can never quite grasp or expiate” — a feeling of loss or dislocation whose true origins we look for, but often fail to see. This confusion leaves us feeling even worse.

When Barbara Easterlin first started studying environmental psychology 30 years ago, she told me, the focus of study was on ways in which cultivating a relationship with nature can be good for mental health

A poll by the American Psychiatric Association in the same year found that nearly half of Americans think climate change is already harming the nation’s mental health.

the field is still so new that it does not yet have evidence-tested treatments or standards of practice. Therapists sometimes feel as if they are finding the path as they go.

Rebecca Weston, a licensed clinical social worker practicing in New York and a co-president of the CPA-NA, told me that when she treats anxiety disorders, her goal is often to help the patient understand how much of their fear is internally produced — out of proportion to the reality they’re facing

climate anxiety is a different challenge, because people worried about climate change and environmental breakdown are often having the opposite experience: Their worries are rational and evidence-based, but they feel isolated and frustrated because they’re living in a society that tends to dismiss them.

One of the emerging tenets of climate psychology is that counselors should validate their clients’ climate-related emotions as reasonable, not pathological

it does mean validating that feelings like grief and fear and shame aren’t a form of sickness, but, as Weston put it, “are actually rational responses to a world that’s very scary and very uncertain and very dangerous for people

In the words of a handbook on climate psychology, “Paying heed to what is happening in our communities and across the globe is a healthier response than turning away in denial or disavowal.”

But this, too, raises difficult questions. “How much do we normalize people to the system we’re in?” Weston asked. “And is that the definition of health?

Or is the definition of health resisting the things that are making us so unhappy? That’s the profound tension within our field.”

“It seems to shift all the time, the sort of content and material that people are bringing in,” Alexandra Woollacott, a psychotherapist in Seattle, told the group. Sometimes it was a pervasive anxiety about the future, or trauma responses to fires or smoke or heat; other times, clients, especially young ones, wanted to vent their “sort of righteous anger and sense of betrayal” at the various powers that had built and maintained a society that was so destructive.

“I’m so glad that we have each other to process this,” she said, “because we’re humans living through this, too. I have my own trauma responses to it, I have my own grief process around it, I have my own fury at government and oil companies, and I think I don’t want to burden my clients with my own emotional response to it.”

In a field that has long emphasized boundaries, discouraging therapists from bringing their own issues or experiences into the therapy room, climate therapy offers a particular challenge: Separation can be harder when the problems at hand affect therapist and client alike

Some therapists I spoke to were worried about navigating the breakdown of barriers, while others had embraced it. “There is no place on the planet that won’t eventually be impacted, where client and therapist won’t be in it together,” a family therapist wrote in a CPA-NA newsletter. “Most therapists I know have become more vulnerable and self-disclosing in their practice.”

“If you look at or consider typical theoretical framings of something like post-traumatic growth, which is the understanding of this idea that people can sort of grow and become stronger and better after a traumatic event,” she said, then the climate crisis poses a dilemma because “there is no afterwards, right? There is no resolution anytime in our lifetimes to this crisis that we nonetheless have to build the capacities to face and to endure and to hopefully engage.”

many of her patients are also disconnected from the natural world, which means that they struggle to process or even recognize the grief and alienation that comes from living in a society that treats nature as other, a resource to be used and discarded.

“How,” she asked, “do you think about resilience apart from resolution?”

she believed this framing reflected and reinforced a bias inherent in a field that has long been most accessible to, and practiced by, the privileged. It was hardly new in the world, after all, to face the collapse of your entire way of life and still find ways to keep going.

Torres said that she sometimes takes her therapy sessions outside or asks patients to remember their earliest and deepest connections with animals or plants or places. She believes it will help if they learn to think of themselves “as rooted beings that aren’t just simply living in the human overlay on the environment.” It was valuable to recognize, she said, that “we are part of the land” and suffer when it suffers.

Torres described introducing her clients to methods — mindfulness, distress tolerance, emotion regulation — to help them manage acute feelings of stress or panic and to avoid the brittleness of burnout.

She also encourages them to narrativize the problem, including themselves as agents of change inside stories about how they came to be in this situation, and how they might make it different.

then she encourages them to find a community of other people who care about the same problems, with whom they could connect outside the therapy room. As Woollacott said earlier: “People who share your values. People who are committed to not looking away.”

Dwyer told the group that she had been thinking more about psychological adaptation as a form of climate mitigation

Therapy, she said, could be a way to steward human energy and creative capacities at a time when they’re most needed.

It was hard, Bryant told me when we first spoke, to do this sort of work without finding yourself asking bigger questions — namely, what was therapy actually about?

