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When broken out by how masculine or feminine they identified themselves, completely masculine men were the only group where the majority (60 percent) said they had voted for Trump.

research conducted before the election found that these men, or men who fall into a similar category, were less likely to wear masks in the first place or take other precautions to stop the spread of COVID-19, including social distancing.

this conclusion lines up with a broader tendency among men to take fewer health precautions period — like wearing seat belts or going to the doctor regularly. Cassino said that traditional stereotypes around masculinity encourage men to shake off vulnerability, such as hiding a fear of illness and instead projecting strength

. “Reaffirming that you are traditionally masculine is itself a political statement today — a way to push back on changes to the way society is organized,” he said.

this reflects the extent to which Americans’ views about gender roles have become intertwined with their partisan identity,

“COVID-19 makes men focus more on their masculine identity than they otherwise would have, because they feel this pressure to say and demonstrate, ‘Yeah, this big scary medical crisis is happening, but it’s not going to affect me,’” Cassino said.

Republican men who identified as completely masculine were somewhat more likely than less-masculine Republican men to approve of the way Trump has handled the pandemic, although the difference wasn’t necessarily all that huge (79 percent compared with 69 percent).

One possible explanation is that the threat of business closures or other restrictions on the economy may have been alarming especially to men who identify as completely masculine. “Because employment and working is so central to American masculinity, job loss is seen as a threat to masculinity,”

by actively seizing on the spread of COVID-19 as an opportunity to emphasize his own brand of hypermasculinity and portray his opponent as weak and ineffective, Trump may have crafted a tailor-made pitch for men whose own sense of masculinity was threatened by the pandemic.

According to the Institute for Health Metrics and Evaluation's latest model, by March 1, the U.S. may see nearly 439,000 total deaths from COVID-19. But Mokdad and his colleagues have calculated two alternative scenarios, depending on the path the country takes. If governmental mandates to limit the spread are eased, the model predicts more deaths: perhaps 587,000 by March 1.

There has been good news this month, with Pfizer and Moderna each announcing that their experimental vaccines are highly effective in preventing disease – 95% in the case of Pfizer's, and nearly 95% for Moderna's.

"That means that schools and other institutions that serve primarily children may be continue to need to follow the nonpharmaceutical interventions longer than older adult communities, for example, just because they will not be eligible for the vaccine right away," she says.

"We are in a worse place than we were even in the spring, because in the spring it was primarily New York City and New Jersey and Connecticut that were experiencing a strain on their health care systems," Rivers says. "Right now we are seeing intense community transmission really all across the country. And that doesn't leave a lot of wiggle room to make sure that we are able to deploy extra resources to those places."

As the pandemic stretches on, people get tired of being vigilant about masks and social distancing and not gathering with others indoors. Many people have suffered economic pain from the virus and the restrictions that have followed, and are eager for their lives to return to normal.

Public health officials are pleading with Americans not to celebrate Thanksgiving the way they usually do but instead use this occasion to invent new traditions. One idea is to drop off food contactlessly to another household and then share the meal over video.

Infection numbers in Massachusetts are eight times what they were on Labor Day and hospitalizations have quadrupled.

In Illinois, the virus is now the third leading cause of death behind heart disease and cancer.

More than 250,000 Americans have so far died of the virus -- a higher death toll than any other country -- and a forecast by the US Centers for Disease Control and Prevention projects that number could rise up to 298,000 by December 12.

"It's all about absolute adherence to wearing a mask, avoiding crowds, and yes, we can keep the economy open but we're going to have to diminish indoor places like indoor dining and restaurants."

Only one US state, Hawaii, is showing a decrease in new cases greater than 10% compared to the previous week. Five others -- Idaho, North Dakota, Iowa, Illinois and Arkansas -- are holding steady, while the remaining 44 states are showing increases in new cases greater than at least 10% compared to the week prior.

the 7-day average of new cases is at its highest ever: 161,165 cases a day. That's up 27% compared to last week.

"Virtual gatherings remain the safest way to bring friends and family together from distant points. Outdoor settings can reduce the risks of gatherings with people outside of your household," the group said, also highlighting the importance of face coverings.

New Jersey Gov. Phil Murphy told CNN he wanted people to stay with their immediate family on Thanksgiving and to keep gatherings small -- "not just for next Thursday ... but for the next couple of months."

"This is not a normal year, it's not a normal Thanksgiving, Hanukkah, Christmas, New Year's. Folks have got to stay small, stay within the bubble of their own loved ones, and if we do that, that will be a down payment on a back-to-normal holiday season next year."

There were 79,410 hospitalizations reported on Wednesday, a record high for the United States, according to the Covid Tracking Project. The country is now averaging 72,120 hospitalizations over the last 7 days -- a 19.76% increase compared to last week.

"As a health care provider we are on 250 days of having a Covid patient in our ICU right now,"

"So every day, you walk into work, someone is super sick, someone is potentially dying that day."

"On a normal day, I don't have people dying every day," she said, adding that first week she had three people die in one day -- two of them, from Covid-19.

Students in the country's largest school district are transitioning to remote learning on Thursday following the closure of New York City schools. The decision came after the city's test infection rate reached 3%, a threshold Mayor Bill de Blasio said would trigger such a closure.

