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China’s support for North Korea dates back to the Korean War (1950–1953)

Bilateral trade increased tenfold between 2000 and 2015, peaking in 2014 at $6.86 billion, according to figures from the Seoul-based Korea Trade-Investment Promotion Agency

In 2018, Chinese imports from North Korea plummeted by 88 percent, while exports dropped by 33 percent. Even in the face of mounting trade restrictions, established informal trade along the China-North Korea border in items such as fuel, seafood, silkworms, and cell phones appears to be ongoing, signaling that China may be softening its restrictions.

China, Japan, South Korea, and the United States have provided more than 75 percent of food aid to North Korea since 1995. North Korea, whose famine in the 1990s killed between eight hundred thousand and 2.4 million people, has repeatedly faced extensive droughts and severe flooding, which seriously damage harvests, threatening the food supply.

China has regarded stability on the Korean Peninsula as its primary interest. Its support for North Korea ensures a buffer between China and the democratic South, which is home to around twenty-nine thousand U.S. troops and marines.

The 1961 Sino-North Korean Treaty of Friendship, Cooperation, and Mutual Assistance, up for renewal in 2021, says China is obliged to intervene against unprovoked aggression.

During their most recent meeting, Xi was welcomed to Pyongyang, marking the first time a Chinese leader visited North Korea since 2005.

Promoted to captain, de Gaulle fought in one of the war's most deadly confrontations — the Battle of Verdun — in 1916. During the fight, he was injured and, subsequently, taken prisoner. After several failed escape attempts, de Gaulle was freed at the end of the war.

A dedicated patriot, de Gaulle did not accept France's surrender to Germany in 1940. He instead fled to England, where he became a leader of the Free French movement, with the support of British prime minister Winston Churchill. From London, de Gaulle broadcast a message across the English Channel to his countrymen, calling for them to continue to resist the German occupation.

He did, however, secure his nation an occupation zone in Germany and a seat on the United Nation's Security Council. De Gaulle enjoyed wide support at home and, in 1945, became president of France's provisional government.

"General de Gaulle is dead. France is a widow." France mourned the loss of its famous statesman and military leader; the country had lost one of its greatest heroes — a hero who had seen his people through war, and proved to be instrumental in his country's recovery.

Mr. Trump has vetoed eight other bills during his time in the White House, with several of them focused on foreign policy and national-security issues, such as U.S. military activity in Yemen, the use of force against Iran, and arms sales to Saudi Arabia. While Republicans had joined Democrats to initially pass those measures, supporters couldn’t muster enough GOP votes to override the vetoes from a Republican president.

Congress has passed a version of the NDAA every year for decades, and it has been one of the most popular pieces of legislation on Capitol Hill. Several other presidents in recent history—including Barack Obama, George W. Bush and Bill Clinton —have vetoed an NDAA, according to the Senate Historical Office. In those instances, Congress modified the bill and the president later signed it.

After Congress pulled together a bipartisan NDAA bill this fall, Mr. Trump repeatedly threatened to veto it

A push to increase the size of direct payments in the $900 billion coronavirus relief bill slowed the process in the Senate, though, as Sen. Bernie Sanders (I., Vt.) prevented leadership from fast-tracking the NDAA vote without a vote on increasing the payments. Mr. Sanders had taken up a request from Mr. Trump to increase the size of the payments to $2,000, up from $600. Republicans have repeatedly blocked a stand-alone vote on that proposal.

In addition to creating a commission for removing or changing names of bases, symbols, displays, monuments and paraphernalia honoring Confederate commanders, the bill also limits the president’s authority to use emergency military construction funds. Other measures in the legislation include requiring companies in the U.S. to register their true owners and restricting employees or former employees of the defense-industrial base from working directly for Chinese government-owned or -controlled companies.

“The U.S.A. is a first-world country but it is acting like a third-world country,” said U Aung Thu Nyein, a political analyst in Myanmar.

Adding to the sense of bewilderment, Mr. Trump has refused to embrace an indispensable principle of democracy, dodging questions about whether he will commit to a peaceful transition of power after the November election should he lose.

“It reminds me of Belarus, when a person cannot admit defeat and looks for any means to prove that he couldn’t lose,” said Kiryl Kalbasnikau, a 29-year-old opposition activist and actor. “This would be a warning sign for any democracy.”

