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But despite that constant flow of reporting, Trump continued publicly and privately to play down the threat the virus posed to Americans.

Intelligence agencies “have been warning on this since January,” said a U.S. official who had access to intelligence reporting that was disseminated to members of Congress and their staffs as well as to officials in the Trump administration

“Donald Trump may not have been expecting this, but a lot of other people in the government were — they just couldn’t get him to do anything about it,” this official said. “The system was blinking red.”

The warnings from U.S. intelligence agencies increased in volume toward the end of January and into early February, said officials familiar with the reports. By then, a majority of the intelligence reporting included in daily briefing papers and digests from the Office of the Director of National Intelligence and the CIA was about covid-19, said officials who have read the reports.

The surge in warnings coincided with a move by Sen. Richard Burr (R-N.C.) to sell dozens of stocks worth between $628,033 and $1.72 million.

A key task for analysts during disease outbreaks is to determine whether foreign officials are trying to minimize the effects of an outbreak or take steps to hide a public health crisis

At the State Department, personnel had been nervously tracking early reports about the virus. One official noted that it was discussed at a meeting in the third week of January, around the time that cable traffic showed that U.S. diplomats in Wuhan were being brought home on chartered planes — a sign that the public health risk was significant

Inside the White House, Trump’s advisers struggled to get him to take the virus seriously, according to multiple officials with knowledge of meetings among those advisers and with the president.

Azar couldn’t get through to Trump to speak with him about the virus until Jan. 18, according to two senior administration officials. When he reached Trump by phone, the president interjected to ask about vaping and when flavored vaping products would be back on the market

On Jan. 27, White House aides huddled with then-acting chief of staff Mick Mulvaney in his office, trying to get senior officials to pay more attention to the virus

Joe Grogan, the head of the White House Domestic Policy Council, argued that the administration needed to take the virus seriously or it could cost the president his reelection, and that dealing with the virus was likely to dominate life in the United States for many months.

Trump was dismissive because he did not believe that the virus had spread widely throughout the United States.

By early February, Grogan and others worried that there weren’t enough tests to determine the rate of infection, according to people who spoke directly to Grogan

But Trump resisted and continued to assure Americans that the coronavirus would never run rampant as it had in other countries.“I think it’s going to work out fine,” Trump said on Feb. 19. “I think when we get into April, in the warmer weather, that has a very negative effect on that and that type of a virus.”

“The Coronavirus is very much under control in the USA,” Trump tweeted five days later. “Stock Market starting to look very good to me!”

But earlier that month, a senior official in the Department of Health and Human Services delivered a starkly different message to the Senate Intelligence Committee, in a classified briefing that four U.S. officials said covered the coronavirus and its global health implications. The House Intelligence Committee received a similar briefing.

Robert Kadlec, the assistant secretary for preparedness and response — who was joined by intelligence officials, including from the CIA — told committee members that the virus posed a “serious” threat, one of those officials said.

he said that to get ahead of the virus and blunt its effects, Americans would need to take actions that could disrupt their daily lives, the official said. “It was very alarming.”

Trump’s insistence on the contrary seemed to rest in his relationship with China’s President Xi Jingping, whom Trump believed was providing him with reliable information about how the virus was spreading in China, despite reports from intelligence agencies that Chinese officials were not being candid about the true scale of the crisis.

Some of Trump’s advisers told him that Beijing was not providing accurate numbers

Rather than press China to be more forthcoming, Trump publicly praised its response.

“China has been working very hard to contain the Coronavirus,” Trump tweeted Jan. 24. “The United States greatly appreciates their efforts and transparency. It will all work out well. In particular, on behalf of the American People, I want to thank President Xi!”

Trump on Feb. 3 banned foreigners who had been in China in the previous 14 days from entering the United States, a step he often credits for helping to protect Americans against the virus. He has also said publicly that the Chinese weren’t honest about the effects of the virus. But that travel ban wasn’t accompanied by additional significant steps to prepare

As the first cases of infection were confirmed in the United States, Trump continued to insist that the risk to Americans was small.“I think the virus is going to be — it’s going to be fine,” he said on Feb. 10

In recent years, the tobacco industry has joined forces with certain civil rights activists, among them the Rev. Al Sharpton, who according to the California Department of Public Health, visited Black communities in the state, raising fear that a menthol ban would give the police an excuse to stop and frisk more Black individuals. Mr. Sharpton also helped to defeat a ban in New York.

He thinks Democrats are making a huge mistake in the campaign so far – by telling voters who they really are. The main candidates are veering too far left, he thinks, away from the disaffected Trump voters they will have to turn.

to Wilson, Democratic “policy is the enemy”, whether it concerns Medicare for All, gun control or women’s right to choose.

“Guys like me who still work on the Trump side of the fence can always turn it into something that is a millstone around their neck. It’s not even that hard. Elizabeth Warren produces a 600-page healthcare plan and my research geeks can’t find, I don’t know, 30 things in there that I can’t demagogue the hell out of? Because I can. Or the guys that are me now can.”

Away from the coasts and the college towns, Wilson contends, America is still a conservative place. Accordingly, Running Against the Devil contains a lot of what its author calls “tough love”, telling harsh truths and demanding Democrats put party purity aside

“No matter how much they want to talk about choice and reproductive rights, when you go into Catholic communities it is still a burden on them and they don’t have this ability to say, ‘Maybe rural Michigan isn’t the same thing as San Jose, California.’”

Wilson insists Trump’s defeat in the popular vote in 2016 – by nearly 3 million votes to Hillary Clinton – didn’t matter. Nor will it matter if Trump wins in the electoral college again. Them’s the rules, they ain’t changing soon and if a state doesn’t help paint the college blue, no Democrat should visit it for anything other than dollars.

“You’ve got to run where the game is played and fight where the fight is, which is these 15 electoral college swing states, and those states are not as woke and liberal as other parts of the country.”

“This isn’t rocket science. How did we Republicans elect guys in Wisconsin and Vermont and other places in recent years? We did it because we weren’t running them as national Republican figures. We helped elect a Republican governor in Vermont, four times. And you’re thinking, ‘Wow, Vermont, super liberal, how did that happen?’ Well, our guy was out there saying the Bush administration was wrong on climate change.

Asked which Democrat is best suited for the fight, Wilson admits to being impressed by Warren’s willingness to work hard and how she champions the little guy. But he still goes for Joe Biden.

“I think it will be Biden because name ID is very powerful,” he says of the former senator and vice-president. “He is the one candidate who has shown the most ability to contrast with Trump in terms of a broader, bigger picture that isn’t just locked into what’s the hot flavor of Democratic messaging this year.

“He’s talking about that big American sense of unity and reconciliation and saying we’ve got to work with Republicans too.”

“There’s nothing in Joe Biden that scans as evil or dark or weird or out of touch,” Wilson says. “He can be a little goofy but that’s not bad, not the worst thing in the world right now

“I think neither Warren nor Sanders and certainly not Pete Buttigieg have ever had a breakthrough with African American voters sufficient to eliminate Biden’s advantage. And also, Biden’s got the secret weapon.

“If Barack Obama is free to get out there and do the campaigning that only he can do in American political life, I think that would be a meaningful lift for the Democrats.”

Wilson is a co-founder of the Lincoln Project, a Super Pac named for the party’s greatest leader and meant to persuade loyalists away from a man many consider its worst

“You sometimes need hard men and hard women to do tough things,” he says. In that sense, the name of his project is fitting. Lincoln saved the union and ended slavery with all the guile and will of the most ruthless, when necessary the most dirty politician.

I am putting my ideological priors and my preferences aside, because I think that Donald Trump is an existential threat to the Republic. I’ll do anything I can to help ensure that he is not president for another four years.”

“I can’t think of anyone more anathema to the seat of Sioux county, but a packed house there suggests there’s broad appeal, for whatever reason,” Best said.

Corrie Hayes, a 21-year-old senior at Northwestern College, said she was impressed particularly with his response to a question about abortion rights, when he said that in the Book of Genesis, life begins with breath. She wouldn’t get into her positions on policy – she said she was deeply religious and her faith guided her every day – but she said she could tell Buttigieg was sincere about his faith.

More people than ever before are reading and supporting our journalism, in more than 180 countries around the world. And this is only possible because we made a different choice: to keep our reporting open for all, regardless of where they live or what they can afford to pay.

None of this would have been attainable without our readers’ generosity – your financial support has meant we can keep investigating, disentangling and interrogating. It has protected our independence, which has never been so critical. We are so grateful.

Pete Buttigieg knew he was foraying into unfriendly confines when he was en route to Orange City, the seat of Iowa’s most conservative county.

In the end, the vote on Cheney was taken by secret ballot, allowing members to express their feelings with less fear of reprisal. She won the backing of more than two-thirds of her colleagues. Greene lost her committee seats based on the en bloc vote of the Democratic majority, but she was supported by all but 11 of her Republican colleagues.

But if you are talking about the mixture of violence and politics ... if you are talking about people who feel they are entitled to power and are being denied it and choose violence as a way to demand it back ... if you are talking about questions of race and dominance ... all these things have deep roots in American history."

And was this merely an expression of the rough-hewn, frontier-flavored behavior of Americans in the years before the Civil War? No, Freeman argues, it was an instrument for the defense of privilege and political power.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

since 9/11 right-wing terrorists in the United States have killed 110 people for political reasons, while Antifa supporters have killed exactly no one for political reasons.

Yet there is no indication that the Trump administration will effectively criminalize being a member of an American right-wing extremist group. And for good reason: The First Amendment is the first for a reason, and it allows Americans to hold extremist beliefs of all flavors without fear of prosecution — including Antifa supporters.

I had other doubts, too. It seemed hubristic, or worse, to make multitrillion-dollar policy bets based on computer models trying to forecast climate patterns decades into the future. Climate activists kept promoting policies based on technologies that were either far from mature (solar energy) or sometimes actively harmful (biofuels).

Expensive efforts to curb greenhouse gas emissions in Europe and North America seemed particularly fruitless when China, India and other developing countries weren’t about to curb their own appetite for fossil fuels

just how fast is Greenland’s ice melting right now? Is this an emergency for our time, or is it a problem for the future?

His pitch was simple: The coastline we have taken for granted for thousands of years of human history changed rapidly in the past on account of natural forces — and would soon be changing rapidly and disastrously by man-made ones. A trip to Greenland, which holds one-eighth of the world’s ice on land (most of the rest is in Antarctica) would show me just how drastic those changes have been. Would I join him?

Greenland is about the size of Alaska and California combined and, except at its coasts, is covered by ice that in places is nearly two miles thick. Even that’s only a fraction of the ice in Antarctica, which is more than six times as large

Greenland’s ice also poses a nearer-term risk because it is melting faster. If all its ice were to melt, global sea levels would rise by some 24 feet. That would be more than enough to inundate hundreds of coastal cities in scores of nations, from Jakarta and Bangkok to Copenhagen and Amsterdam to Miami and New Orleans.

There was also a millenarian fervor that bothered me about climate activism, with its apocalyptic imagery (the Statue of Liberty underwater) and threats of doom unless we were willing to live far more frugally.

“We haven’t had a good positive mass balance year since the late 1990s,” he told me in a follow-on email when I asked him to explain the data for me. The losses can vary sharply by year. The annualized average over the past 30 years, he added, is 170 gigatons per year. That’s the equivalent of about 5,400 tons of ice loss per second. That “suggests that Greenland ice loss has been tracking the I.P.P.C. worse-case, highest-carbon-emission scenario.