Kentucky Gov. Andy Beshear also announced new measures that will go into effect Friday, including limiting social gatherings to a maximum of two people from no more than two households, and prohibiting indoor service for restaurants and bars. And starting Monday, schools should begin remote learning, the governor said.

In Minnesota, the governor said the state is at a "breaking point" and announced a four-week dial back that will "help prevent more families from losing a loved one and ensure our hospitals can treat those who fall ill."

"As hospitals near the crisis of turning away new patients, continuing as things are is simply not sustainable," Gov. Tim Walz said.

A final analysis of the Phase 3 trial of Pfizer's Covid-19 vaccine shows it was 95% effective in preventing infections, even in older adults and caused no serious safety concerns, the company said Wednesday. It said it will seek a US Food and Drug Administration emergency use authorization "within days."

The Pfizer analysis came just days after a separate vaccine maker, Moderna, released early data showing its vaccine was about 95% effective.

Distribution is expected to begin within 24 hours after a vaccine receives the green light, according to Gen. Gustave Perna, who is helping oversee Operation Warp Speed.

"We'll be more ready next week, and if the vaccine is available, we have to go with what we have. We may not be perfect, but every day we're more prepared than we were the day before," he added.

If authorized, the US plans to start by shipping about 6 million doses across the country, said Gen. Gustave Perna, chief operating officer of Operation Warp Speed.

"We're going to have enough for 20 million people to get vaccinated by the end of December," Health and Human Services Secretary Alex Azar said.

About 2.9 million doses of the vaccine either have been or will be received nationwide this week. That's enough to start vaccinating 1.45 million people, since each person needs two doses.

More than 300,000 people in the US have died from coronavirus in 10 months, according to Johns Hopkis.

In the past week, the US has reported an average of more than 215,000 new infections a day, according to Johns Hopkins University.

The CDC has recommended that health care workers and residents of long-term care facilities get the vaccine first.

And another 186,000 are projected to die over the next three months, according to the University of Washington's Institute for Health Metrics and Evaluation. "

"There are tens of thousands of Black and brown people dying every year because they are distrustful of the system," Adams said. "In many cases, rightly so, but also because they're not getting the facts to help restore their trust in the system."

In California, Gov. Gavin Newsom said that while the vaccines offered a moment of hope, he added "we are in the midst of the worst moment of this pandemic."

Los Angeles County health officials said Monday new cases have increased 625% since November 1, with "younger people continuing to drive the increase in community transmission."

"Our reality is frightening at the moment," they said in a statement. "By next weekend, there are likely to be over 5,000 patients hospitalized and more than 50% of ICU beds occupied by COVID-19 patients."

In New York City, Mayor Bill de Blasio hinted at tighter restrictions in the coming weeks, saying the city was on a "very troubling" trajectory, "in terms of the number of people who get sick, the number of people we would lose ... and obviously the impact on hospitals, their ability to treat people."

"We will be monitoring and evaluating our current situation day to day and ... (we) will remain under the current restrictions for now, with the goal of getting through the next month."

"If officials and experts agree that our trends are going beyond our ability to respond, I will be forced to come in front of you all again with tougher actions."

The Asian-American coalition, by contrast, is demanding policies that in some way address those who are struggling and in need, and who are often people of color.

“Asian-Americans converge in several notable ways, including experiences with discrimination, voting behavior and attitudes on policies ranging from environmental protection to gun control to higher taxation and social service provision.”

The question for the Asian-American coalition, as for the Democratic Party as a whole, is what constitutes economic justice: the Clinton-Obama neoliberalism of favoring Wall Street and trade deals, with insufficient attention paid to the middle and working classes?

Or a more robust form of economic redistribution that would tax the wealthy at a higher rate, eliminate or greatly reduce student and medical debt, expand health insurance and child care, bolster public schools and enhance access to higher education?

As today’s Asian-American coalition sees it, no policy can be carried out effectively without paying attention to identities and differences

The majority of Asian-Americans, for example, support affirmative action, recognizing that it is needed to reduce inequities not only for African-Americans and Latinos but also for Pacific Islanders and poorer Asian-Americans.

Group interest and self-interest sometimes align and sometimes don’t, but solidarity entails that a coalition’s members sometimes seek justice for themselves, and sometimes for others.

A crucial lesson of the Asian-American coalition is that although celebrating diversity can sometimes draw attention away from issues of economic inequality, that does not mean that a focus on diversity, difference or identity ignores economic inequality. On the contrary, economic inequality in this country has always been built on racial differences.

Only the affirmation of racial differences, harnessed with a robust approach to economic justice, can help alleviate the many economic problems this country faces.

The Harriman railroad fortune paid local charities, such as the New York Bureau of Industries and Immigration, to seek out Jewish, Italian and other immigrants in New York and other crowded cities and subject them to deportation, trumped up confinement or forced sterilization.

The Rockefeller Foundation helped found the German eugenics program and even funded the program that Josef Mengele worked in before he went to Auschwitz.

In an America demographically reeling from immigration upheaval and torn by post-Reconstruction chaos, race conflict was everywhere in the early twentieth century. Elitists, utopians and so-called "progressives" fused their smoldering race fears and class bias with their desire to make a better world.

They reinvented Galton's eugenics into a repressive and racist ideology. The intent: populate the earth with vastly more of their own socio-economic and biological kind--and less or none of everyone else.

