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There were also roasted-beet salads with honeyed goat cheese, and dessert trays (panna cotta, cheesecake, tartlets featuring raspberries, strawberries, and blueberries) that formed a pretty assemblage of reds, whites, and blues. There were dinner plates featuring both monkfish and filets of beef: the surf and the turf, the this and the that, entrees suggesting that, despite the evidence to the contrary, it is possible to have it both ways. There was Aya Hijazi, an Egyptian American social activist who was imprisoned for nearly three years for those activities, speaking passionately, via a prerecorded video, about her ordeal—and the journalistic work that led to her liberation. There were journalism awards presented to reporters who cover the White House. There were announcements of the recipients of this year’s White House Correspondents’ Association scholarships—the college students who may come to serve as the next generation of White House correspondents. “This night is about you, and what you’ve accomplished,” Talev told them.

If one person can eclipse an entire evening’s worth of celebration—the military show, the scholarships, the awards, the urgent discussion of the profound necessity of press freedom—that’s a good sign that something should change about the evening. There’s the Correspondents’ Dinner as an event, and the Correspondents’ Dinner as a norm; both would benefit, at this point, from scaling back to become something smaller, more intimate, more meaningful—less about celebrity, less about comedy, and more about journalism. A smaller dinner would be more boring, definitely, but also more in line with journalism’s own best vision of itself: as a watchdog, as a safeguard, as an extension of the curiosity of the American people.

GM’s view contrasts with other auto-making giants, including Toyota Motor Corp. TM 0.93% and Ford Motor Co. F -0.32% , which are working on full electrics but also expanding their U.S. hybrid offerings

Last week, Continental AG, one of the world’s biggest car-parts makers, said it would cut investment in conventional engine parts because of a faster-than-expected fall in demand—yet another sign the industry is accelerating the shift to electric vehicles.

Today, auto companies generally lose money on each electric car they sell, mostly because of the high cost of lithium-ion batteries. Concerns about the battery range, along with a lack of places to plug in, also deter buyers from considering electric vehicles. Those factors make going straight to all-electric cars a risky strategy

Hybrids, which were popularized by Toyota’s Prius last decade as a social statement, accounted for about 3% of U.S. sales in 2018, according to research firm LMC Automotive. Sales of plug-in electric vehicles were around 1% of the total market—mostly thanks to the success of Tesla Inc.’s offerings.

pouring investment into both hybrids and electrics strains car-company finances, Morgan Stanley analyst Adam Jonas said. “It’s time to pick a path and commit to it,”

VW and GM are focused on all-electric cars largely because of China, where new regulations require car companies to sell a minimum number of zero-emissions vehicles to avoid financial penalties.

VW plans to use its electric-car expansion in China to build scale and drive down prices faster in the U.S., said Scott Keogh, VW’s U.S. chief.

Auto companies are spending $225 billion to develop more than 200 new plug-in vehicles through 2023, a figure that doesn’t include hybrids

For now, both hybrids and electric cars are more expensive to produce than comparable gas-powered vehicles. A hybrid system can add roughly $2,000 to a vehicle’s cost, while a fully electric version costs an additional $6,000 to $10,000,

Toyota’s sales chief for North America, said that with U.S. electric-vehicle sales expected to lag behind Europe and China, the company needs a nearer-term remedy. “That’s why we feel so confident in hybrids

In a matter of weeks, China has gone from being the epicenter of the virus to almost the only refuge from it, prompting hundreds of thousands of Chinese citizens abroad to flock home. Some 20,000 people are arriving on flights into China every day

“Certainly, China is indeed very safe now,” said Li, while the United States is just becoming more dangerous.

“The U.S. can’t test everyone, like in China. Testing an entire planeload of passengers and providing results the next day is impossible in the U.S.,” he said, referring to the entry procedures he went through on arrival in his home country.

There has also been a rush of returned from Britain since a government adviser advocated a “herd immunity” strategy, suggesting that it could be helpful if 60 percent of the population was infected.

Beijing’s municipal government on Sunday introduced new rules requiring all people arriving in the capital go into “centralized quarantine” at hotels for 14 days upon arrival, at their own expense.

Areas around the country, from Inner Mongolia in the north to Sanya on the island of Hainan in the south, have instituted similar measures, requiring stays in quarantine centers rather than trusting people to isolate themselves at home. More local authorities are expected to follow suit.

Beijing police authorities have made an example of a 37-year-old Chinese woman who works at Massachusetts biotechnology company Biogen and attended the Boston conference that has been linked to other infections, according to local media reports

She failed to report she was feeling sick before boarding her flight, took painkillers to suppress her fever and then lied to flight attendants about her condition, local police said.

The suspicious attendants reported her to police authorities upon arrival, who quarantined her and had her tested for the virus. It came back positive. In addition to being sick, she is now under criminal investigation for obstructing infectious disease prevention.

he program began in 2007 and was largely funded at the request of Harry Reid, the Nevada Democrat who was the Senate majority leader at the time. It was officially shut down in 2012, when the money dried up, according to the Pentagon. But Luis Elizondo, who ran the program at the time, said that he continued it until 2017. After the publication of a New York Times article later that year about the program and criticism from program officials that the government was not forthcoming about reports on aerial phenomena, the Pentagon restarted the program last summer as the Unidentified Aerial Phenomena Task Force.

Officials briefed on the report said it also examined video that shows a whitish oval object described as a giant Tic Tac, about the size of a commercial plane, encountered by two Navy fighter jets off the coast of San Diego in 2004.

Nonetheless, the government began a classified study, called Project Sign, out of concern that such objects could be advanced Soviet weapons. That was followed by Project Blue Book, which reviewed about 12,000 cases from 1952 to 1969, 701 of which could not be explained. It ended with a report saying U.F.O.s were not worth further study

Other cases include a spinning disk that was seen hovering above O’Hare Airport in Chicago in 2006, and two “sunlight-colored” objects reported by a professional pilot in England in 2007, as The New Yorker reported.

Senior administration officials who had been briefed on the report’s contents told The Times that the report still cannot explain the unusual movements that have mystified scientists and the military, but that it concludes a vast majority of more than 120 incidents over the past two decades did not originate from any American military or other advanced U.S. government technology.

Over the same period, ByteDance has flourished. Its TikTok app has been downloaded a billion times, of which nearly 100 million came from the United States, and it has a jaw-dropping valuation of $75 billion.

ByteDance has also been working with Xinjiang authorities under a program called “Xinjiang Aid,” whereby Chinese companies open subsidiaries or factories in Xinjiang and employ locals who have been detained in the camps. Its operations are centered on Hotan, an area of Xinjiang considered backward by the Communist Party and where the repression has been among the most severe.

Leaked documents have previously shown how ByteDance censors content that the Chinese government disapproves of, including Tiananmen Square, Tibetan independence, or the banned religious group Falun Gong.

ByteDance has been guiding and helping Xinjiang authorities and media outlets to use its news aggregation app and Douyin to “propagate and showcase Hotan’s new image,” according to the ASPI report.

In the case of Huawei, which is locked in an existential battle with the Trump administration, there is evidence of extensive and direct work with Chinese security organs in Xinjiang, including helping authorities there with the “digitization requirements” of public security projects.

“Together with the Public Security Bureau, Huawei will unlock a new era of smart policing and help build a safer, smarter society,” a Xinjiang government website quoted one Huawei director as saying last year.

When the Xinjiang Public Security Department and Huawei signed the agreement to establish an “intelligent security industry” innovation lab in the regional capital of Urumqi last year, a local official said Huawei had been supplying “reliable technical support” for the department, according to the report

Huawei has also participated in a program called “Safe Xinjiang,” which the ASPI experts said was “code for a police surveillance system.”

“The Chinese tech companies in this report enjoy a highly favorable regulatory environment and are unencumbered by privacy and human rights concerns,” it concludes. Many are engaged in deeply unethical behavior in Xinjiang, where their work directly supports and enables mass human rights abuses.”

the objection from President Donald Trump's Republican allies has virtually zero chance of changing the election outcome, only to delay for a few hours the inevitable affirmation of Biden's victory as the Electoral College winner and the next president.

On Wednesday, Missouri Republican Sen. Josh Hawley became the first senator to announce plans to object to the results -- a significant move since both a House member and senator are required to mount an objection when Congress counts the electoral votes. CNN previously reported that at least 140 House Republicans are expected to vote against counting the electoral votes in Congress, according to two GOP House members.

Senate Majority Leader Mitch McConnell -- who has said the vote would mark one of the most significant, perhaps the most significant, he'd ever cast

Senate Minority Leader Chuck Schumer, a New York Democrat, seemingly dismissed the announcement Saturday from the handful of Republicans, tweeting: "Joe Biden and Kamala Harris will be President and Vice President of the United States in 18 days."

On Friday, a federal judge threw out a lawsuit from GOP Rep. Louie Gohmert of Texas and several Arizona Republicans seeking to force Vice President Mike Pence to help throw the election to Trump.

The parallel effort in the House is being led by Representative Mo Brooks, Republican of Alabama, who has said there was “serious voter fraud and election theft in this election,” even though there is considerable evidence to the contrary. He is eyeing challenges to the election results in five states — Arizona, Pennsylvania, Nevada, Georgia and Wisconsin — where Trump loyalists claim that varying degrees of fraud or illegal voting took place, despite certification by the voting authorities and no evidence of widespread impropriety.Those challenges are required to have a senator’s signature affixed, according to the Constitution and the Electoral Count Act of 1887.

Mr. Hawley, who swept into Washington in 2019 after defeating the incumbent Democrat, Claire McCaskill, has embraced Mr. Trump’s brand of populism in his short time in the Senate, pushing for $2,000 pandemic relief checks and railing against social media companies. He is widely considered a potential contender for the 2024 presidential election.

fter the 2016 election, several House Democrats tried again, rising during the joint session to register challenges against Mr. Trump’s victory over Hillary Clinton in various states. The Democrats cited reasons ranging from long lines at polling sites to the Kremlin’s election influence operation.But no senators supported them, leading the departing vice president presiding over the session — Mr. Biden — to gavel down the House members’ verbal objections and declare, “It is over.”Thomas Kaplan contributed reporting from Washington, and Astead W. Herndon from Macon, Ga.

The lawmakers convened Wednesday evening, after hours of delay, in a show of defiance. House Speaker Nancy Pelosi said she had consulted with fellow congressional leaders, the Pentagon, the Justice Department and Vice President Pence before concluding that Congress should move ahead with the ceremony interrupted earlier in the day by rioters provoked to action by Trump at a morning rally.

As lawmakers returned to work following the riot, the tone of the debate turned more somber and impassioned than before the interruption, with a number of Republicans who had planned to slow the proceedings with objections announcing they would stand aside.

Both chambers picked up Wednesday night where they had left off before the evacuation, considering a challenge to Biden’s 11 electoral votes in Arizona. The Senate rejected the challenge by 93 to 6 and the House by 303 to 121.

That sparked an exchange of words between Republicans and Democrats sitting behind Lamb that nearly led to blows before aides intervened.

Lawmakers then moved to reconvene the joint session and complete the counting of the remaining states, setting up a final confirmation of Biden’s victory at 3:45 a.m. — nearly 21 hours after the proceedings began.

Earlier in the day, the ceremonial reading of the electoral votes had just begun when pro-Trump rioters rushed the building at around 2 p.m., forcing the evacuation of both chambers of Congress. For hours, rioters rampaged through the Capitol complex. One woman was fatally shot in the building.

Still, the outcome of the congressional proceedings had been clear from the start, particularly after Pence announced he would reject pleas from the president to use his role as the session’s presiding officer to hand a win to Trump.

While lawmakers huddled in an undisclosed location during the siege, Republican leaders pressed their members to abandon their plans to challenge the electoral vote. Several senators said they would no longer object, notably Sen. Kelly Loeffler (R-Ga.), who had embraced the challenge as part of the hard-fought Senate election she lost Tuesday.

The congressional process was supposed to be a mere procedural checkpoint on the way to Biden’s oath-taking later this month. Biden won the popular vote on Nov. 3 and, last month, the electoral college met in each state capital, as stipulated in the U.S. Constitution. Biden won 306 electoral votes to Trump’s 232.

According to an 1887 law that governs the process, any member of the House of Representatives, joined by a senator, can object to an individual state’s electoral tally, prompting a two-hour debate, followed by a vote in each chamber

Some of the last bastions of objective reporting in Britain are shaking. The world of shared-facts is crumbling away. The sacred role of impartial broadcasting in British public life is teetering on the edge.

The electors cast their ballots for president and vice president via paper ballot. Thirty-three states and the District of Columbia legally require their electors to choose whoever won the state’s popular vote, so there should be no surprises there. The other 17 states don’t “bind” their electors, meaning they can vote for whomever they choose.

After the electors cast their ballots, the votes are counted and the electors sign certificates showing the results. These are paired with certificates from the governor’s office showing the state’s vote totals.

Congress officially counts the votes in a joint session held in the House chamber on Jan. 6, with Mr. Pence presiding. Mr. Pence opens the certificates

The session cannot be ended until the count is complete and the result publicly declared. At this point, the election is officially decided. The only remaining task is the inauguration on Jan. 20.