The data shows unmistakably that Greenland’s ice is not in balance. It is losing far more than it is gaining.

scientists have been drilling ice-core samples from Greenland for decades, giving them a very good idea of climatic changes stretching back thousands of years. Better yet, a pair of satellites that detect anomalies in Earth’s gravity fields have been taking measurements of the sheet regularly for nearly 20 years, giving scientists a much more precise idea of what is happening.

it’s hard to forecast with any precision what that means. “Anyone who says they know what the sea level is going to be in 2100 is giving you an educated guess,” said NASA’s Willis. “The fact is, we’re seeing these big ice sheets melt for the first time in history, and we don’t really know how fast they can go.”

His own educated guess: “By 2100, we are probably looking at more than a foot or two and hopefully less than seven or eight feet. But we are struggling to figure out just how fast the ice sheets can melt. So the upper end of range is still not well known.”

On the face of it, that sounds manageable. Even if sea levels rise by eight feet, won’t the world have nearly 80 years to come to grips with the problem, during which technologies that help us mitigate the effects of climate change while adapting to its consequences are likely to make dramatic advances?

Won’t the world — including countries that today are poor — become far richer and thus more capable of weathering the floods, surges and superstorms?

The average rate at which sea level is rising around the world, he estimates, has more than tripled over the past three decades, to five millimeters a year from 1.5 millimeters. That may still seem minute, yet as the world learned during the pandemic, exponential increases have a way of hitting hard.

“When something is on a straight line or a smooth curve, you can plot its trajectory,” Englander said. “But sea level, like earthquakes and mudslides, is something that happens irregularly and can change rather quickly and surprise us. The point is, you can no longer predict the future by the recent past.”

In The Wall Street Journal’s editorial pages, where I used to work, the theoretical physicist Steven Koonin, a former under secretary for science in the Obama administration’s Energy Department, cast doubt on the threat from Thwaites in a voice that could have once been mine. He also thinks the risks associated with Greenland’s melting are less a product of human-induced global warming than of natural cycles in North Atlantic currents and temperatures, which over time have a way of regressing to the mean.

Even the poorest countries, while still unacceptably vulnerable, are suffering far fewer human and economic losses to climate-related disasters.

Another climate nonalarmist is Roger Pielke Jr., a professor of environmental studies at the University of Colorado Boulder. I call Pielke a nonalarmist rather than a skeptic because he readily acknowledges that the challenges associated with climate change, including sea-level rise, are real, serious and probably unstoppable, at least for many decades.

“If we have to have a problem,” he told me when I reached him by phone, “we probably want one with a slow onset that we can see coming. It’s not like an asteroid coming from space.”

“Since the 1940s, the impact of floods as a proportion of U.S. gross domestic product has dropped by 70 percent-plus,” Pielke said. “We see this around the world, across phenomena. The story is that fewer people are dying and we are having less damage proportional to G.D.P.”

“Much climate reporting today highlights short-term changes when they fit the narrative of a broken climate but then ignores or plays down changes when they don’t, often dismissing them as ‘just weather,’” he wrote in February.

Global warming is real and getting worse, Pielke said, yet still it’s possible that humanity will be able to adapt to, and compensate for, its effects.

A few years ago, I would have found voices like Koonin’s and Pielke’s persuasive. Now I’m less sure. What intervened was a pandemic.

That’s what I thought until the spring of 2020, when, along with everyone else, I experienced how swiftly and implacably nature can overwhelm even the richest and most technologically advanced societies. It was a lesson in the sort of intellectual humility I recommended for others

It was also a lesson in thinking about risk, especially those in the category known as high-impact, low-probability events that seem to be hitting us with such regularity in this century: the attacks of Sept. 11, 2001; the tsunamis of 2004 and 2011, the mass upheavals in the Arab world

What if the past does nothing to predict the future? What if climate risks do not evolve gradually and relatively predictably but instead suddenly soar uncontrollably? How much lead time is required to deal with something like sea-level rise? How do we weigh the risks of underreacting to climate change against the risks of overreacting to it?