How? By identifying so-called "defective" family trees and subjecting them to lifelong segregation and sterilization programs to kill their bloodlines. The grand plan was to literally wipe away the reproductive capability of those deemed weak and inferior--the so-called "unfit."

Eighteen solutions were explored in a Carnegie-supported 1911 "Preliminary Report of the Committee of the Eugenic Section of the American Breeder's Association to Study and to Report on the Best Practical Means for Cutting Off the Defective Germ-Plasm in the Human Population." Point eight was euthanasia.

The most commonly suggested method of eugenicide in America was a "lethal chamber" or public locally operated gas chambers.

Applied Eugenics also devoted a chapter to "Lethal Selection," which operated "through the destruction of the individual by some adverse feature of the environment, such as excessive cold, or bacteria, or by bodily deficiency."

Eugenic breeders believed American society was not ready to implement an organized lethal solution. But many mental institutions and doctors practiced improvised medical lethality and passive euthanasia on their own.

One institution in Lincoln, Illinois fed its incoming patients milk from tubercular cows believing a eugenically strong individual would be immune. Thirty to forty percent annual death rates resulted at Lincoln.

Some doctors practiced passive eugenicide one newborn infant at a time. Others doctors at mental institutions engaged in lethal neglect.

Only after eugenics became entrenched in the United States was the campaign transplanted into Germany, in no small measure through the efforts of California eugenicists, who published booklets idealizing sterilization and circulated them to German officials and scientists.

Hitler studied American eugenics laws. He tried to legitimize his anti-Semitism by medicalizing it, and wrapping it in the more palatable pseudoscientific facade of eugenics. Hitler was able to recruit more followers among reasonable Germans by claiming that science was on his side. While Hitler's race hatred sprung from his own mind, the intellectual outlines of the eugenics Hitler adopted in 1924 were made in America.

In Mein Kampf, published in 1924, Hitler quoted American eugenic ideology and openly displayed a thorough knowledge of American eugenics. "There is today one state," wrote Hitler, "in which at least weak beginnings toward a better conception [of immigration] are noticeable. Of course, it is not our model German Republic, but the United States."

Hitler even wrote a fan letter to American eugenic leader Madison Grant calling his race-based eugenics book, The Passing of the Great Race his "bible."

In 1934, as Germany's sterilizations were accelerating beyond 5,000 per month, the California eugenics leader C. M. Goethe upon returning from Germany ebulliently bragged to a key colleague, "You will be interested to know, that your work has played a powerful part in shaping the opinions of the group of intellectuals who are behind Hitler in this epoch-making program. Everywhere I sensed that their opinions have been tremendously stimulated by American thought.…I want you, my dear friend, to carry this thought with you for the rest of your life, that you have really jolted into action a great government of 60 million people."

In the fall of 1950, the University of Münster offered Verschuer a position at its new Institute of Human Genetics, where he later became a dean. In the early and mid-1950s, Verschuer became an honorary member of numerous prestigious societies, including the Italian Society of Genetics, the Anthropological Society of Vienna, and the Japanese Society for Human Genetics.

Another in the Kaiser Wilhelm Institute's eugenic complex of institutions was the Institute for Brain Research. Since 1915, it had operated out of a single room. Everything changed when Rockefeller money arrived in 1929. A grant of $317,000 allowed the Institute to construct a major building and take center stage in German race biology. The Institute received additional grants from the Rockefeller Foundation during the next several years. Leading the Institute, once again, was Hitler's medical henchman Ernst Rüdin. Rüdin's organization became a prime director and recipient of the murderous experimentation and research conducted on Jews, Gypsies and others.

Leon Whitney, executive secretary of the American Eugenics Society declared of Nazism, "While we were pussy-footing around…the Germans were calling a spade a spade."

Mengele began searching the boxcar arrivals for twins. When he found them, he performed beastly experiments, scrupulously wrote up the reports and sent the paperwork back to Verschuer's institute for evaluation. Often, cadavers, eyes and other body parts were also dispatched to Berlin's eugenic institutes.

More than just providing the scientific roadmap, America funded Germany's eugenic institutions. By 1926, Rockefeller had donated some $410,000 -- almost $4 million in 21st-Century money -- to hundreds of German researchers. In May 1926, Rockefeller awarded $250,000 to the German Psychiatric Institute of the Kaiser Wilhelm Institute, later to become the Kaiser Wilhelm Institute for Psychiatry

Human genetics' genocidal roots in eugenics were ignored by a victorious generation that refused to link itself to the crimes of Nazism and by succeeding generations that never knew the truth of the years leading up to war. Now governors of five states, including California have issued public apologies to their citizens, past and present, for sterilization and other abuses spawned by the eugenics movement.

“There was nothing but crap out there. Crap in every sense. I was beginning to feel that people’s predictions about the dumbing-down of society had happened and were happening, and I started to see everything getting tawdry and cheap.”