Many of the therapists I talked to spoke of their role not as “fixing” a patient’s problem or responding to a pathology, but simply giving their patients the tools to name and explore their most difficult emotions, to sit with painful feelings without instantly running away from them

many of the methods in their traditional tool kits continue to be useful in climate psychology. Anxiety and hopelessness and anger are all familiar territory, after all, with long histories of well-studied treatments.

They focused on trying to help patients develop coping skills and find meaning amid destabilization, to still see themselves as having agency and choice.

Weston, the therapist in New York, has had patients who struggle to be in a world that surrounds them with waste and trash, who experience panic because they can never find a place free of reminders of their society’s destruction

eston said, that she has trouble with the repeated refrain that therapist and patient experiencing the same losses and dreads at the same time constituted a major departure from traditional therapeutic practice

“I’m so excited by what you’re bringing in,” Woollacott replied. “I’m doing psychoanalytic training at the moment, and we study attachment theory” — how the stability of early emotional bonds affects future relationships and feelings of well-being. “But nowhere in the literature does it talk about our attachment to the land.”

Lately, Bryant told me, he’s been most excited about the work that happens outside the therapy room: places where groups of people gather to talk about their feelings and the future they’re facing

It was at such a meeting — a community event where people were brainstorming ways to adapt to climate chaos — that Weston, realizing she had concrete skills to offer, was inspired to rework her practice to focus on the challenge. She remembers finding the gathering empowering and energizing in a way she hadn’t experienced before. In such settings, it was automatic that people would feel embraced instead of isolated, natural that the conversation would start moving away from the individual and toward collective experiences and ideas.

There was no fully separate space, to be mended on its own. There was only a shared and broken world, and a community united in loving it.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

OpenAI was was trying to balance safety and development — a balance that became harder to maintain under the pressures of commercialization.

It was founded as a nonprofit by people who professed sincere concern about taking things safe and slow. But it was also full of AI nerds who wanted to, you know, make cool AIs.

OpenAI set up a for-profit arm — but with a corporate structure that left the nonprofit board able to cry “stop” if things started moving too fast (or, if you prefer, gave “a handful of people with no financial stake in the company the power to upend the project on a whim”).

On Friday, those people, in a fit of whimsy, kicked Brockman off the board and fired Altman. Reportedly, the move was driven by Ilya Sutskever, OpenAI’s chief scientist, who, along with other members of the board, has allegedly clashed repeatedly with Altman over the speed of generative AI development and the sufficiency of safety precautions.

Chief among the signatories was Sutskever, who tweeted Monday morning, “I deeply regret my participation in the board’s actions. I never intended to harm OpenAI. I love everything we’ve built together and I will do everything I can to reunite the company.”

Humanity can’t help itself; we have kept monkeying with technology, no matter the dangers, since some enterprising hominid struck the first stone ax.

a software company has little in the way of tangible assets; its people are its capital. And this capital looks willing to follow Altman to where the money is.

More broadly still, it perfectly encapsulates the AI alignment problem, which in the end is also a human alignment problem

And that’s why we are probably not going to “solve” it so much as hope we don’t have to.

it’s also a valuable general lesson about corporate structure and corporate culture. The nonprofit’s altruistic mission was in tension with the profit-making, AI-generating part — and when push came to shove, the profit-making part won.

When scientists started messing with the atom, there were real worries that nuclear weapons might set Earth’s atmosphere on fire. By the time an actual bomb was exploded, scientists were pretty sure that wouldn’t happen

But if the worries had persisted, would anyone have behaved differently — knowing that it might mean someone else would win the race for a superweapon? Better to go forward and ensure that at least the right people were in charge.

Now consider Sutskever: Did he change his mind over the weekend about his disputes with Altman? More likely, he simply realized that, whatever his reservations, he had no power to stop the bobsled — so he might as well join his friends onboard. And like it or not, we’re all going with them.

All the empathy and humility in the world will not mean much against the pressures of intolerance and tribalism without an invaluable quality that Sulzberger did not emphasise: courage.

Sulzberger seems to underestimate the struggle he is in, that all journalism and indeed America itself is in

In describing the essential qualities of independent journalism in his essay, he unspooled a list of admirable traits – empathy, humility, curiosity and so forth. These qualities have for generations been helpful in contending with the Times’s familiar problem, which is liberal bias

on their own, these qualities have no chance against the Times’s new, more dangerous problem, which is in crucial respects the opposite of the old one.

The Times’s problem has metastasised from liberal bias to illiberal bias, from an inclination to favour one side of the national debate to an impulse to shut debate down altogether

the internet knocked the industry off its foundations. Local newspapers were the proving ground between college campuses and national newsrooms. As they disintegrated, the national news media lost a source of seasoned reporters and many Americans lost a journalism whose truth they could verify with their own eyes.

far more than when I set out to become a journalist, doing the work right today demands a particular kind of courage: