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In late February, there were just a few dozen known cases in the United States, most of them linked to travel. But by summer, the virus had torn through every state, infecting more people than the combined populations of Connecticut and Oklahoma. And in the fall, the national death toll exceeded 230,000, more than the population of Boise, Idaho.

American life has been fundamentally reordered because of the virus. Concerts, parades and high school football games continue to be called off. Countless people have found themselves jobless and struggling to afford housing. Many schools and colleges have held few or no in-person classes this fall. More than 214,000 cases have been linked to colleges and universities over the course of the pandemic. Thousands more cases have been identified in elementary, middle and high schools.

The Times’s data collection for this page is based on reports from state and local health agencies, a process that is unchanged by the Trump administration's requirement that hospitals bypass the Centers for Disease Control and Prevention and send all patient information to a central database in Washington.

The Northeast experienced the worst this spring, as temporary morgues were deployed in New York City. Over the summer, cases spiked across the Sun Belt, prompting many states to tighten restrictions just weeks after reopening. By fall, the virus was filling rural hospitals in the Midwest and West as it devastated communities that had for months avoided the pandemic’s worst.

In Cook County, Ill., which includes Chicago, more than 5,400 people have died. In Los Angeles County, Calif., more than 300,000 people have had the virus, more than in most states. And in New York City, about one of every 352 residents has died.

Coronavirus cases have been reported in more than 23,000 nursing homes and other long-term care facilities, according to data collected by The New York Times from states, counties, the federal government and facilities themselves. More than 581,000 residents and employees of those homes have been infected, and more than 87,000 have died. That means more than 35 percent of deaths from the virus in the United States have been tied to nursing homes and other long-term care facilities.

In July, the Centers for Disease Control and Prevention reported more than 16,000 infections and 86 deaths tied to meat and poultry processing. But those numbers are almost certainly an undercount. Only 28 states provided data to the C.D.C., and many states and food processing companies have refused to provide case totals. Other large outbreaks have emerged on farms, in fruit or vegetable processing facilities and at plants where pet food is made.

with case numbers rising in 44 out of 50 states, the White House, abruptly abandoning its always spotty commitment to federalism, has begun issuing marching orders about opening schools full-time and on schedule, masks and social distancing be damned.

In a classic bit of Trump gaslighting, not only has any hope for increased school funding dematerialized, but the administration is threatening to defund individual school districts if they don’t comply with the order to reopen.

As late summer closes in, there’s a special flavor of rage as parents realize that we’re now being forced to advocate for the very outcome that, a few weeks ago, we were hoping against hope to avoid: keeping school all-online in the fall.

We agree, for example, that we would give up even our current limited interactions with the world — daily dog walks, weekly grocery runs, the occasional masked-and-distanced walk in the park with a friend — if it meant my daughter could attend the school of her dreams in person.

Now it’s clear that on a larger societal plane, this is precisely the deal we have all been making every day in real life, though with the terms reversed. What we chose as a country — or rather, what was chosen for us by an administration seemingly committed to chaos and entropy as governing principles — was to jeopardize the future of public education while prioritizing the opening of restaurants, bars and Home Depots

If we were willing, right now, to collectively agree to give up other activities for a time — according to many epidemiologists, a hard six-week lockdown plus rigorous public masking would do it — we could lower infection rates enough to open schools safely

Prioritizing schools in this way would be a universal public good, even for Americans with no children and no connection to the school system. Set aside the enormous significance of education for children’s enrichment, socialization and health; just getting them out of the house during the week would allow parents to start returning to work full time.

most Americans are concerned that reopening schools for in-person learning will lead to a coronavirus surge, and 35 percent of parents think they shouldn’t open at all.

Another 41 percent of parents think they should only open with “major adjustments.”

Whichever we go with, we will no doubt spend the semester wondering if we harmed either our child’s education or our community’s health by not picking the other option.

Most of us are resigned to go back to the hell of online learning, because the only alternative our leaders have left us with is even worse.

Between 1928 and 1940, Stalin enforced the collectivization of the agricultural sector. Rural peasants were forced to join collective farms. Those that owned land or livestock were stripped of their holdings. Hundreds of thousands of higher-income farmers, called kulaks, were rounded up and executed, their property confiscated.

Stalin eliminated all likely opposition to his leadership by terrorizing Communist Party officials and the public through his secret police.

The Soviet Union by 1948 had installed communist-leaning governments in Eastern European countries that the USSR had liberated from Nazi control during the war. The Americans and British feared the spread of communism into Western Europe and worldwide.

The Cold War power struggle—waged on political, economic and propaganda fronts between the Eastern and Western blocs—would persist in various forms until the fall of the Soviet Union in 1991.

At home, however, Khrushchev initiated a series of political reforms that made Soviet society less repressive. During this period, later known as de-Stalinization, Khrushchev criticized Stalin for arresting and deporting opponents, took steps to raise living conditions, freed many political prisoners, loosened artistic censorship, and closed the Gulag labor camps.

On October 4, 1957, the USSR publicly launched Sputnik 1—the first-ever artificial satellite—into low Earth orbit. The success of Sputnik made Americans fear that the U.S. was falling behind its Cold War rival in technology.

Gorbachev’s glasnost plan called for political openness. It addressed personal restrictions of the Soviet people. Glasnost eliminated remaining traces of Stalinist repression, such as the banning of books (like Boris Pasternak’s Nobel Prize-winning “Dr. Zhivago”) and the much-loathed secret police (though the KGB wouldn’t fully dissolve until the Soviet Union’s collapse in 1991). Newspapers could criticize the government, and parties other than the Communist Party could participate in elections.