“We used to look to the U.S. for democratic governance inspiration,” said Eduardo Bohórquez, the director of Transparency International Mexico. “Sadly, this is not the case anymore.”

“The world sees the dismantling of social cohesion within American society and the mess in managing Covid,” said Yenny Wahid, an Indonesian politician and activist. “There is a vacuum of leadership that needs to be filled, but America is not fulfilling that leadership role.

Ms. Wahid, whose father was president of Indonesia after the country emerged from decades of strongman rule, said she worried that Mr. Trump’s dismissive attitude toward democratic principles could legitimize authoritarians.

“Trump inspired many dictators, many leaders who are interested in dictatorship, to copy his style, and he emboldened them,” she said.

“They now know what it’s like in other countries: violating norms, international trade and its own institutions,” said Eunice Rendon, an expert on migration and security and the director of Migrant Agenda, a nonprofit organization in Mexico. “The most powerful country in the world all of a sudden looks vulnerable.”

In Cambodia, which reports being largely spared by the virus so far, there is a measure of schadenfreude toward the United States. Prime Minister Hun Sen has survived as Asia’s longest serving leader by cracking down on dissent and cozying up to China.

“He has many nuclear weapons,” Sok Eysan, a spokesman for Mr. Hun Sen’s Cambodian People’s Party, said of Mr. Trump. “But he is careless with a disease that can’t be seen.”

In 2014, the Pew Research Center asked Americans to rank the “greatest dangers in the world.” A plurality put inequality first, ahead of “religious and ethnic hatred,” nuclear weapons, and environmental degradation. And yet people don’t agree about what, exactly, “equality” means.

One side argues that the city should guarantee procedural equality: it should insure that all students and families are equally informed about and encouraged to study for the entrance exam. The other side argues for a more direct, representation-based form of equality: it would jettison the exam, adopting a new admissions system designed to produce student bodies reflective of the city’s demography

In the past year, for example, New York City residents have found themselves in a debate over the city’s élite public high schools

The complexities of egalitarianism are especially frustrating because inequalities are so easy to grasp. C.E.O.s, on average, make almost three hundred times what their employees make; billionaire donors shape our politics; automation favors owners over workers; urban economies grow while rural areas stagnate; the best health care goes to the richest.

It’s not just about money. Tocqueville, writing in 1835, noted that our “ordinary practices of life” were egalitarian, too: we behaved as if there weren’t many differences among us. Today, there are “premiere” lines for popcorn at the movies and five tiers of Uber;

Inequality is everywhere, and unignorable. We’ve diagnosed the disease. Why can’t we agree on a cure?

In a book based on those lectures, “One Another’s Equals: The Basis of Human Equality,” Waldron points out that people are also marked by differences of skill, experience, creativity, and virtue. Given such consequential differences, he asks, in what sense are people “equal”?

According to the Declaration of Independence, it is “self-evident” that all men are created equal. But, from a certain perspective, it’s our inequality that’s self-evident.

More than twenty per cent of Americans, according to a 2015 poll, agree: they believe that the statement “All men are created equal” is false.

In Waldron’s view, though, it’s not a binary choice; it’s possible to see people as equal and unequal simultaneously. A society can sort its members into various categories—lawful and criminal, brilliant and not—while also allowing some principle of basic equality to circumscribe its judgments and, in some contexts, override them

Egalitarians like Dworkin and Waldron call this principle “deep equality.” It’s because of deep equality that even those people who acquire additional, justified worth through their actions—heroes, senators, pop stars—can still be considered fundamentally no better than anyone else.

In the course of his search, he explores centuries of intellectual history. Many thinkers, from Cicero to Locke, have argued that our ability to reason is what makes us equals.

Other thinkers, including Immanuel Kant, have cited our moral sense.

Some philosophers, such as Jeremy Bentham, have suggested that it’s our capacity to suffer that equalizes us

Waldron finds none of these arguments totally persuasive.

In various religious traditions, he observes, equality flows not just from broad assurances that we are all made in God’s image but from some sense that everyone is the protagonist in a saga of error, realization, and redemption: we’re equal because God cares about how things turn out for each of us.

Waldron himself is taken by Hannah Arendt’s related concept of “natality,” the notion that what each of us share is having been born as a “newcomer,” entering into history with “the capacity of beginning something anew, that is, of acting.”

equality may be not a self-evident fact about human beings but a human-made social construction that we must choose to put into practice.