Democrats will hold control of the House. And Republicans will control the Senate, regardless of the results of the Georgia runoff elections on Jan. 5, because Mr. Pence will still be in office to act as the tiebreaking vote if the chamber is split 50 to 50.

Any objection to a state’s results must be made in writing and be signed by at least one senator and one member of the House. The two chambers would then separate to debate the objection.

Stopping Mr. Biden from assuming office remains a long-shot strategy for Republicans.For an objection to stand, it must pass both houses of Congress by a simple majority. If the vote followed party lines, Republicans could not block Mr. Biden’s victory.

With some Trump allies already planning objections, the congressional session is likely to make for good political theater. But the process has little chance of changing the outcome of the election.

the results were consistent with Albert Einstein’s theory of general relativity, which describes how matter and energy warp space-time to create what we call gravity. As more data is gathered, this cosmic hum could help researchers understand how the universe achieved its current structure and perhaps reveal exotic types of matter that may have existed shortly after the Big Bang 13.7 billion years ago.

“The gravitational-wave background was always going to be the loudest, most obvious thing to find,” said Chiara Mingarelli, an astrophysicist at Yale University and a member of NANOGrav, which is funded by the National Science Foundation. “This is really just the beginning of a whole new way to observe the universe.”

Gravitational waves are created by any object that spins, such as the rotating remnants of stellar corpses, orbiting black holes or even two people “doing a do-si-do,” Dr. Mingarelli said. But unlike other types of waves, these ripples stretch and squeeze the very fabric of space-time, warping the distances between any celestial objects they pass by.

Gravitational waves were first detected in 2016 as audible chirps by the Laser Interferometer Gravitational-Wave Observatory, or LIGO, collaboration; the breakthrough solidified Einstein’s theory of general relativity as an accurate model of the universe and earned the project’s founders the Nobel Prize in Physics in 2017. But LIGO’s signals were mostly in the frequency range of a few hundred hertz, and were created by individual pairs of black holes or neutron stars that were 10 to 100 times as massive as our sun.

In contrast, the researchers involved in this work were looking for a collective hum at much lower frequencies — one-billionth of one hertz, far below the audible range — emanating from everywhere all at once.

If the signal does arise from orbiting pairs of supermassive black holes, studying the gravitational-wave background will shed light on the evolutionary history of these systems and the galaxies surrounding them. But the gravitational-wave background could also be coming from something else, like hypothetical cracks in space-time known as cosmic strings.

Or it could be a relic of the Big Bang, akin to the cosmic microwave background, which led to fundamental discoveries about the structure of the universe to within 400,000 years of its beginning. The gravitational-wave background would be an even better primordial probe, Dr. Mingarelli said, because it would have been emitted almost instantaneously.

To detect the gravitational-wave background, researchers analyzed the lighthouse-like nature of pulsars. These objects act like cosmic clocks, emitting beams of radio waves that can be periodically measured on Earth.

Einstein’s theory of general relativity predicts that as gravitational waves sweep past pulsars, they should expand and shrink the distance between these objects and Earth, changing the time it takes for the radio signals to arrive at observers. And if the gravitational-wave background is indeed everywhere, pulsars across the universe should be affected in a correlated way.

The findings carry a confidence level in the range of 3.5- to 4-sigma, just shy of the 5-sigma standard generally expected by physicists to claim a smoking-gun discovery. That means the odds of seeing a result like this randomly are about 1 in 1,000 years, Dr. Mingarelli said. “That’s good enough for me, but other people want once in a million years,” she said. “We’ll get there eventually.”

f the ripples originated with the Big Bang, they might instead provide insight into the expansion of the cosmos or the nature of dark matter — the invisible glue scientists think holds the universe together — and perhaps even reveal new particles or forces that once existed.

a few more years may be needed to confirm the source of the gravitational-wave background. Researchers have already begun using their data to piece together maps of the universe and to look for intense, nearby regions of gravitational-wave signals indicative of an individual supermassive black hole binary.

Let’s start with the obvious: Israel has a right to defend itself, rescue the hostages, arrest and prosecute Hamas and engage in lawful armed combat with its enemy.

People claiming the Hamas attack is the ‘violence of the oppressed’ are deluded. Hamas rules Gaza like a mafia state: its operatives walk around neighbourhoods in twos, dressed in dark suits, prying into people’s business. They run the place on a mixture of terror, public service provision and the kudos of their fighters.