I called Seth Klarman, one of the world’s most successful hedge-fund managers, to think through questions of risk. While he’s not an expert on climate change, he has spent decades thinking deeply about every manner of risk

And we will almost certainly have to do it from sources other than Russia, China, the Democratic Republic of Congo and other places that pose unacceptable strategic, environmental or humanitarian risks

“If you face something that is potentially existential,” he explained, “existential for nations, even for life as we know it, even if you thought the risk is, say, 5 percent, you’d want to hedge against it.”

“One thing we try to do,” he said, “is we buy protection when it’s really inexpensive, even when we think we may well not need it.” The forces contributing to climate change, he noted, echoing Englander, “might be irreversible sooner than the damage from climate change has become fully apparent. You can’t say it’s far off and wait when, if you had acted sooner, you might have dealt with it better and at less cost. We have to act now.”

In other words, an ounce of prevention is worth a pound of cure. That’s particularly true if climate change is akin to cancer — manageable or curable in its earlier stages, disastrous in its later ones.

As I’ve always believed, knowing there is grave risk to future generations — and expecting current ones to make immediate sacrifices for it — defies most of what we know about human nature. So I began to think more deeply about that challenge, and others.

For the world to achieve the net-zero goal for carbon dioxide emissions by 2050, according to the International Energy Agency, we will have to mine, by 2040, six times the current amounts of critical minerals — nickel, cobalt, copper, lithium, manganese, graphite, chromium, rare earths and other minerals and elements — needed for electric vehicles, wind turbines and solar panels.

The poster child for this kind of magical thinking is Germany, which undertook a historic Energiewende — “energy revolution” — only to come up short. At the turn of the century, Germany got about 85 percent of its primary energy from fossil fuels. Now it gets about 78 percent, a puny reduction, considering that the country has spent massive sums on renewables to increase the share of electricity it generates from them.

As in everything else in life, so too with the environment: There is no such thing as a free lunch. Whether it’s nuclear, biofuels, natural gas, hydroelectric or, yes, wind and solar, there will always be serious environmental downsides to any form of energy when used on a massive scale. A single industrial-size wind turbine, for instance, typically requires about a ton of rare earth metals as well as three metric tons of copper, which is notoriously destructive and dirty to mine.

no “clean energy” solution will easily liberate us from our overwhelming and, for now, inescapable dependence on fossil fuels.

Nobody brings the point home better than Vaclav Smil, the Canadian polymath whose most recent book, “How the World Really Works,” should be required reading for policymakers and anyone else interested in a serious discussion about potential climate solutions.

“I’ve talked to so many experts and seen so much evidence,” he told me over Zoom, “I’m convinced the climate is changing, and addressing climate change has become a philanthropic priority of mine.”

Things could turn a corner once scientists finally figure out a technical solution to the energy storage problem. Or when governments and local actors get over their NIMBYism when it comes to permitting and building a large energy grid to move electricity from Germany’s windy north to its energy-hungry south. Or when thoughtful environmental activists finally come to grips with the necessity of nuclear energy

Till then, even as I’ve come to accept the danger we face, I think it’s worth extending the cancer metaphor a little further: Just as cancer treatments, when they work at all, can have terrible side effects, much the same can be said of climate treatments: The gap between an accurate diagnosis and effective treatment remains dismayingly wide

Only when countries like Vietnam and China turned to a different model, of largely bottom-up, market-driven development, did hundreds of millions of people get lifted out of destitution.

the most important transformation has come in agriculture, which uses about 70 percent of the world’s freshwater supply.

Farmers gradually adopted sprinkler and drip irrigation systems, rather than more wasteful flood irrigation, not to conserve water but because the technology provided higher crop yields and larger profit margins.

Water shortages “will spur a revolutionary, aggressive approach to getting rid of flood irrigation,” said Seth Siegel, the chief sustainability officer of the Israeli AgTech company N-Drip. “Most of this innovation will be driven by free-market capitalism, with important incentives from government and NGOs.

meaningful environmental progress has been made through market forces. In this century, America’s carbon dioxide emissions across fuel types have fallen to well below 5,000 million metric tons per year, from a peak of about 6,000 million in 2007, even as our inflation-adjusted G.D.P. has grown by over 50 percent and total population by about 17 percent.