In the end, Waldron concludes that there is no “small polished unitary soul-like substance” that makes us equal; there’s only a patchwork of arguments for our deep equality, collectively compelling but individually limited.

Equality is a composite idea—a nexus of complementary and competing intuitions.

The blurry nature of equality makes it hard to solve egalitarian dilemmas from first principles. In each situation, we must feel our way forward, reconciling our conflicting intuitions about what “equal” means.

The communities that have the easiest time doing that tend to have some clearly defined, shared purpose. Sprinters competing in a hundred-metre dash have varied endowments and train in different conditions; from a certain perspective, those differences make every race unfair.

By embracing an agreed-upon theory of equality before the race, the sprinters can find collective meaning in the ranked inequalities that emerge when it ends

Perhaps because necessity is so demanding, our egalitarian commitments tend to rest on a different principle: luck.

“Some people are blessed with good luck, some are cursed with bad luck, and it is the responsibility of society—all of us regarded collectively—to alter the distribution of goods and evils that arises from the jumble of lotteries that constitutes human life as we know it.” Anderson, in an influential coinage, calls this outlook “luck egalitarianism.”

This sort of artisanal egalitarianism is comparatively easy to arrange. Mass-producing it is what’s hard. A whole society can’t get together in a room to hash things out. Instead, consensus must coalesce slowly around broad egalitarian principles.

No principle is perfect; each contains hidden dangers that emerge with time. Many people, in contemplating the division of goods, invoke the principle of necessity: the idea that our first priority should be the equal fulfillment of fundamental needs. The hidden danger here becomes apparent once we go past a certain point of subsistence.

a core problem that bedevils egalitarianism—what philosophers call “the problem of expensive tastes.”

The problem—what feels like a necessity to one person seems like a luxury to another—is familiar to anyone who’s argued with a foodie spouse or roommate about the grocery bil

The problem is so insistent that a whole body of political philosophy—“prioritarianism”—is devoted to the challenge of sorting people with needs from people with wants

the line shifts as the years pass. Medical procedures that seem optional today become necessities tomorrow; educational attainments that were once unusual, such as college degrees, become increasingly indispensable with time

Some thinkers try to tame the problem of expensive tastes by asking what a “normal” or “typical” person might find necessary. But it’s easy to define “typical” too narrowly, letting unfair assumptions influence our judgment

an odd feature of our social contract: if you’re fired from your job, unemployment benefits help keep you afloat, while if you stop working to have a child you must deal with the loss of income yourself. This contradiction, she writes, reveals an assumption that “the desire to procreate is just another expensive taste”; it reflects, she argues, the sexist presumption that “atomistic egoism and self-sufficiency” are the human norm. The word “necessity” suggests the idea of a bare minimum. In fact, it sets a high bar. Clearing it may require rethinking how society functions.

In conversations with senior staff, Milley reportedly likened Jan. 6 to the 1905 Russian Revolution, which was put down by the Tsar but presaged the successful 1917 revolutions that overthrew the country’s government. “What you might have seen was a precursor to something far worse down the road,” the book quotes him as saying.

Mr Sullivan did not spell out whether the sanctions would include the “nuclear option” of cutting Russia off from the Western financial networks, notably the SWIFT system of financial transfers

“Countries should be able to freely choose who they associate with.” And yet, given the fragility of Ukraine’s government, the widespread corruption in the country and its unresolved conflict, membership of NATO seems a distant if not impossible goal

real problem for Mr Putin may be less Ukraine joining NATO than NATO helping Ukraine

“True sovereignty of Ukraine is possible only in partnership with Russia.”

In 2014 Mr Putin took over and annexed Crimea, and backed Russian-speaking separatists in the east of the country, crushing Ukrainian forces and creating the breakaway republics of Donetsk and Luhansk. The Minsk agreements, intended to end the conflict, would have created a highly decentralised country and, in effect, given Russia a veto over its actions.

he has shut down almost the entire independent media, threatened journalists with up to 15 years in jail if they do not parrot official falsehoods, and had anti-war protesters arrested in their thousands.

Having failed to win a quick victory, Russia is trying to sow panic by starving Ukrainian cities and pounding them blindly.