They are feared but there is widespread disrespect for them, especially among secular and nationalist sections of the population.

Paradoxically, the western ‘anti-imperialists’ trying to apologise for the terror attack, and the Israeli right calling for retribution against civilians, both need to identify Hamas with the Palestinian population of Gaza in order to justify violence. But there is no basis for doing so.

The fact that a violent action takes place in the context of a wider oppression does not make it either (a) just (b) lawful under international law or c) effective in pursuit of social justice.

In this case, Hamas’s act of terror looks set to achieve the opposite.

What does Hamas want?

Hamas has offered a truce and asked for negotiations, stating that it has ‘achieved its objective’. If so, it’s logical to conclude that the immediate objective was to demonstrate proof-of-concept of an unstoppable pogromist terror. Do as we ask or we do this again, might be a fair summary.

The wider aim, according to numerous experts, is to force Hamas and Iran back into the power-broking process in the Middle East region, paralysing Saudi-Israeli rapprochement.

The firm view of the Islamic Republic is that the governments that are gambling on normalizing relations with the Zionist regime will suffer losses. Defeat awaits them…Today, the situation of the Zionist regime is not a situation that encourages closeness to it. They [other governments] should not make this mistake. The usurper [Zionist] regime is coming to an end.

Hamas could only achieve the aim of ending Saudi-Israeli rapprochement with an attack designed to trigger massive retribution, risking a regional all-out war.

there’s a line in Khamenei’s 3 October speech that, in retrospect looks explanatory: Thus, [the Zionists] are filled with grudge. They are filled with anger! Of course, the Quran exclaims: “Say, “die of your rage!” (3:119). That’s right. Be angry, and die of your rage. And this will happen. They are dying. With God’s help, this matter of ‘die of your rage’ is happening now as regards the Zionist regime.

‘Die of your rage’ might actually be a good summary of what Hamas intends Israel to now do.

Enraged by the barbarity of the attacks, Israel unleashes unprecedented collective punishment against Gaza, triggering both Hezbollah and West Bank militants to join in the fight; this in turn prompts a wave of anti-Semitic demonstrations in western cities, and draws the USA into a regional quagmire, testing the limits of American support for Israel

Meanwhile combat losses, and retribution over the complete failure of Netanyahu’s strategy of ‘managing’ the conflict, raise political divisions in Israeli society to the point where its democracy fails.

In a context where both Russia and China have complex hybrid destabilisation operations going on in western democracies, and where the Brics+ project is pursuing the active decomposition of the rules-based order, this objective does not look as mad as at first sight.

the ‘multipolar world’ turns out not to be one of peaceful coexistence, but characterised by extreme conflicts and genocide.

In pursuit of systemic competition Beijing and Moscow are scraping at every open wound in the body geopolitic

it’s what you get when you purposefully dismantle an international order based on treaties and explicit rules. And where elites in Russia, the USA, Brasil and parts of Europe are openly experimenting with ethno-nationalist politics.

Chaos, then, is a feature of multipolarity, not a bug.

Israel has signalled its military objective is to destroy Hamas. From my experience in Gaza I would say: that is possible.

But be in no doubt. It will need a sustained urban combat operation, a long-term military occupation, massive loss of civilian life, an existential refugee crisis in Sinai, and the diversion of US-supplied ammunition and resources from Ukraine.

Attempting it with a largely conscript/reservist army, full of recently mobilised and enraged soldiers? Again it’s worth remembering Khamenei’s exhortation to Israelis to ‘die of your rage’.

The very impossibility of all these outcomes shows why we need an internationally mediated peace, alongside a functional two-state solution, which allows the people of Gaza to live in peace, exercise democracy and travel across borders.

not only will liberal sympathy for Israel evaporate, but the Muslim minorities in some Western countries will be radicalised.

Typically, from my experience, combat in Gaza takes the following form. There is a street with children playing at one end; in the middle it is eerily deserted; at the other end is the IDF and above is an IDF drone. But there is no front line. The mujahedeen are in tunnels, popping up to take sniper shots or lay IEDs at night, and only committing ATGMs once a vehicle comes into view. The only front line is, for most of the time, between the IDF and Palestinian civilians.

Both sides risk miscalculating. Hamas does not care what happens to Palestinian civilians in Gaza, many of whom hate Hamas.

But there is a danger of miscalculation for Israel too. Netanyahu’s far-right government completely missed the threat, actively stoked tensions in the West Bank and Al Aqsa, and could easily now double down on a self-destructive course.