Younger viewers do not have to fear Chase’s wrath, because they are not so obviously its object. They are also able to watch the show for hours on end, which makes the subtext and themes more apparent. Perhaps all of this has offered clarity that was not possible when the show aired. Perhaps it is easier now to see exactly who — or what — Chase was angry at.

it is easily one of the most written-about TV shows in the medium’s short history. But more than the shows that have emerged in its wake, which are subjected to close readings and recaps in nearly every major publication, “The Sopranos” has a novelistic quality that actually withstands this level of scrutiny. It’s not uncommon to hear from people who have watched the series several times, or who do so on a routine basis — people who say it reveals new charms at different points in life

Perhaps the greatest mystery of all, looking back on “The Sopranos” all these years later, is this: What was Chase seeing in the mid-’90s — a period when the United States’ chief geopolitical foe was Serbia, when the line-item veto and school uniforms were front-page news, when “Macarena” topped the charts — that compelled him to make a show that was so thoroughly pessimistic about this country?

“I don’t think I felt like it was a good time,” he told me. He is 76 now, and speaks deliberately and thoughtfully. “I felt that things were going downhill.” He’d become convinced America was, as Neil Postman’s 1985 polemic put it, “Amusing Ourselves to Death,” not an easy thing for a journeyman TV writer to accept.

that’s what I felt back in those days,” he said, “that everything was for sale — it was all about distraction, it didn’t seem serious. It all felt foolish and headed for a crash.”

Expanded access to credit had cut into what mobsters call the shylock business; there’s no need to go to a loan shark when the payday lender will offer you similarly competitive rates. Gambling was legalized in many states and flourishes on many reservations; nearly every state in the Union has a lottery, which decimated the numbers racket. Italian American neighborhoods have emptied out — as Jacobs writes, “radically diminishing the pool of tough teenagers with Cosa Nostra potential”; this is dramatized brilliantly in the final episode of the series, when a mobster from a New York family hurries through Little Italy on an important phone call and, when the call ends, looks around to see he’s wandered into an encroaching and vibrant Chinatown. And, Jacobs notes, union membership has been decimated. “In the mid-1950s, about 35 percent of U.S. workers belonged to a union,” he writes. “In recent years, only 6.5 percent of private-sector workers have been union members.”

I was about to change the subject when he hit on something. “Have you noticed — or maybe you haven’t noticed — how nobody does what they say they’re going to do?” he said, suddenly animated. “If your sink gets jammed up, and a guy says he’s going to be out there at 5:30 — no. Very few people do what they say they’re going to do. There is a decline in goods and services that is enormous.”

Chase told me the real joke of the show was not “What if a mobster went to therapy?” The comedic engine, for him, was this: What if things had become so selfish and narcissistic in America that even the mob couldn’t take it? “That was the whole thing,” he said. “America was so off the rails that everything that the Mafia had done was nothing compared to what was going on around them.”

In “The Mafia: A Cultural History,” Roberto M. Dainotto, a professor of literature at Duke, writes that one thing our cinematic Mafiosi have that we admire, against our better judgment, is access to structures of meaning outside of market forces: the church, family, honor. The Mafia movie often pits these traditional values against the corrosive and homogenizing effects of American life.

What “The Sopranos” shows us, Dainotto argues, is what happens when all that ballast is gone, and the Mafia is revealed to be as ignoble as anything else. “Life is what it is,” he writes, “and repeats as such.”

The show puts all this American social and cultural rot in front of characters wholly incapable of articulating it, if they even notice it.

What is, for me, one of the show’s most memorable scenes has no dialogue at all. Tony and his crew have just returned from a business trip to Italy, during which they were delighted with the Old Country but also confronted with the degree of their alienation from their own heritage. They’re off the plane, and in a car traveling through Essex County. As the camera pans by the detritus of their disenchanted world — overpasses, warehouses — Tony, Paulie and Christopher are seeing their home with fresh eyes, and maybe wondering if their ancestors made a bad trade or if, somewhere along the line, something has gone horribly wrong. But we don’t know: For once, these arrogant, stupid and loquacious men are completely silent.

Around the time “The Sopranos” premiered, the N.Y.U. Law professor James B. Jacobs wrote a paper, along with a student, arguing that the Mafia, though weakened by decades of prosecutions, could come roaring back. By 2019, though, he had published a new paper called “The Rise and Fall of Organized Crime in the United States,” declaring the Mafia all but finished. “The world in which the Cosa Nostra became powerful is largely gone,” he wrote. And he cites a litany of factors that aided its collapse, a mix of technological advances, deregulation and financialization — many of the same forces that have created the stratified economy of today.

In his first therapy session with Dr. Melfi, Tony tries to explain why he thinks he has panic attacks, why he suffers from stress. “The morning of the day I got sick, I’d been thinking: It’s good to be in something from the ground floor,” he says. “I came too late for that, I know. But lately, I’m getting the feeling that I came in at the end. The best is over.” Melfi tells him that many Americans feel that way. Tony presses on: “I think about my father: He never reached the heights like me, but in a lot of ways he had it better. He had his people, they had their standards, they had their pride. Today, what do we got?”

You can see this world — one in which no one can be squeezed because everyone is being squeezed — starting to take shape from the very beginning of the show. In the pilot, Tony is fending off competition from a new waste-hauling business undercutting his company’s extortionate fees, and trying to figure out how he can get a piece of the similarly extortionate costs his health insurer paid for his M.R.I. — a procedure he had because the stress in his life had given him a panic attack.