If Mr Putin is committing war crimes against the fellow Slavs he eulogised in his writings, he is ready to inflict slaughter at home.

even if the war drags on for months, it is hard to see Mr Putin as the victor.

Mr Putin’s puppet could not rule without an occupation, but Russia does not have the money or the troops to garrison even half of Ukraine.

Russia has lost mountains of equipment and endured thousands of casualties, almost as many in two weeks as America has suffered in Iraq since it invaded in 2003.

by attacking Ukraine, Mr Putin has committed a catastrophic error. He has wrecked the reputation of Russia’s supposedly formidable armed forces, which have proved tactically inept against a smaller, worse-armed but motivated opponent.

Western tech firms are wrong to shut their operations in Russia, because they are handing the regime total control over the flow of information.

Mr Putin will not impose a puppet government—because he cannot—then he will have to compromise with Ukraine in peace talks.

Western exporters are withholding vital components, leading to factory stoppages. Sanctions on energy—for now, limited—threaten to crimp the foreign exchange Russia needs to pay for its imports.

Mr Putin is destroying the bourgeoisie, the great motor of Russia’s modernisation. Instead of being sent to the gulag, they are fleeing to cities like Istanbul, in Turkey, and Yerevan, in Armenia.

Those who choose to stay are being muzzled by restrictions on free speech and free association.

Not only is he failing to win a war of choice while impoverishing his people: his regime lacks an ideological core. “Putinism”, such as it is, blends nationalism and orthodox religion for a television audience.

Factions in the regime will turn on each other in a spiral of blame. Mr Putin, fearful of a coup, will trust nobody and may have to fight for power. He may also try to change the course of the war by terrifying his Ukrainian foes and driving off their Western backers with chemical weapons, or even a nuclear strike.

The central bank does not have access to the hard currency it needs to support the banking system and stabilise the rouble.

NATO should state that it will not shoot at Russian forces, so long as they do not attack first. It must not give Mr Putin a reason to draw Russia into a wider war by a declaring no-fly zone that would need enforcing militarily.

Mr Putin is isolated and morally dead; Mr Zelensky is a brave Everyman who has rallied his people and the world. He is Mr Putin’s antithesis—and perhaps his nemesis.

With Trump, evil is always better when it’s also a bargain.

Until as recently as January this year, “62 percent of Republicans and Republican-leaning independents considered Vladimir Putin a stronger leader than Joe Biden.” That’s the primrose path down which the GOP led its supporters — seeing Putin as a more legitimate president than Biden.

Steve Bannon summed it up: “Putin ain’t woke. He’s anti-woke.”

over the years, this drumbeat of love for the Russian dictator shifted the views of many grassroots Republicans. In the wake of Trump’s personal infatuation with Putin, the murderer’s favorability among Republicans jumped from 10 percent in 2014 to 37 percent by December 2016.

For besieged social conservatives and Christianists in America, Putin loomed like some phantasm of strange hope.

The last two weeks, to put it mildly, have pummeled this narrative. It’s happened in a couple of ways. The first is that there really is no legitimate defense — even at CPAC, the fetid armpit of the Trump right — of sending troops and tanks into a neighboring country to teach it a lesson in submission to Mother Russia

If you’re Bannon, you can still try and wing it, but the sheer sight of bombed hospitals, murdered children, homeless seniors, and mortar explosions in residential neighborhoods tends to shape public opinion overnight.

Secondly, and perhaps most important, Putin is failing. He looks weak. The visual of a vast, stalled, vulnerable convoy of trucks on its way — or not — to Kyiv is now a metaphor for Putin’s presidency.

Putin has also done something no US president has been able to do in decades: rally Europe around NATO, get NATO countries to re-arm (finally), and give them a new and pointed mission: the deterrence of Russia

Putin’s blunder has revealed, in fact, that the West has a unique new weapon in the history of global warfare that can end wars almost before they begin: an economic kill-switch. The vast and complex set of financial, economic, and travel sanctions that the West unveiled this past fortnight and is imposing on Russia — effectively removing it from international banking and most international trade — is something no country can survive for very long.

if the EU is able to ramp up nuclear power (as France and Britain are), allow more fracking, and keep its investment in renewables surging, Russia’s entire carbon-based economy will have an expiration date attached to it.