During the 1960s and 1970s, the Communist Party elite rapidly gained wealth and power while millions of average Soviet citizens faced starvation. The Soviet Union’s push to industrialize at any cost resulted in frequent shortages of food and consumer goods. Bread lines were common throughout the 1970s and 1980s. Soviet citizens often did not have access to basic needs, such as clothing or shoes.

An unsuccessful coup by Communist Party hard-liners in August 1991 sealed the Soviet Union’s fate by diminishing Gorbachev’s power and propelling democratic forces, led by Boris Yeltsin, to the forefront of Russian politics.

0.6 percent of the world’s population is 47 million people, and 0.6 percent of the American population is 2 million people. The virus remains a major threat.

China had reported 90,294 cases as of Friday and 4,634 deaths, which is a C.F.R. of 5 percent. The United States was very close to that mark. It has had 2,811,447 cases and 129,403 deaths, about 4.6 percent

So far, in most countries, about 20 percent of all confirmed Covid-19 patients become ill enough to need supplemental oxygen or even more advanced hospital care

it is difficult to measure fatality rates during pandemics, especially at the beginning.

In the chaos that ensues when a new virus hits a city hard, thousands of people may die and be buried without ever being tested, and certainly without them all being autopsied.

Normally, once the chaos has subsided, more testing is done and more mild cases are found — and because the denominator of the fraction rises, fatality rates fall. But the results are not always consistent or predictable.

Ten sizable countries, most of them in Western Europe, have tested bigger percentages of their populations than has the United States, according to Worldometer, which gathers statistics. They are Iceland, Denmark, Spain, Portugal, Belgium, Ireland, Italy, Britain, Israel and New Zealand.

But their case fatality rates vary wildly: Iceland’s is less than 1 percent, New Zealand’s and Israel’s are below 2 percent. Belgium, by comparison, is at 16 percent, and Italy and Britain at 14 percent

Those percentages are far higher rates than the 2.5 percent death rate often ascribed to the 1918 flu pandemic.

Whether those patients survive depends on a host of factors, including age, underlying illnesses and the level of medical care available.

Death rates are expected to be lower in countries with younger populations and less obesity, which are often the poorest countries. Conversely, the figures should be higher in countries that lack oxygen tanks, ventilators and dialysis machines, and where many people live far from hospitals. Those are also often the poorest countries.

new evidence that people with Type A blood are more likely to fall deathly ill could change risk calculations. Type A blood is relatively rare in West Africa and South Asia, and very rare among the Indigenous peoples of South America.

it had relied on a mix of data sent in by member countries and by academic groups, and on a meta-analysis done in May by scientists at the University of Wollongong and James Cook University in Australia.

Those researchers looked at 267 studies in more than a dozen countries, and then chose the 25 they considered the most accurate, weighting them for accuracy and averaged the data. They concluded that the global I.F.R. was 0.64 percent.

The 25 studies that the Australian researchers considered the most accurate relied on very different methodologies. One report, for example, was based on diagnostic PCR tests of all passengers and crew aboard the Diamond Princess, the cruise ship that docked in Japan after it was overcome by the coronavirus. Another study drew data from an antibody survey of 38,000 Spaniards, while another included only 1,104 Swedes.

To arrive at the C.D.C.’s new estimate, researchers tested samples from 11,933 people for antibodies to the coronavirus in six regions in the United States. New York City reported 53,803 cases by April 1, but the actual number of infections was 12 times higher — nearly 642,000, the agency estimated.

The global fatality rates could still change. With one or two exceptions, like Iran and Ecuador, the pandemic first struck wealthier countries in Asia, Western Europe and North America where advanced medical care was available.

Many experts fear that infections and deaths will shoot up in the fall as colder weather forces people indoors, where they are more likely to infect one another. Discipline about wearing masks and avoiding breathing on one another will be even more important then.

In each of the eight influenza pandemics to hit the United States since 1763, a relatively mild first wave — no matter what time of year it arrived — was followed by a larger, much more lethal wave a few months later

More than a third of all the people killed by the Spanish flu, which lasted from March 1918 to late 1920, died in the short stretch between September and December 1918 — about six months after a first, relatively mild version of what may have been the same virus broke out in western Kansas.

The slowdown in cases, however, is already prompting action from Spain’s regions, which are responsible for the healthcare systems, Covid-19 vaccination drives and coronavirus restrictions in their territories.

According to the Cantabria health department, the Covid pass is no longer able to achieve the goal of cutting transmission in indoor areas now that the omicron variant has become dominant. This new strain is highly transmissible, and is able to infect both the vaccinated and unvaccinated.

For this same reason, Catalonia is also considering lifting the use of the Covid pass in the region. “We think that it has made an effect: it has raised awareness on the importance of vaccination and was also applied to make the public aware that we were in a pandemic situation,” said Carme Cabezas, the Catalan secretary of Public Health.

For the other Spanish regions with coronavirus restrictions in force, no changes have been announced, but many of the measures that are currently in place will expire soon if not extended.

A prolonged period when more oil has been consumed than pumped has drained tank farms to low levels. Investment in new drilling for new oil has also fallen to multiyear lows, though it is expected to pick up this year. At the same time, demand is expected to grow strongly, reaching prepandemic levels this year.

Energy Aspects forecasts that the deficit will reach just over one million barrels a day this month, or 1 percent of world supplies, and will probably increase later in the year.