The bien-pensant line on Tony remains that he’s a sociopath, and only used therapy to become a better criminal. This is an idea spoon-fed to the viewer in the final episodes by a contrite Dr. Melfi, in a show that spoon-feeds almost nothing to the viewer. Melfi herself might call this a coping mechanism to avoid the messier reality, which is that Tony lives in an immoral world nestled within another immoral world, both of which have only grown more chaotic because of forces outside his control.

Because of this, you can see how he reasons himself into more and more heinous crimes, justifying each and every one of them to himself. Perhaps to you too — at least, up to a point. That sympathy for Tony led contemporaneous critics to ask if people were watching the show in the wrong way, or if our enjoyment pointed to a deficiency of the heart.

t is this quality of Tony’s — this combination of privilege and self-loathing — that I suspect resonates with a younger generation, whether we want to admit it or not. He’s not so different from us, after all. He has an anxiety disorder. He goes to therapy and takes S.S.R.I.s, but never really improves — not for long, anyway. He has a mild case of impostor syndrome, having skipped some key steps to becoming boss, and he knows that people who hold it against him are sort of right. He’s still proud of his accomplishments in high school. He does psychedelics in the desert, and they change his perspective on things. He often repeats stuff he half-remembers someone smarter than him saying. He’s arguably in an open marriage with Carmela, if a rather lopsided one. He liked listening to “Don’t Stop Believin’” in 2007. He’s impulsive and selfish and does not go to church, though he does seem open to vaguer notions of spirituality. He wishes his career provided him with meaning, but once he had the career, he discovered that someone had pulled the rug out at some point, and an institution that had been a lodestar to him for his whole life was revealed to be a means of making money and nothing more. Does this sound at all familiar to you?

Like many young people, Tony is a world-historically spoiled man who is nevertheless cursed, thanks to timing, to live out the end of an enterprise he knows on some level to be immoral.

It gives him panic attacks, but he’s powerless to find a way out. Thus trapped — and depressed — it’s not so hard for him to allow himself a few passes, to refuse to become better because the world is so rotten anyway.

Tony’s predicament was once his to suffer alone, but history has unfolded in such a way as to render his condition nearly universal.

That the people in power truly had insulated themselves in a fantasy environment — not just in the realm of foreign policy, but also, more concretely, in the endless faux-bucolic subdivisions that would crater the economy. We were living in a sort of irreality, one whose totality would humiliate and delegitimize nearly every important institution in American life when it ended, leaving — of all people — the Meadows and A.J.s of the world to make sense of things.

The notion that individual action might help us avoid any coming or ongoing crises is now seen as hopelessly naïve, the stuff of Obama-era liberalism.

Whether that’s true or not, it offers us all permission to become little Tonys, lamenting the sad state of affairs while doing almost exactly nothing to improve ourselves, or anything at all.

This tendency is perhaps most pronounced online, where we are all in therapy all day, and where you can find median generational opinions perfectly priced by the marketplace of ideas — where we bemoan the wrongs of the world and tell ourselves that we can continue being who we are, and enjoy the comforts we’ve grown accustomed to.

In the show’s finale, as the extended Soprano family gathers to mourn the death of Bobby Baccalieri, we find Paulie Walnuts stuck at the kids’ table, where A.J., newly politically awakened, charges into a rant. You people are screwed, he says. “You’re living in a dream.” Bush let Al Qaeda escape, he tells them, and then made us invade some other country? Someone at the table tells him that if he really cares, he should join up. A.J. responds: “It’s more noble than watching these jackoff fantasies on TV of how we’re kicking their ass. It’s like: America.” Again, he’s interrupted: What in the world does he mean? He explains: “This is still where people come to make it. It’s a beautiful idea. And then what do they get? Bling? And come-ons for [expletive] they don’t need and can’t afford?”

However inartfully, A.J. was gesturing at something that would have been hard for someone his age to see at the time, which is that the ’00s were a sort of fever dream, a tragic farce built on cheap money and propaganda.

if people still see a monster in Tony, then the monster is themselves: a twisted reflection of a generation whose awakening to the structures that control them came in tandem with a growing aversion to personal accountability in the face of these systems.

. The “leftist ‘Sopranos’ fan” is now such a well-known type that it is rounding the corner to being an object of scorn and mockery online.

One oddity that can’t be ignored in this “Sopranos” resurgence is that, somewhat atypically for a TV fandom, there is an openly left-wing subcurrent within it

Nathaniel Persily, a professor at Stanford Law School, has a neat way of describing the most basic problem in policing Facebook: “At present,” Persily has written, “we do not know even what we do not know” about social media’s effect on the world.

Rashad Robinson, president of the civil rights advocacy group Color of Charge, favored another proposed law, the Algorithmic Justice and Online Platform Transparency Act, which would also require that platforms release data about how they collect and use personal information about, among other demographic categories, users’ race, ethnicity, sex, religion, gender identity, sexual orientation and disability status, in order to show whether their systems are being applied in discriminatory ways.

one idea as “unsexy but important”: Educating the public to resist believing everything they see online.

What we need, then, is something like a society-wide effort to teach people how to process digital information.

In his new book, “Tech Panic: Why We Shouldn’t Fear Facebook and the Future,” Robby Soave, an editor at Reason magazine, argues that the media and lawmakers have become too worked up about the dangers posed by Facebook.He doesn’t disagree that the company’s rise has had some terrible effects, but he worries that some proposals could exacerbate Facebook’s dominance — a point with which I agree.