None of this was supposed to happen. The West wasn’t supposed to unite this expeditiously; the EU wasn’t expected to find a new and confident voice; Russia’s access to global finance wasn’t supposed to be severed overnight; and a senile American president wasn’t supposed to corral a massive coalition to marginalize and isolate Russia on the global stage.

“Everything the [far right] wanted to perceive as decadent and weak has proven strong and brave; everything they wanted to represent as fearsome and powerful has revealed itself as brutal and stupid

so a president recently celebrated as a mastermind on the world stage has allowed his ancient fantasies of imperial glory to kick-start his own country’s economic and social collapse. Putin emerges from this as neither smart nor strong; he is, in fact, dumb and increasingly weak.

That’s why he’s a useful insight into what reactionism actually is. It’s not really a politics; it’s a mood. It’s not really about the problems of the present; it’s about living in an imagined past, and believing that you alone can restore it by some mystical rhetorical magic.

It’s about “subscribing to a worldview that combines Orthodox Christian mysticism, anti-American conspiracy theories and hedonism.

Trump longs for the 1950s in America — just as Putin longs for the USSR of the same period

Wrapped up in nationalism, provoked by left-extremism, corralled by skillful demagogues, this longing can be a path to power. It can bring tyrants into office. But it cannot work in practice — because the world is different now. We live in 2022. America will never have the cultural and relative demographic homogeneity of the 1950s again. Never.

“White nationalism” in the most ethnically diverse democracy in human history is a kind of insanity — perpetuated by woke leftists and sad rightists. No wall, no president, no new immigration policy, no mass deportations, no book-bannings and no neo-Nazi rallies will bring it back. It’s gone.

globalization as a whole will not be undone. And because it will not be undone, exclusion from it will effectively remove any country from great power status in the foreseeable future. And so Putin has had his bluff called as well. If the sanctions hold, the danger from Russia henceforth will come from desperation, not ambition.

d this is often the risk of reactionary movements. The backlash they provoke can be lethal to their cause.

If Trudeau tried to freeze the bank accounts of political opponents, the West has chosen to cut an entire country off from global finance — to precipitate its collapse. The scale of this organized global cabal and the immensity of its power should alarm anyone. Putin’s hyper-nationalism has actually generated the most potent globalist power grab since the Cold War. And made it look reasonable.

President Biden has said the goal of U.S. aid is to put Ukraine in the strongest possible position for eventual peace negotiations, without saying under what conditions it should negotiate.

But throughout the war, strengthening Ukraine with decisive firepower has clashed with another, overriding Western priority: to avoid uncontrolled escalation that leads to a direct war with Russia or to Putin using nuclear weapons.

A drawback of the U.S.’s incremental approach to military aid: Without a battlefield breakthrough, Kyiv doesn’t want to negotiate peace—and Moscow doesn’t have to.

“You end up in a strange middle ground where you’re not necessarily able to accomplish that second goal of putting Ukraine in a position of strength that makes negotiations possible.”

The thinking stems from an eagerness to contain a conflict whose shock waves have been felt across the global economy, uncertainty about how long Western voters will support the current levels of aid for Kyiv and disbelief that Ukraine can fully expel Russian forces.

arl von Clausewitz famously wrote that “war is a mere continuation of policy by other means,” stressing that military force is an instrument for attaining a political goal. Some unsuccessful wars have resulted less from lost battles than from the lack of an achievable political aim, so that campaigns came to be seen as draining and fruitless. Modern examples arguably include the Soviet and U.S. failures in Afghanistan and America’s defeat in Vietnam.

Some observers believe the state of war against Ukraine and its Western backers is becoming an end in itself, the raison d’être of a regime that can no longer offer economic growth and stability.

Russia hasn’t given up its maximal goal, pursued in many neighboring countries for years, Polyakova said: to reassert its old sphere of influence and stop countries such as Ukraine from moving further West—whether that means domination or turning them into failed states. The Kremlin’s lesser declared aims are tactical maneuvering

Merkel’s successive governments also squeezed defense budgets while boosting welfare spending. Lt. Gen. Alfons Mais, commander of the army, posted an emotional article on his LinkedIn profile on the day of the invasion, lamenting that Germany’s once-mighty military had been hollowed out to such an extent that it would be all but unable to protect the country in the event of a Russian attack.

her refusal to stop buying energy from Putin after he seized Crimea from Ukraine in 2014—she instead worked to double gas imports from Russia—emboldened him to finish the job eight years later.