A variety of factors are causing production in some countries to fall short, including political turmoil, outmoded regulatory regimes and pressures on international oil companies to rethink their investments so as to bolster profits and reduce carbon emissions. That shift could leave developing countries that depend on oil income out in the cold.

Nigeria’s industry is plagued by damage to infrastructure caused by oil thieves and others, problems that have worsened in recent months, according to the industry.

Kamel al-Harami, a Kuwaiti analyst, said that the domestic industry “does not have the experience and the expertise to deal with old and aged oil fields” but that public opinion is resistant to bringing in international companies.

Following a schedule agreed to in July, the group plans to raise the overall output by 400,000 barrels a day each month, even though they are missing the targets.

Analysts say Saudi officials don’t want to unilaterally increase output and risk busting up the arrangement with other producers that gives them so much control.

A less organized band of knights and commoners known as the “People’s Crusade” set off before the others under the command of a popular preacher known as Peter the Hermit.

Encamping before Jerusalem in June 1099, the Christians forced the besieged city’s governor to surrender by mid-July.

Muslim forces began gaining ground in their own holy war (or jihad) against the Christians, whom they called “Franks.”

News of Edessa’s fall stunned Europe and caused Christian authorities in the West to call for another Crusade

In September 1191, Richard’s forces defeated those of Saladin in the battle of Arsuf, which would be the only true battle of the Third Crusade.

In response, the Crusaders declared war on Constantinople, and the Fourth Crusade ended with the devastating Fall of Constantinople, marked by a bloody conquest, looting and near-destruction of the magnificent Byzantine capital later that year.

Throughout the remainder of the 13th century, a variety of Crusades aimed not so much to topple Muslim forces in the Holy Land but to combat any and all of those seen as enemies of the Christian faith.

A so-called Children’s Crusade took place in 1212 when thousands of young children vowed to march to Jerusalem

From 1248 to 1254, Louis IX of France organized a crusade against Egypt. This battle, known as the Seventh Crusade, was a failure for Louis.

a new dynasty, known as the Mamluks, descended from former slaves of the Islamic Empire, took power in Egypt

In 1291, one of the only remaining Crusader cities, Acre, fell to the Muslim Mamluks.

While the Crusades ultimately resulted in defeat for Europeans and a Muslim victory, many argue that they successfully extended the reach of Christianity and Western civilization.

Trade and transportation also improved throughout Europe as a result of the Crusades.

After the Crusades, there was a heightened interest in travel and learning throughout Europe, which some historians believe may have paved the way for the Renaissance.

the Crusaders were regarded as immoral, bloody and savage.

Even today, some Muslims derisively refer to the West’s involvement in the Middle East as a “crusade.”

In the ’90s, when Ericsson looked into the numbers for the two dozen or so clinics that use his process, he discovered, to his surprise, that couples were requesting more girls than boys, a gap that has persisted, even though Ericsson advertises the method as more effective for producing boys. In some clinics, Ericsson has said, the ratio is now as high as 2 to 1.

A newer method for sperm selection, called MicroSort, is currently completing Food and Drug Administration clinical trials. The girl requests for that method run at about 75 percent.

Even more unsettling for Ericsson, it has become clear that in choosing the sex of the next generation, he is no longer the boss. “It’s the women who are driving all the decisions,”

Now the centuries-old preference for sons is eroding—or even reversing. “Women of our generation want daughters precisely because we like who we are,”

what if equality isn’t the end point? What if modern, postindustrial society is simply better suited to women?

Even Ericsson, the stubborn old goat, can sigh and mark the passing of an era. “Did male dominance exist? Of course it existed. But it seems to be gone now. And the era of the firstborn son is totally gone.”

Ericsson’s extended family is as good an illustration of the rapidly shifting landscape as any other. His 26-year-old granddaughter—“tall, slender, brighter than hell, with a take-no-prisoners personality”—is a biochemist and works on genetic sequencing. His niece studied civil engineering at the University of Southern California. His grandsons, he says, are bright and handsome, but in school “their eyes glaze over. I have to tell ’em: ‘Just don’t screw up and crash your pickup truck and get some girl pregnant and ruin your life.’

Man has been the dominant sex since, well, the dawn of mankind. But for the first time in human history, that is changing—and with shocking speed. Cultural and economic changes always reinforce each other

And the global economy is evolving in a way that is eroding the historical preference for male children, worldwide

Over several centuries, South Korea, for instance, constructed one of the most rigid patriarchal societies in the world.

As recently as 1985, about half of all women in a national survey said they “must have a son.” That percentage fell slowly until 1991 and then plummeted to just over 15 percent by 2003. Male preference in South Korea “is over,” says Monica Das Gupta, a demographer and Asia expert at the World Bank. “It happened so fast. It’s hard to believe it, but it is.” The same shift is now beginning in other rapidly industrializing countries such as India and China.

As thinking and communicating have come to eclipse physical strength and stamina as the keys to economic success, those societies that take advantage of the talents of all their adults, not just half of them, have pulled away from the rest. And because geopolitics and global culture are, ultimately, Darwinian, other societies either follow suit or end up marginalized

None of the 30 or so men sitting in a classroom at a downtown Kansas City school have come for voluntary adult enrichment. Having failed to pay their child support, they were given the choice by a judge to go to jail or attend a weekly class on fathering, which to them seemed the better deal.

in the U.S., the world’s most advanced economy, something much more remarkable seems to be happening. American parents are beginning to choose to have girls over boys. As they imagine the pride of watching a child grow and develop and succeed as an adult, it is more often a girl that they see in their mind’s eye.