Ultimately, you cannot hold two million people in an open air prison without a gaoler to keep order. If Hamas can’t do it, the IDF will have to be a permanent occupation force, or it will have to install the PA, or the UN will have to send a stabilisation force.

Danger of miscalculation

The Brics+ ideology

The Gaza crisis is the latest example of how the Russian/Chinese ‘multipolar world’ project works in practice. It doesn’t matter whether there is a chain of command that goes Moscow→Tehran→Hamas. There is a chain of understanding – seize every opportunity to militarise all conflict; exploit every unexpected breakthrough; make all violence symbolic; weaponise the information space and push conflict into the heartlands of ‘imperialism’.

the Brics+ ideology. Its central tenets are that a multipolar world is better than the charter system; that universalism and international law are over; that the West no longer has the right to use the structures of international governance to normalise concepts like democracy or human rights; and that everything that disorganises the rules-based order is progressive, even when carried out by reactionary political forces.

Arab nationalism no longer looks like the dominant ideology on the demonstrations we’ve seen in Sydney, London and NYC. Alongside it there’s a mixture of Islamism plus the ‘decolonisation’ agenda of postmodernist academia.

For the past two years, during the Ukraine war, this incipient red-brown ideology has been mostly contained:

with this conflict there is now a danger that the masses turn up, and are corralled into this emergent fusion of far-left/far-right politics.

I’ve spent the period post-2016 trying to equip the democratic left to defeat this ideology. It’s not about being ‘anti-woke’, or apologising for colonialism: it means teaching people that a cocktail of anti-humanism, anti-universalism and anti-rationality is a route to excusing the totalitarian states in Russia and China, and – now – the genocidal actions of their proxies.

A case study of this is the statement issued by 31 Harvard student groups saying they ‘hold the Israeli regime entirely responsible for all the unfolding violence’ – just hours after the Hamas attack began.

the global left is rapidly splitting into irreconcilable camps – as Edward Thompson recognised it would, under the influence of post-structuralism in the 1970s.

The logical implication is that Palestinians have no agency whatsoever. That Hamas murders civilians because Israel has ‘structured’ Palestinian reality to make that inevitable. For people presumably wedded to ‘decolonising’ the curriculum, it is a shockingly colonialist premise.

The logic is that Israel is responsible for everything Hamas does because its violence has ‘structured every aspect of Palestinian existence’ since the Nakba.

There are many civilisations, and none is superior or inferior to another. They are equal since each civilisation represents a unique expression of its own culture, traditions, and the aspirations of its people.

In a way, what Putin preaches is an ‘intersectionality of the peoples’: identity politics raised from the level of the individual to the level of the ethnic group.

And it turns out anti-Enlightenment leftism makes it pretty easy to converge with that view. The common assumptions are disdain for universalism, scorn for international law and human rights, repudiation of the Enlightenment (and thus liberalism, social democracy, humanistic Marxism and anarchism) and worship of any totalitarian government that delivers economic development.

This is the modern incarnation of Stalinism, and – to the surprise of nobody who has studied actual Stalinism – it has no problem seeing fascists like Hamas as the ‘agent of progress’.

we need to understand how closely this hyper-deterministic and anti-universal world view maps onto the ideology presented, for example, by Putin at Valdai last week. For Putin there is no single human civilisation, only civilisations, which must be rooted in ethnicity establish their co-existence through the survival of the fittest:

One camp, he said, is a theology. The other a tradition of active reason. The first repudiates liberalism and universalism. The second recognises its debt to liberalism and wants to make universalism consistent

The first claims international law is a sham; the second knows that, though the institutions of the rules-based order are flawed, they are better than chaos.

that you can stand with the Israeli people under attack while simultaneously standing up for the Palestinian people’s right to self-determination.

Those flaunting their joy at the murder of Israeli civilians need to understand the licence this creates in the minds of rightwing ethno-nationalists in our own society. What Hamas did to the kids of Kfar Azar, the far right wants to do to you.

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.

Hirschman was suggesting that doubt could be a source not of paralysis and death but of creativity and self-renewal. One of his last books, published when he was about eighty, is called A Propensity to Self-Subversion. In the title essay, Hirschman celebrates skepticism about his own theories and ideas, and he captures not only the insight but also the pleasure, even the joy, that can come from learning that one had it wrong.

Hirschman’s work changes how you see the world. It illuminates yesterday, today, and tomorrow. His categories become your categories.