But Soave will probably get what he wants. As long as there’s wide disagreement among politicians about how to address Facebook’s ills, doing nothing might be the likeliest outcome.

It’s the height of American exceptionalism that we are where we are. I have family in other parts of the world where health-care workers and vulnerable elderly people are begging to get the vaccine. And here, we’re sitting on stockpiles and begging people to take the vaccine.

Do you think verification and mandates could work in the U.S. with our notions of freedom, individual liberty?

I think we need to reframe freedom here, right? I don’t agree with the statement that some people have been putting out about vaccines, that this is just about personal choice. You can say that maybe eating unhealthy food is your personal choice. But in this case, nobody should have the right to carry an infectious disease that is able to endanger others and potentially kill them. I mean, I’ve got two little kids. I’m very upset thinking about how there are other people who are choosing not to be vaccinated. And as a result, they are choosing to endanger our children. I’m sure they’re not trying to do this intentionally, but that is the end result.

I hope that people see that by not being vaccinated, they’re actually impeding societal progress too. They’re making it harder for kids to get back in school. They’re making it harder for the economy to come back. And why are we allowed to make that kind of personal choice when we do not allow people to make the personal choice to go drunk driving?

How much do you worry about hesitancy, not just around the vaccine, but mistrust of science and mistrust of public health even?

I worry about this a lot. You’ve seen what happened in Tennessee with the vaccine director being fired for trying to promote covid vaccines to adolescents. And even more disturbing, I think is that now, Tennessee health officials are being prohibited from promoting vaccines to children. Not just covid vaccines, but all other childhood immunizations. I mean, public health is now under attack in a way that it has not been before.

Dole announced in February 2021 that he’d been diagnosed with stage 4 lung cancer. During his 36-year career on Capitol Hill, Dole became one of the most influential legislators and party leaders in the Senate

Today’s accessible government offices and national parks, sidewalk ramps and the sign-language interpreters at official local events are just some of the more visible hallmarks of his legacy and that of the fellow lawmakers he rounded up for that sweeping civil rights legislation 30 years ago.

Long gone from Kansas, Dole made his life in the capital, at the center of power and then in its shadow upon his retirement, living all the while at the storied Watergate complex.

He tried three times to become president. The last was in 1996, when he won the Republican nomination only to see President Bill Clinton reelected.

He sought his party’s presidential nomination in 1980 and 1988 and was the 1976 GOP vice presidential candidate on the losing ticket with President Gerald Ford.

Dole could be merciless with his rivals, whether Democrat or Republican.

But when Bush died in December 2018, old rivalries were forgotten as Dole appeared before Bush’s casket in the Capitol Rotunda. As an aide lifted him from his wheelchair, Dole slowly steadied himself and saluted his one-time nemesis with his left hand, his chin quivering.

For all of his bare-knuckle ways, he was a deep believer in the Senate as an institution and commanded respect and even affection from many Democrats. Just days after Dole announced his dire cancer diagnosis, President Joe Biden visited him at his home to wish him well. The White House said the two were close friends from their days in the Senate.

Biden ordered that U.S. flags be flown at half-staff at the White House and all public buildings and grounds until sunset Thursday.

He served as a committee chairman, majority leader and minority leader in the Senate during the 1980s and ’90s. Altogether, he was the Republicans’ leader in the Senate for nearly 11½ years, a record until Kentucky Sen. Mitch McConnell broke it in 2018.

After Republicans won Senate control, Dole became chairman of the tax-writing Finance Committee and won acclaim from deficit hawks and others for his handling of a 1982 tax bill, in which he persuaded Ronald Reagan’s White House to go along with increasing revenues by $100 billion to ease the federal budget deficit.

Relegated to private life, Dole became an elder statesman who helped Clinton get a chemical-weapons treaty passed.

He also tended his wife’s political ambitions. Elizabeth Dole ran unsuccessfully for the Republican presidential nomination in 2000, then served a term as senator from North Carolina.

With so many needs met, economists estimate China now has to invest about $9 to produce each dollar of GDP growth, up from less than $5 a decade ago, and a little over $3 in the 1990s.

Returns on assets by private firms have declined to 3.9% from 9.3% five years ago, according to Bert Hofman, head of the National University of Singapore’s East Asian Institute. State companies’ returns have retreated to 2.8% from 4.3%.

China’s labor force, meanwhile, is shrinking, and productivity growth is slowing. From the 1980s to the early 2000s, productivity gains contributed about a third of China’s GDP growth, Hofman’s analysis shows. That ratio has declined to less than one sixth in the past decade.

Changing that would require China’s government to undertake measures aimed at encouraging people to spend more and save less. That could include expanding China’s relatively meager social safety net with greater health and unemployment benefits.

Much of the debt was incurred by cities. Limited by Beijing in their ability to borrow directly to fund projects, they turned to off-balance sheet financing vehicles whose debts are expected to reach more than $9 trillion this year,

only about 20% of financing firms used by local governments to fund projects have enough cash reserves to meet their short-term debt obligations, including bonds owned by domestic and foreign investors.