What if the modern, postindustrial economy is simply more congenial to women than to men?

what if men and women were fulfilling not biological imperatives but social roles, based on what was more efficient throughout a long era of human history? What if that era has now come to an end? More to the point, what if the economics of the new era are better suited to women?

Once you open your eyes to this possibility, the evidence is all around you. It can be found, most immediately, in the wreckage of the Great Recession, in which three-quarters of the 8 million jobs lost were lost by men.

The recession merely revealed—and accelerated—a profound economic shift that has been going on for at least 30 years

Earlier this year, for the first time in American history, the balance of the workforce tipped toward women, who now hold a majority of the nation’s job

With few exceptions, the greater the power of women, the greater the country’s economic success

Women dominate today’s colleges and professional schools—for every two men who will receive a B.A. this year, three women will do the same. Of the 15 job categories projected to grow the most in the next decade in the U.S., all but two are occupied primarily by women

Indeed, the U.S. economy is in some ways becoming a kind of traveling sisterhood: upper-class women leave home and enter the workforce, creating domestic jobs for other women to fill.

The postindustrial economy is indifferent to men’s size and strength. The attributes that are most valuable today—social intelligence, open communication, the ability to sit still and focus—are, at a minimum, not predominantly male. In fact, the opposite may be true

Yes, women still do most of the child care. And yes, the upper reaches of society are still dominated by men. But given the power of the forces pushing at the economy, this setup feels like the last gasp of a dying age rather than the permanent establishment

In his final book, The Bachelors’ Ball, published in 2007, the sociologist Pierre Bourdieu describes the changing gender dynamics of Béarn, the region in southwestern France where he grew up. The eldest sons once held the privileges of patrimonial loyalty and filial inheritance in Béarn. But over the decades, changing economic forces turned those privileges into curses. Although the land no longer produced the impressive income it once had, the men felt obligated to tend it. Meanwhile, modern women shunned farm life, lured away by jobs and adventure in the city

The role reversal that’s under way between American men and women shows up most obviously and painfully in the working class

The working class, which has long defined our notions of masculinity, is slowly turning into a matriarchy, with men increasingly absent from the home and women making all the decisions

“Let’s see,” he continues, reading from a worksheet. What are the four kinds of paternal authority? Moral, emotional, social, and physical. “But you ain’t none of those in that house. All you are is a paycheck, and now you ain’t even that. And if you try to exercise your authority, she’ll call 911. How does that make you feel? You’re supposed to be the authority, and she says, ‘Get out of the house, bitch.’ She’s calling you ‘bitch’!”

Just about the only professions in which women still make up a relatively small minority of newly minted workers are engineering and those calling on a hard-science background, and even in those areas, women have made strong gains since the 1970s.

“Who’s doing what?” he asks them. “What is our role? Everyone’s telling us we’re supposed to be the head of a nuclear family, so you feel like you got robbed. It’s toxic, and poisonous, and it’s setting us up for failure.” He writes on the board: $85,000. “This is her salary.” Then: $12,000. “This is your salary. Who’s the damn man? Who’s the man now?” A murmur rises. “That’s right. She’s the man.”

In 1950, roughly one in 20 men of prime working age, like Henderson, was not working; today that ratio is about one in five, the highest ever recorded.

Men dominate just two of the 15 job categories projected to grow the most over the next decade: janitor and computer engineer. Women have everything else—nursing, home health assistance, child care, food preparation

Many of the new jobs, says Heather Boushey of the Center for American Progress, “replace the things that women used to do in the home for free.” None is especially high-paying. But the steady accumulation of these jobs adds up to an economy that, for the working class, has become more amenable to women than to men.

The list of growing jobs is heavy on nurturing professions, in which women, ironically, seem to benefit from old stereotypes and habits.

The men in that room, almost without exception, were casualties of the end of the manufacturing era. Most of them had continued to work with their hands even as demand for manual labor was declining.

Many professions that started out as the province of men are now filled mostly with women—secretary and teacher come to mind. Yet I’m not aware of any that have gone the opposite way. Nursing schools have tried hard to recruit men in the past few years, with minimal success. Teaching schools, eager to recruit male role models, are having a similarly hard time

The range of acceptable masculine roles has changed comparatively little, and has perhaps even narrowed as men have shied away from some careers women have entered. As Jessica Grose wrote in Slate, men seem “fixed in cultural aspic.” And with each passing day, they lag further behind.

women are also starting to dominate middle management, and a surprising number of professional careers as well. According to the Bureau of Labor Statistics, women now hold 51.4 percent of managerial and professional jobs—up from 26.1 percent in 1980

About a third of America’s physicians are now women, as are 45 percent of associates in law firms—and both those percentages are rising fast.

When we look back on this period, argues Jamie Ladge, a business professor at Northeastern University, we will see it as a “turning point for women in the workforce.”

A white-collar economy values raw intellectual horsepower, which men and women have in equal amounts. It also requires communication skills and social intelligence, areas in which women, according to many studies, have a slight edge. Perhaps most important—for better or worse—it increasingly requires formal education credentials, which women are more prone to acquire,

The men are black and white, their ages ranging from about 20 to 40. A couple look like they might have spent a night or two on the streets, but the rest look like they work, or used to. Now they have put down their sodas, and El-Scari has their attention, so he gets a little more philosophical

Companies began moving out of the city in search not only of lower rent but also of the “best educated, most conscientious, most stable workers.” They found their brightest prospects among “underemployed females living in middle-class communities on the fringe of the old urban areas.” As Garreau chronicles the rise of suburban office parks, he places special emphasis on 1978, the peak year for women entering the workforce. When brawn was off the list of job requirements, women often measured up better than men. They were smart, dutiful, and, as long as employers could make the jobs more convenient for them, more reliable

Near the top of the jobs pyramid, of course, the upward march of women stalls. Prominent female CEOs, past and present, are so rare that they count as minor celebrities,

Only 3 percent of Fortune 500 CEOs are women, and the number has never risen much above that.