Hirschman sought, in his early twenties and long before becoming a writer, to “prove Hamlet wrong.” In Shakespeare’s account, Hamlet is immobilized and defeated by doubt. Hirschman was a great believer in doubt—he never doubted it—and he certainly doubted his own convictions. At a conference designed to celebrate the thirtieth anniversary of his first book, who else would take the opportunity to show that one of his own central arguments was wrong

Who else would publish an essay in The American Economic Review exploring the “overproduction of opinionated opinion,” questioning the value of having strong opinions, and emphasizing the importance of doubting one’s opinions and even one’s tastes? Hirschman thought that strong opinions, as such, “might be dangerous to the health of our democracy,” because they are an obstacle to mutual understanding and constructive problem-solving.

The Rhetoric of Reaction (1991) is a study of the reactionary’s tool kit, identifying the standard objections to any and all proposals for reform. The objections are “perversity” (the reform will make the problem even worse), “futility” (the reform will do nothing to solve the problem), and “jeopardy” (the reform will endanger some hard-won social gain). Hirschman shows that these objections are stupefying, mechanical, hyperbolic, and often wrong

He insisted that human history provides “stories, intricate and often nonrepeatable,” which “look more like tricks history has up its sleeve than like social-scientific regularities, not to speak of laws.” He was interested in “the many might-have-beens of history,” including “felicitous and surprising escapes from disaster.

Hirschman was delighted by paradoxes, unintended consequences (especially good ones), the telling detail, inventories of actual practices (rather than big theories), surprises, and improvisation. In his view, “history is nothing if not farfetched.”

He invented the term “possibilism,” meant to draw attention to “the discovery of paths, however narrow, leading to an outcome that appears to be foreclosed on the basis of probabilistic reasoning alone.” In his lifetime, one of many such outcomes was the abrupt collapse of the Soviet Union in 1989, which almost no one anticipated.

Shifting Involvements—a small masterpiece that illuminates the Tea Party, Occupy Wall Street, and protest movements of diverse kinds. Hirschman emphasized that human beings are often choosing between private and public life, and thus between the different forms of happiness that are associated with each of them. He described “pendular motions of collective behavior,” in which people swing from happiness to disappointment in one kind of activity, and then to the other. For example, the disappointments and frustrations of the student rebellions of the late 1960s encouraged a return to private life in the 1970s and 1980s. Rejecting the highly influential idea that the problem of collective action has a kind of invariable, ahistorical “logic,” Hirschman drew attention to the immense importance of history and timing as, in Adelman’s words, “people leave the streets and plazas disenchanted with politics to seek happiness in the shopping malls”—and vice versa.

The Rhetoric of Reaction, written in his mid-seventies, was an outgrowth of the conservative ascendancy of the 1980s, and it speaks directly to our current debates. Hirschman was struck by the routine, stylized, even mechanical character of much conservative thinking—and its close connection, in its rhetoric, to arguments that have been made for hundreds of years. Indeed, conservative rhetoric is the book’s target, perhaps above all in the person of Edmund Burke,

But if The Passions and the Interests was his favorite, and Exit, Voice, and Loyalty his most important, there can be no question about his most characteristic: The Rhetoric of Reaction. The sustained attack on intransigence, the bias in favor of hope, the delight in paradox, the insistence on the creative power of doubt—all these prove a lot of people wrong, not just Hamlet.

So Ailes came up with a brilliantly cynical strategy. He created a conservative news channel that dispensed with objectivity, and sometimes with facts, while claiming it was more objective — “Fair and Balanced” — than the competition.

Baker believes that most media is hopelessly biased, Journal staffers say. He views his critics as liberal whiners, and his approach as the fair and balanced one.

I happen to agree that liberal bias can be a media problem. On important issues — abortion, education, parenting and religion, to name a few — left-leaning beliefs too often distort coverage. The Journal, and every newspaper, should indeed fight that problem.

But that’s very different from saying reporters protect any political party. They don’t. Journalists’ incentives and instincts all point the other way. Which is why the media reported so aggressively on Hillary Clinton’s emails, damaging her badly.

has there ever been a more important time for sophisticated and fearless financial journalism?

Yet another twist in that geography theme is that it changes meaning with changing technology. The Mediterranean Sea was at first an impediment to travel as were the Atlantic and Pacific Oceans, but once a technology had been created for coping with these natural impediments, they became highways for commerce and war. The same idea can be applied to many other things.

Every summer we watch dozens of villains plotting to blow up the entire universe, but the motivations are always hazy. Why, exactly, does the baddie want to destroy everything again? Now we know.