The most obvious solution, economists say, would be for China to shift toward promoting consumer spending and service industries, which would help create a more balanced economy

Household consumption makes up only about 38% of GDP in China, relatively unchanged in recent years, compared with around 68% in the U.S.,

The solution for many parts of the country has been to keep borrowing and building. Total debt, including that held by various levels of government and state-owned companies, climbed to nearly 300% of China’s GDP as of 2022, surpassing U.S. levels and up from less than 200% in 201

i and some of his lieutenants remain suspicious of U.S.-style consumption, which they see as wasteful at a time when China’s focus should be on bolstering its industrial capabilities and girding for potential conflict with the West, people with knowledge of Beijing’

The leadership also worries that empowering individuals to make more decisions over how they spend their money could undermine state authority, without generating the kind of growth Beijing desires.

A plan announced in late July to promote consumption was criticized by economists both in and outside China for lacking details. It suggested promoting sports and cultural events, and pushed for building more convenience stores in rural areas.

Instead, guided by a desire to strengthen political control, Xi’s leadership has doubled down on state intervention to make China an even bigger industrial power, strong in government-favored industries such as semiconductors, EVs and AI.

While foreign experts don’t doubt China can make headway in these areas, they alone aren’t enough to lift up the entire economy or create enough jobs for the millions of college graduate

a speech made by Xi six months earlier to senior officials, in which the leader emphasized the importance of focusing on long-term goals instead of pursuing Western-style material wealth. “We must maintain historic patience and insist on making steady, step-by-step progress,” Xi said in the speech. 

These high-risk areas were where the department sent police cars to sit with their emergency lights on or where 10-officer crime-response teams were dispatched.

This approach can be polarizing, given that hot spots tend to be in communities of color. But statistics suggest it is working. Of the nation’s largest cities, Dallas appears to be the only one to buck the trend of rising crime; in each of the past two years, statistics for murders, rapes and aggravated assaults have gone down.

The oldest of the books of the Hebrew Bible date to roughly 3,000 years ago; the pyramids of Egypt go back about 5,000 years. These were not prehumans or near relatives. They were like us: complex, organized, alive to meaning and living at a time beyond reckoning.

Ruth Tringham of the University of California, Berkeley, who has devoted years to humanizing the remnants of this city of the dim past by focusing on one skeleton, of a woman she has dubbed Dido. Dido replastered her walls regularly, kept her home swept clean, covered the floor in reed mats and decorated the place with art: clay figures of animals and stylized human females. In other words: much like us.

Catalhoyuk was founded by pioneers of urban living. “When the earliest construction began,” Newitz writes, “many people coming to live at Catalhoyuk were only a generation or two removed from nomadism.” It was brand-new, this fixed settlement thing, but it proved remarkably successful. By the time Dido was born, the city was about 600 years old

A thousand years ago, meanwhile, East St. Louis, Ill., was the site of an urban sanctuary that archaeologists today call Cahokia. With a population of 30,000, it was larger than Paris was at the time. Like Paris, with its Eiffel Tower and Notre-Dame, it had distinguishing physical landmarks in the form of black earthen pyramids. It sprawled across both sides of the Mississippi River, beckoning visitors from all over the present-day Southern United States.

Cahokia seems to have been a place of spiritual pilgrimage, which drew diverse groups of Native American peoples, who spoke different languages and worshiped in various ways but came to share a reverence for this city and its ceremonial customs, which included human sacrifice. Its multiethnic, year-round population apparently serviced the religious pilgrims and, in the off-season, went about their own affairs.

Cahokia died not as a result of sudden catastrophe, like Pompeii, but seemingly because it lost its spiritual significance over time. Its people didn’t perish. The pilgrims just stopped coming; the local residents merged with other tribes. There is linguistic and other evidence that the Sioux are their descendants.

Newitz devotes space to debunking the popular notion that civilizations of the past “collapse” and become “lost,” pointing instead to indications of gradual change.

The operative lesson from the past, at least from this curated offering of former metropolises, seems to be that human culture is a plastic thing. Rather than lamenting the fragility of our current urban structures, we might do better figuring out how to bend and shape society for the future.

the effect of reading “Four Lost Cities” was more meditative. This is a long, long, long ride we are on. Much is beyond our control. Humanity trundles on.

this is like if Russell Moore came out and said that, on the whole, Christianity turns out to be a bad thing. It’s that big of a deal.

Thompson’s case centers around constraints and supply, particularly as they apply to content creation.

In the pre-internet days, creating and distributing content was relatively expensive, which placed content publishers—be they newspapers, or TV stations, or movie studios—high on the value chain.

The internet reduced distribution costs to zero and this shifted value away from publishers and over to aggregators: Suddenly it was more important to aggregate an audience—a la Google and Facebook—than to be a content creator.

Hellscape

What has alarmed Thompson is that AI has now reduced the cost of creating content to zero.

what does the world look like when both the creation and distribution of content are zero?

We’re headed to a place where content is artificially created and distributed in such a way as to be tailored to a given user’s preferences. Which will be the equivalent of living in a hall of mirrors.

At the other end of the spectrum, independent journalists should be okay. A lone reporter running a focused Substack who only needs four digits’ worth of subscribers to sustain them.

What does that mean for news? Nothing good.

It doesn’t really make sense to talk about “news media” because there are fundamental differences between publication models that are driven by scale.

So the challenges the New York Times face will be different than the challenges that NPR or your local paper face.

Two big takeaways:

(1) Ad-supported publications will not survive

Zero-cost for content creation combined with zero-cost distribution means an infinite supply of content. The more content you have, the more ad space exists—the lower ad prices go.