What are these talents? Once it was thought that leaders should be aggressive and competitive, and that men are naturally more of both. But psychological research has complicated this picture. In lab studies that simulate negotiations, men and women are just about equally assertive and competitive, with slight variations. Men tend to assert themselves in a controlling manner, while women tend to take into account the rights of others, but both styles are equally effective,

Researchers have started looking into the relationship between testosterone and excessive risk, and wondering if groups of men, in some basic hormonal way, spur each other to make reckless decisions. The picture emerging is a mirror image of the traditional gender map: men and markets on the side of the irrational and overemotional, and women on the side of the cool and levelheaded.

the perception of the ideal business leader is starting to shift. The old model of command and control, with one leader holding all the decision-making power, is considered hidebound. The new model is sometimes called “post-heroic,” or “transformational”

he aim is to behave like a good coach, and channel your charisma to motivate others to be hardworking and creative. The model is not explicitly defined as feminist, but it echoes literature about male-female differences

Most important, women earn almost 60 percent of all bachelor’s degrees—the minimum requirement, in most cases, for an affluent life.

Firms that had women in top positions performed better, and this was especially true if the firm pursued what the researchers called an “innovation intensive strategy,” in which, they argued, “creativity and collaboration may be especially important”

he association is clear: innovative, successful firms are the ones that promote women. The same Columbia-Maryland study ranked America’s industries by the proportion of firms that employed female executives, and the bottom of the list reads like the ghosts of the economy past: shipbuilding, real estate, coal, steelworks, machinery.

To see the future—of the workforce, the economy, and the culture—you need to spend some time at America’s colleges and professional schools

emographically, we can see with absolute clarity that in the coming decades the middle class will be dominated by women.

Women now earn 60 percent of master’s degrees, about half of all law and medical degrees, and 42 percent of all M.B.A.s

“We never explicitly say, ‘Develop your feminine side,’ but it’s clear that’s what we’re advocating,” s

n a stark reversal since the 1970s, men are now more likely than women to hold only a high-school diploma.

ne would think that if men were acting in a rational way, they would be getting the education they need to get along out there,” says Tom Mortenson, a senior scholar at the Pell Institute for the Study of Opportunity in Higher Education. “But they are just failing to adapt.”

I visited a few schools around Kansas City to get a feel for the gender dynamics of higher education. I started at the downtown campus of Metropolitan Community College. Metropolitan is the kind of place where people go to learn practical job skills and keep current with the changing economy, and as in most community colleges these days, men were conspicuously absent.

the tidal wave of women continues to wash through the school—they now make up about 70 percent of its students. They come to train to be nurses and teachers

As for the men? Well, little has changed. “I recall one guy who was really smart,” one of the school’s counselors told me. “But he was reading at a sixth-grade level and felt embarrassed in front of the women. He had to hide his books from his friends, who would tease him when he studied. Then came the excuses. ‘It’s spring, gotta play ball.’ ‘It’s winter, too cold.’ He didn’t make it.”

“The economy isn’t as friendly to men as it once was,” says Jacqueline King, of the American Council on Education. “You would think men and women would go to these colleges at the same rate.” But they don’t.

Men, it turned out, had a harder time committing to school, even when they desperately needed to retool. They tended to start out behind academically, and many felt intimidated by the schoolwork. They reported feeling isolated and were much worse at seeking out fellow students, study groups, or counselors to help them adjust.

Mothers going back to school described themselves as good role models for their children. Fathers worried that they were abrogating their responsibilities as breadwinner.

it began showing up not just in community and liberal-arts colleges but in the flagship public universities—the UCs and the SUNYs and the UNCs.

Guys high-five each other when they get a C, while girls beat themselves up over a B-minus. Guys play video games in each other’s rooms, while girls crowd the study hall. Girls get their degrees with no drama, while guys seem always in danger of drifting away.

realized how much the basic expectations for men and women had shifted. Many of the women’s mothers had established their careers later in life, sometimes after a divorce, and they had urged their daughters to get to their own careers more quickly. They would be a campus of Tracy Flicks, except that they seemed neither especially brittle nor secretly falling apart.

Among traditional college students from the highest-income families, the gender gap pretty much disappears. But the story is not so simple. Wealthier students tend to go to elite private schools, and elite private schools live by their own rules.

Quietly, they’ve been opening up a new frontier in affirmative action, with boys playing the role of the underprivileged applicants needing an extra boost

among selective liberal-arts schools, being male raises the chance of college acceptance by 6.5 to 9 percentage points

the U.S. Commission on Civil Rights has voted to investigate what some academics have described as the “open secret” that private schools “are discriminating in admissions in order to maintain what they regard as an appropriate gender balance.”

To avoid crossing the dreaded 60 percent threshold, admissions officers have created a language to explain away the boys’ deficits: “Brain hasn’t kicked in yet.” “Slow to cook.” “Hasn’t quite peaked.” “Holistic picture.”