It’s not just Elon Musk, who stated that ‘there’s a one in a billion chance we’re living in base reality,’ who believes this—in an extraordinary piece of hedge-betting, the Bank of America has judiciously announced that the probability that waking life is just an illusion is, oh, about fifty-fifty

Tech products no longer feel like something offered to the public, but something imposed: The great visionary looks at the way everyone is doing something, and decides, single-handedly, to change it.

once social reality is the exclusive property of a few geegaw-tinkerers, why shouldn’t physical reality be next? With Google’s Calico seeking hedge-fund investment for human immortality and the Transformative Technology Lab hoping to externalize human consciousness, the tech industry is moving into territory once cordoned off for the occult. Why shouldn’t the fate of the entire cosmos be in the hands of programmers hiding from the California sun, to keep or destroy as they wish?

Unsurprisingly, nobody bothered to ask us whether we want the end of the world or not; they’re just setting about trying to do it. Silicon Valley works by solving problems that hadn’t heretofore existed; its culture is pathologically fixated on the notion of ‘disruption.’

Its real antecedents are the Gnostics, an early Christian sect who believed that the physical universe was the creation of the demiurge, Samael or Ialdaboath, sometimes figured as a snake with the head of a lion, a blind and stupid god who creates his false world in imperfect imitation of the real Creator. This world is a distorted mirror, an image; in other words, a kind of software.

Kabbalist mysticists, Descartes with his deceiving demon, and Zhuangzi in his butterfly dream have all questioned the reality of their sense-experiences, but this isn’t a private, solipsistic hallucination; in the simulation hypothesis, reality is a prison for all of us

there’s always been the lingering suspicion that our reality is somehow unreal—it’s just that what we once thought about in terms of dreams and magic, cosmic minds or whispering devils, is now expressed through boring old computers, that piece of clunky hardware that waits predatory on your desk every morning to code the finest details of your life.

The Gnostics were often accused by other early Christians of Satanism, and they might have had a point: Many identified the jealous, petty, prurient God of the Old Testament with the Demiurge, while sects such as the Ophites revered the serpent in the Garden of Eden as the first to offer knowledge to humanity, freeing them from their first cage

In his book, Baudrillard also talks about virtual realities and deceptive images, but his point isn’t that they have clouded our perception of the reality beyond. The present system of social images is so vast and all-encompassing that it’s produced a total reality for itself; it only lies when it has us thinking that there’s something else behind the façade. Baudrillard, always something of an overgrown child, loved to refer to Disneyland: As he pointed out, it’s in no way a fake—when you leave its gates, you return to an America that’s just one giant Disneyland, a copy without an original, from coast to coast

‘The simulacrum is never that which conceals the truth—it is the truth which conceals that there is none.

Digital and cinematic media actively construct our experience of reality. The world of film stars and theme parks, social media and supermarket shelves designed to look like something out of an old-time grocery—this is the one we live in. Our Silicon Valley Satanists have made a very questionable assumption: What if there’s nowhere to break out into?

the virtual is also real. Why is a universe composed of software necessarily any less real than one composed of matter? Computer simulation is of course only a metaphor, a new-ish way of describing what was once expressed in oneiric or theological terms. They can’t really mean that our universe was built in something similar to the machine you’re using to read these words right now;

simulation is a process independent of whatever divine or technological apparatus is used to achieve it. The real argument is that, by some unknown mechanism, what we see is only a function of what really exists. But we’ve known since Kant that our sense-perception can never give us a full account of the material world; all this can be said of any conceivable reality

Outside the simulation hypothesis there are scientists who propose that our universe is a single black hole, with what we perceive as matter being a hologram emerging from a two-dimensional ring of information along its event horizon; there are mathematical Platonists who, following Max Tegmark, consider the world to be a set of abstract mathematical objects, of which physical objects are a crude epiphenomenon. If matter doesn’t ‘really’ exist, there’s no need for anything to be rooted anywhere; we might live suspended in a looping chain of simulations and appearances that coils back on itself and never has to touch the ground

Elon Musk and his co-religionists aren’t actually blinded by artifice; they’re fixated on a strange and outdated notion that somewhere, there has to be a concrete reality—they’ve just decided that it’s not this one

What’s far more worrying is the fact that the people who want to destroy the only world we really have are also the people increasingly in charge of it.

they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it.

The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions.

“Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.”

alls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer.

What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests.

Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research

While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve.

“Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since

Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know,

In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?

But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money.

Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.”

which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.”

these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said.