Actually, some ad-supported publications will survive. They just won’t be news. What will survive will be content mills that exist to serve ads specifically matched to targeted audiences.

(2) Size is determinative.

The New York Times has a moat by dint of its size. It will see the utility of its soft “news” sections decline in value, because AI is going to be better at creating cooking and style content than breaking hard news. But still, the NYT will be okay because it has pivoted hard into being a subscription-based service over the last decade.

Audiences were valuable; content was commoditized.

But everything in between? That’s a crapshoot.

Technology writers sometimes talk about the contrast between “builders” and “conservers” — roughly speaking, between those who are most animated by what we stand to gain from technology and those animated by what we stand to lose.

in our moment the builder and conserver types are proving quite mercurial. On issues ranging from Big Tech to medicine, human enhancement to technologies of governance, the politics of technology are in upheaval.

Dispositions are supposed to be basically fixed. So who would have thought that deep blue cities that yesterday were hotbeds of vaccine skepticism would today become pioneers of vaccine passports? Or that outlets that yesterday reported on science and tech developments in reverent tones would today make it their mission to unmask “tech bros”?

One way to understand this churn is that the builder and the conserver types each speak to real, contrasting features within human nature. Another way is that these types each pick out real, contrasting features of technology. Focusing strictly on one set of features or the other eventually becomes unstable, forcing the other back into view.

First, Israel is facing threats from a set of enemies who combine medieval theocratic worldviews with 21st century weaponry — and are no longer organized as small bands of militiamen, but as modern armies with brigades, battalions, cyber capabilities, long-range rockets, drones and technical support.

my third, deep concern.

But Israel’s war against Hamas in Gaza entails urban, house-to-house fighting that creates thousands of civilian casualties — innocent men, women and children

But President Biden can only sustainably generate the support Israel needs if Israel is ready to engage in some kind of a wartime diplomatic initiative directed at the Palestinians in the West Bank — and hopefully in a post-Hamas Gaza — that indicates Israel will discuss some kind of two-state solutions if Palestinian officials can get their political house unified and in order.

The second danger I see is that the only conceivable way that Israel can generate the legitimacy, resources, time and allies to fight such a difficult war with so many enemies is if it has unwavering partners abroad, led by the United States.

Netanyahu’s message to the world remains, in effect: “Help us defeat Hamas in Gaza, while we work to expand settlements, annex the West Bank and build a Jewish supremacist state there.”

Worse, I am stunned at the degree to which that leader, Prime Minister Benjamin Netanyahu, continues to put the interests of holding on to the support of his far-right base

Israel has the worst leader in its history, maybe in all of Jewish history — who has no will or ability to produce such an initiative.

This kind of chilling exuberance — Israel was built so that such a thing could never happen — explains the homemade sign I saw on a sidewalk while driving through the French Hill Jewish neighborhood of Jerusalem the other day: “It’s either us or them.’’

After being slammed by the public for digitally stabbing his army and intelligence chiefs in the back in the middle of a war, Netanyahu published a new tweet. “I was wrong,” he wrote, adding that “the things I said following the press conference should not have been said, and I apologize for that. I fully support the heads of [Israel’s] security services.”

As a result, there is a conviction in the army that they must demonstrate to the entire neighborhood — to Hezbollah in Lebanon, to the Houthis in Yemen, to the Islamic militias in Iraq to the Hamas and other fighters in the West Bank — that they will stop at nothing to re-establish the security of their borders

it wants to show that no one can out-crazy Israel to drive them from this region — even if the Israeli military has to defy the U.S. and even if they do not have any solid plan for governing Gaza the morning after the war.

“Israel cannot accept such an active threat on its borders. The whole idea of people living side by side in the Middle East was jeopardized by Hamas.”

This conflict is now back to its most biblical and primordial roots. This seems to be a time of eyes for eyes and teeth for teeth. The morning-after policy thinking will have to wait for the mourning after.

So, Netanyahu is saying that seven million Jews are going to indefinitely control the lives of five million Palestinians in the West Bank and Gaza

while offering them no political horizon, nothing, by way of statehood one day on any demilitarized conditions.

Early on the morning of Oct. 29, as the Israeli Army was just moving into Gaza, Netanyahu tweeted and then deleted a social media post in which he blamed Israel’s defense and intelligence establishment for failing to anticipate Hamas’s surprise attack.

The euphoric rampage of Oct. 7 that killed some 1,400 soldiers and civilians has not only hardened Israeli hearts toward the suffering of Gaza civilians. It has also inflicted a deep sense of humiliation and guilt on the Israeli Army and defense establishment, for having failed in their most basic mission of protecting the country’s borders.

the damage was done. How much do you suppose those military leaders trust what Netanyahu will say if the Gaza campaign stalls? What real leader would behave that way at the start of a war of survival?

Netanyahu and his far-right zealots have taken Israel on multiple flights of fancy in the last year: dividing the country and the army over the fraudulent judicial reform, bankrupting its future with massive investments in religious schools that teach no math and in West Bank Jewish settlements that teach no pluralism — while building up Hamas, which would never be a partner for peace, and tearing down the Palestinian Authority, the only possible partner for peace.

“When you go to the front, you are overwhelmed by the power of what we lost.”

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