Clearly, some percentage of boys are just temperamentally unsuited to college, at least at age 18 or 20, but without it, they have a harder time finding their place these days

“Forty years ago, 30 years ago, if you were one of the fairly constant fraction of boys who wasn’t ready to learn in high school, there were ways for you to enter the mainstream economy,” says Henry Farber, an economist at Princeton. “When you woke up, there were jobs. There were good industrial jobs, so you could have a good industrial, blue-collar career. Now those jobs are gone.”

the disparities start before college. Throughout the ’90s, various authors and researchers agonized over why boys seemed to be failing at every level of education, from elementary school on up

identified various culprits: a misguided feminism that treated normal boys as incipient harassers (Christina Hoff Sommers); different brain chemistry (Michael Gurian); a demanding, verbally focused curriculum that ignored boys’ interests (Richard Whitmire)

t’s not all that clear that boys have become more dysfunctional—or have changed in any way. What’s clear is that schools, like the economy, now value the self-control, focus, and verbal aptitude that seem to come more easily to young girls.

movement is growing for more all-boys schools and classes, and for respecting the individual learning styles of boys

In their desperation to reach out to boys, some colleges have formed football teams and started engineering programs.

allowing generations of boys to grow up feeling rootless and obsolete is not a recipe for a peaceful future. Men have few natural support groups and little access to social welfare; the men’s-rights groups that do exist in the U.S. are taking on an angry, antiwoman edge.

Marriages fall apart or never happen at all, and children are raised with no fathers. Far from being celebrated, women’s rising power is perceived as a threat.

his is the first time that the cohort of Americans ages 30 to 44 has more college-educated women than college-educated men, and the effects are upsetting the traditional Cleaver-family dynamics. In 1970, women contributed 2 to 6 percent of the family income. Now the typical working wife brings home 42.2 percent, and four in 10 mothers—many of them single mothers—are the primary breadwinners in their familie

ncreasing numbers of women—unable to find men with a similar income and education—are forgoing marriage altogether. In 1970, 84 percent of women ages 30 to 44 were married; now 60 percent are.

or all the hand-wringing over the lonely spinster, the real loser in society—the only one to have made just slight financial gains since the 1970s—is the single man, whether poor or rich, college-educated or not. Hens rejoice; it’s the bachelor party that’s over.

The sociologist Kathryn Edin spent five years talking with low-income mothers in the inner suburbs of Philadelphia. Many of these neighborhoods, she found, had turned into matriarchies, with women making all the decisions and dictating what the men should and should not do. “I think something feminists have missed,” Edin told me, “is how much power women have” when they’re not bound by marriage

he women, she explained, “make every important decision”—whether to have a baby, how to raise it, where to live. “It’s definitely ‘my way or the highway,’

Thirty years ago, cultural norms were such that the fathers might have said, ‘Great, catch me if you can.’ Now they are desperate to father, but they are pessimistic about whether they can meet her expectations.” The women don’t want them as husbands, and they have no steady income to provide. So what do they have?

Nothing,” Edin says. “They have nothing. The men were just annihilated in the recession of the ’90s, and things never got better. Now it’s just awful.”

The phenomenon of children being born to unmarried parents “has spread to barrios and trailer parks and rural areas and small towns,” Edin says, and it is creeping up the class ladder. After staying steady for a while, the portion of American children born to unmarried parents jumped to 40 percent in the past few years.

Many of their mothers are struggling financially; the most successful are working and going to school and hustling to feed the children, and then falling asleep in the elevator of the community college.

Still, they are in charge. “The family changes over the past four decades have been bad for men and bad for kids, but it’s not clear they are bad for women,”

Over the years, researchers have proposed different theories to explain the erosion of marriage in the lower classes: the rise of welfare, or the disappearance of work and thus of marriageable men

the most compelling theory is that marriage has disappeared because women are setting the terms—and setting them too high for the men around them to reach.

The whole country’s future could look much as the present does for many lower-class African Americans: the mothers pull themselves up, but the men don’t follow. First-generation college-educated white women may join their black counterparts in a new kind of middle class, where marriage is increasingly rare.

Japan is in a national panic over the rise of the “herbivores,” the cohort of young men who are rejecting the hard-drinking salaryman life of their fathers and are instead gardening, organizing dessert parties, acting cartoonishly feminine, and declining to have sex. The generational young-women counterparts are known in Japan as the “carnivores,” or sometimes the “hunters.”

American pop culture keeps producing endless variations on the omega male, who ranks even below the beta in the wolf pack.

At the same time, a new kind of alpha female has appeared, stirring up anxiety and, occasionally, fear. The cougar trope started out as a joke about desperate older women. Now it’s gone mainstream, even in Hollywood,

the more women dominate, the more they behave, fittingly, like the dominant sex. Rates of violence committed by middle-aged women have skyrocketed since the 1980

A high vaccination rate was especially important in Florida, which trails only Maine in the share of residents 65 and older. By the end of July, Florida had vaccinated about 60 percent of adults, just shy of the national average

Had it reached a vaccination rate of 74 percent — the average for five New England states at the time — it could have prevented more than 16,000 deaths and more than 61,000 hospitalizations that summer, according to a study published in the medical journal The Lancet.

in Florida, unlike the nation as a whole — and states like New York and California that Mr. DeSantis likes to single out — most people who died from Covid died after vaccines became available to all adults, not before.

Mr. DeSantis and his aides have said that his opposition was to mandates, not to the vaccinations themselves. They say the governor only questioned the efficacy of the shots once it became evident that they did not necessarily prevent infection — which prompted him to criticize experts and the federal government.