1) Engagement with critics is vital. Insults and stridency are never good tools of persuasion, and trying to cow or censor climate skeptics into silence rarely works

the biggest single driver in emissions reductions from 2005 to 2017 was the switch from coal to natural gas for power generation, since gas produces roughly half the carbon dioxide as coal. This, in turn, was the result of a fracking revolution in the past decade, fiercely resisted by many environmental activists, that made the United States the world’s largest gas producer.

In the long run, we are likelier to make progress when we adopt partial solutions that work with the grain of human nature, not big ones that work against it

Renewables, particularly wind power, played a role. So did efficiency mandates.

The problem with our civilization isn’t overconfidence. It’s polarization, paralysis and a profound lack of trust in all institutions, including the scientific one

Devising effective climate policies begins with recognizing the reality of the social and political landscape in which all policy operates. Some thoughts on how we might do better:

They may not be directly related to climate change but can nonetheless have a positive impact on it. And they probably won’t come in the form of One Big Idea but in thousands of little ones whose cumulative impacts add up.

2) Separate facts from predictions and predictions from policy. Global warming is a fact. So is the human contribution to it. So are observed increases in temperature and sea levels. So are continued increases if we continue to do more of the same. But the rate of those increases is difficult to predict even with the most sophisticated computer modeling

3) Don’t allow climate to become a mainly left-of-center concern. One reason the topic of climate has become so anathema to many conservatives is that so many of the proposed solutions have the flavor, and often the price tag, of old-fashioned statism

4) Be honest about the nature of the challenge. Talk of an imminent climate catastrophe is probably misleading, at least in the way most people understand “imminent.”

A more accurate description of the challenge might be a “potentially imminent tipping point,” meaning the worst consequences of climate change can still be far off but our ability to reverse them is drawing near. Again, the metaphor of cancer — never safe to ignore and always better to deal with at Stage 2 than at Stage 4 — can be helpful.

5) Be humble about the nature of the solutions. The larger the political and financial investment in a “big fix” response to climate change on the scale of the Energiewende, the greater the loss in time, capital and (crucially) public trust when it doesn’t work as planned

6) Begin solving problems our great-grandchildren will face. Start with sea-level rise

We can also stop providing incentives for building in flood-prone areas by raising the price of federal flood insurance to reflect the increased risk more accurately.

7) Stop viewing economic growth as a problem. Industrialization may be the leading cause of climate change. But we cannot and will not reverse it through some form of deindustrialization, which would send the world into poverty and deprivation

8) Get serious about the environmental trade-offs that come with clean energy. You cannot support wind farms but hinder the transmission lines needed to bring their power to the markets where they are needed.

9) A problem for the future is, by its very nature, a moral one. A conservative movement that claims to care about what we owe the future has the twin responsibility of setting an example for its children and at the same time preparing for that future.

global warming represents the collapse of such complex systems at such an extreme scale that it overrides our emotional capacity

it is darkly inverted on the Instagram account @afffirmations, where new-age positive thinking buckles under the weight of generational despair, and serene stock photography collides with mantras like “I am not climate change psychosis” and “Humanity is not doomed.”

Often the features of our dystopia are itemized, as if we are briskly touring the concentric circles of hell — rising inequality, declining democracy, unending pandemic, the financial system optimistically described as “late” capitalism — until we have reached the inferno’s toasty center, which is the destruction of the Earth through man-made global warming.

This creates its own perverse flavor of climate denial: We acknowledge the science but do not truly accept it, at least not enough to urgently act.

This paralysis itself is almost too horrible to contemplate. As global warming cooks the Earth, it melts our brains, fries our nerves and explodes the narratives that we like to tell about humankind — even the apocalyptic ones.

This “end of the world” does not resemble the ends of religious prophecies or disaster films, in which the human experiment culminates in dramatic final spectacles

Instead we persist in an oxymoronic state, inhabiting an end that has already begun but may never actually end.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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