The governor had early success in following his instincts. In 2020, the state supplied its nearly 4,000 long-term care homes with Covid tests and isolated Covid patients, avoiding New York’s mistake of releasing Covid patients from hospitals to nursing homes where they infected others. Florida’s death rate in the pandemic’s first year, adjusted for age, was lower than all but 10 other states’.

Florida was also one of only four states to require schools to hold in-person classes in the fall of 2020, a move that Mr. DeSantis has said defied the nation’s public health experts

In fact, Dr. Anthony S. Fauci, a federal infectious disease expert on former President Donald J. Trump’s task force, said repeatedly that summer and fall that schools could open safely with the right precautions. Nonetheless, facing strong opposition from teachers’ unions, nearly three-fourths of the nation’s 100 largest school districts offered only remote learning that fall.

At the same time, though, the governor was embracing more extreme views, including those of Dr. Scott W. Atla

Both he and Dr. Bhattacharya argued that people who were not at risk of severe consequences should not face Covid restrictions. If they were infected, they would develop natural immunity, which would eventually build up in the population and cause the virus to fade away, they said.

Many public health experts were alarmed by this strategy, which was articulated in a document known as the Great Barrington Declaration. They said it would be impossible to ring-fence the vulnerable, or even to clearly communicate to the public who they were. Besides older Americans, as many as 41 million younger adults were considered to be at high risk of severe disease if infected because of underlying medical conditions like obesity.

Dr. Atlas, however, argued that the virus was not dangerous to an overwhelming majority of Americans. Both he and Dr. Bhattacharya said the Covid death rate for everyone under 70 was very low. Dr. Atlas claimed that children had “virtually zero” risk of death.

As of this summer, more than 345,000 Americans under 70 have died of the virus, and more than 3.5 million have been hospitalized

The disease has killed nearly 2,300 children and adolescents, and nearly 200,000 have been hospitalized.

Mr. DeSantis gave him a platform at a series of public events in Florida at the end of the summer of 2020. He would go on to echo Dr. Atlas’s views, sometimes in modified form, throughout the pandemic.

Mr. DeSantis subsequently promoted the shots in 27 counties. Florida offered the vaccine to everyone 65 and older, an eligibility system simpler than an early one recommended by the Centers for Disease Control and Prevention, and adopted by many states, that prioritized essential workers and those over 75.

But his enthusiasm for shots waned fast, tracking the growing hostility toward them among the party’s conservative activists. In late February, when Mr. DeSantis hosted a gathering of such activists for the Conservative Political Action Conference in Orlando, he boasted that Florida was an “oasis of freedom” in a nation led by misguided health authorities.

By the time all adults became eligible for the vaccines in April of that year, Mr. DeSantis was rarely promoting them.

“Some are choosing not to take it, which is fine,” he said in March, at a 100-minute public event on Covid in which he did not once urge people to get vaccinated. In dozens of appearances on Fox News in the first half of 2021, he was carefully neutral about shots, except for those over 65.

“Younger people are just simply at very little risk for this,”

A few months later, he told Fox News that he had concluded early on that Covid “was something that was risky for elderly people,” but that it posed minimal risks for people “who were in reasonably good health, who were, say, under 50.”

The data-driven governor also turned away from Covid case data.

In May 2021, Florida closed its 27 state-run testing centers. The next month, on orders from the governor’s office, the Health Department halted daily reports on infections and deaths, switching to weekly reports that drew less attention.

Both polls and political events showed that Republicans were not as excited as Democrats about the shots. At an Alabama political rally that August, Mr. Trump recommended the vaccine — and was booed. When a reporter asked Mr. DeSantis later that year if he had gotten a booster shot, he responded that he had gotten “the normal shot.”

After the highly contagious Delta variant began spreading in Florida that summer, Mr. DeSantis insisted that his approach had worked. Younger adults were driving the surge but “they’re not getting really sick from it or anything,” he said, adding: “They will develop immunity as a result of those infections.”

But they were getting sick. And vaccinations, which Mr. DeSantis suddenly began recommending again in late July, took weeks to confer protection

With hospitalizations rising, he began a campaign to offer monoclonal antibody treatments — a triage response to the pandemic’s frightening resurgence.

The drug cost vastly more than shots and required more medical staff to administer. Within about six weeks, the state had administered more than 90,000 treatments and probably kept 5,000 people out of the hospital, Dr. Rivkees said.

Mr. DeSantis accused the media in early August of “lying” about Covid patients’ flooding hospitals. Two weeks later, Mary C. Mayhew, head of the Florida Hospital Association, said: “There can be no question that many Florida hospitals are stretched to their absolute limits.”

“Our patients are younger and sicker,” Mr. Smith wrote. Of 17 patients on ventilators in intensive care on Aug. 13, 2021, more than half were younger than 55. Only one was vaccinated.

“People say that the decision about vaccination is a personal one and it doesn’t affect anyone else,” Mr. Smith wrote. “Tell that to the kids who lost their mom.”

When shots became available last year for children under 5, Florida did not preorder them because, Mr. DeSantis said, he did not consider them “appropriate.” Florida’s vaccination rates are well below the national average for children under 5. The state also trails in booster shots.

After Dr. Ladapo issued misleading claims about the risks of Covid shots for young men, the heads of the C.D.C. and the Food and Drug Administration sent a scathing four-page rebuttal. Such misinformation “puts people at risk of death or serious illness,” they said.

While the pandemic waned, leaving more than 80,000 Floridians and 1.13 million Americans dead, the governor continued to push policies that kept him at the vanguard of the anti-vaccine and anti-mandate conversation. A new state law, signed by Mr. DeSantis in May, bans government agencies, businesses and schools from requiring Covid testing, vaccination or mask wearing.

“Everything involving Covid — I think there needs to be major, major accountability,” he said in Iowa this month. “Because if there’s not, if you don’t have a reckoning, they are going to do it again.”

On Tuesday China’s government also announced the GDP had grown 3% in 2022. That figure would mark one of the slowest periods of growth in decades, but was still higher than predicted, prompting some scepticism among analysts given the incredibly stringent zero-Covid restrictions in place during the fourth quarter.

Yi Fuxian, an obstetrics and gynaecology researcher at the University of Wisconsin-Madison and expert on China’s population changes, said the decline in population was occurring almost a decade earlier than the country’s government and the United Nations had projected.

“Meaning that China’s real demographic crisis is beyond imagination and that all of China’s past economic, social, defence, and foreign policies were based on faulty demographic data,” Yi said on Twitter

“China’s demographic and economic outlook is much bleaker than expected. China will have to undergo a strategic contraction and adjust its social, economic, defence, and foreign policies. China will improve relations with the West.”

In the absence of elections, Communist Party officials in China rise up the ranks based on how well they deliver on the party’s priorities, at least in theory. For years, the top priority was economic growth

Local officials plowed money into the highways, ports and power plants that manufacturers needed, turning China into the world’s factory.

Under Mr. Xi, government priorities have shifted toward self-sufficiency and the use of industrial robots, something that Chinese leaders believe is critical to escaping the middle-income trap, in which a country can no longer compete in low-wage manufacturing because of rising wages but has not yet made the leap to the value-added products of high-income countries.

some Chinese companies purchased robots that don’t work well and exaggerated their success to get government subsidies and curry favor with politicians. Directives from party officials with little expertise in robotics fetishize machines beyond their actual usefulness.

Those unskilled laborers — who will increasingly be replaced by robots, according to China’s grand strategy — present an economic challenge and a threat to political stability

What many Chinese businesses wanted most, she said, was “invisible infrastructure”: a predictable judicial system, fair access to bank credit and land, and regulations that are applied without regard to political connections

Her findings, reported in detail in “The Gilded Cage: Techno-State Capitalism in China,” which will be published next fall, suggest that Beijing’s pronouncements about amazing technological advancement should be viewed with a touch of skepticism.

Mr. Xi had a privileged childhood as the son of a top Communist Party official. But the Cultural Revolution shattered that sheltered life; he was sent to a remote village for seven years, where he did hard labor and slept in a hillside cave home. As a result, he can claim a familiarity with rural people and rural problems that few world leaders can even imagine.

One of Mr. Xi’s most celebrated campaigns has been a vow to stamp out extreme poverty, a tacit acknowledgment that China’s economic miracle has left hundreds of millions of rural farmers behind

Some corporate managers complained that government subsidies often flowed to politically connected firms and were wasted, while others grumbled that government directives were unpredictable and ill informed.

Only 30 percent of working Chinese adults have high school diplomas, although 80 percent of young people are getting them now, according to Scott Rozelle, a co-author of “Invisible China: How the Urban-Rural Divide Threatens China’s Rise.”

more than 600 million Chinese people scrape by on the equivalent of $140 per month.

Last year, Mr. Xi declared “complete victory” in eradicating extreme poverty in China, but skepticism about his success abounds. Some experts on China report that local officials gave out cash to rural families — one-time payments that got them temporarily over the poverty line — instead of initiating badly needed structural reforms.

“Rural Chinese in many ways are like the lowest class in a policy-driven caste system,” Mr. Rozelle told me. Nevertheless, even a flawed program to address rural poverty is better than no program at all.

He set out to save his rudderless Communist Party by cracking down on graft and bringing wayward nouveaux riches back into the fold by recruiting them as party members. He ordered chief executives to contribute more toward “common prosperity” and showed what could happen to those who didn’t toe the party line.

Mr. Xi’s crackdown went too far. Increasingly, foreign investors and Chinese entrepreneurs are fleeing. Coupled with a draconian zero-Covid strategy, Mr. Xi’s policies have sent the economy into a tailspin.

More worrisome still is the return of an atmosphere of fear and sycophancy not seen since Chairman Mao’s time. A businessman who was critical of Mr. Xi was sent to prison for 18 years. The era of relative openness to intellectual debate and foreign ideas appears to have come to an end.

id another despot like Mao, have gone out the window so Mr. Xi can have more time in power. Mr. Xi has been called a modern-day emperor, the chairman of everything and the most powerful man in the world

Yuhua Wang, a political scientist at Harvard who is author of the book “The Rise and Fall of Imperial China,” released this month. Mr. Wang studied 2,000 years of Chinese history and discovered, somewhat counterintuitively, that China’s central government has always been the weakest under its longest-serving rulers.

Emperors, he explains, have always stayed in power by weakening the elites who might have overthrown them — the very people who are capable of building a strong and competent government.

“One can argue that he has good intentions,” Mr. Wang told me of Mr. Xi. But the tactics he has used to maintain power — crushing critics, micromanaging businesses, whipping up nationalist fervor and walling China off from the world — may end up weakening China in the end.

it is a local manifestation of a global phenomenon

many more people would be eager to migrate here if we let them. The two phenomena of small boats crossing the Channel and stowaways falling from planes both indicate that some people are eager to come even when we don’t let them, and that lethal danger will not dissuade them from trying to find their way to places as dull and rich and lovely as Sheen.

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.”