Joachim Gauck, who was president of Germany when Putin first invaded Ukraine in 2014, said Merkel’s decision to boost energy imports from Russia in the wake of Putin’s aggression was clearly a mistake. “Some people recognize their mistakes earlier, and some later,” he said.

Since leaving office, Merkel has defended the pipeline project as a purely commercial decision. She had to choose, she said, between importing cheap Russian gas or liquefied natural gas, which she said was a third more expensive.

After Russia’s invasion of Crimea in 2014, Anders Fogh Rasmussen, then NATO secretary general, warned her against making Germany more dependent on a rogue Putin, who had just occupied and annexed part of a European nation. For Putin, he said, the pipeline “had nothing to do with business or the economy—it was a geopolitical weapon.”

Officials who served under Merkel, including Schäuble and Frank-Walter Steinmeier (her former foreign minister and now Germany’s federal president), have apologized or expressed regret for their roles in these decisions. They believe that Merkel’s policies empowered Putin without setting boundaries to his imperial ambitions.

At an event last year, Merkel recalled that after annexing Crimea, Putin had told her that he wanted to destroy the European Union. But she still forged ahead with plans to build the Nord Stream 2 pipeline, linking Germany directly to Siberia’s natural gas fields, in the face of protests from the U.S. Merkel’s government also approved the sale of Germany’s largest gas storage facilities to Russia’s state-controlled gas giant Gazprom.

That mistake had its roots in another decision by Merkel: Her move to greatly accelerate Germany’s planned phasing out of nuclear energy in 2011, in response to the Fukushima disaster in Japan. The gap in energy supply created by this dramatic shift meant that Germany had to import more energy, and it had to do so as cheaply as possible.

Merkel’s role in shaping NATO policy toward Ukraine goes back to 2008, when she vetoed a push by the Bush administration to admit Ukraine and Georgia into the alliance, said Fiona Hill, a former National Security Council official and presidential adviser on Russia.

Merkel instead helped to broker NATO’s open but noncommittal invitation to Ukraine and Georgia, an outcome that Hill said was the “worst of all worlds” because it enraged Putin without giving the two countries any protection. Putin invaded Georgia in 2008 before marching into Ukraine.

After Putin first attacked Ukraine, Merkel led the effort to negotiate a quick settlement that disappointed Kyiv and imposed no substantial punishment on Russia for occupying its neighbor, Hill added. “No red lines were drawn for Putin,” she said. “Merkel took a calculated risk. It was a gambit, but ultimately it failed.”

Merkel still has supporters, and as Germany begins to grapple with her complicated legacy, many still hold a more nuanced view of her role in laying the groundwork for today’s crises

Kaeser, who now chairs the supervisory board of Siemens Energy, a listed subsidiary, agrees that Germany’s dependence on Russian natural gas grew under Merkel, but he says that there was—and is—no alternative for powering Europe’s industrial engine at a viable price.

“We didn’t expect that there would be war in Europe with the methods of the 20th century. This never featured in our thinking,” said Kaeser, who himself met Putin several times. He believes that Merkel’s Russia policy was justified. Even Germany’s new government has not found a sustainable and affordable replacement for Russian energy exports, he said, which could lead to deindustrialization.

Many defenders of Merkel say that she merely articulated a consensus. Making her country dependent on Washington for security, on Moscow for energy and on Beijing for trade (China became Germany’s biggest trade partner under her chancellorship) was what all of Germany’s political parties wanted at the time, said Constanze Stelzenmüller of the Brookings Institution.

“Without backing from the U.S.A., which was very restrained at the time, any tougher German reaction to the annexation of Crimea could hardly have been possible,” said Jürgen Osterhammer, a historian whose work on globalization and China has been cited by Merkel as an influence on her thinking.

In retirement, Merkel told the German news magazine Der Spiegel, she has watched “Munich,” a Netflix movie about Prime Minister Neville’s Chamberlain’s infamous negotiations with Hitler in the run-up to World War II. Though Chamberlain’s name has become synonymous with the delusions of appeasement, the film offers a more nuanced picture of the British leader as a realist statesman working to postpone the inevitable conflict. That reinterpretation appealed to Merkel, the magazine reported.

In April, Merkel was again asked on stage at a book fair whether she would not reconsider her refusal to admit having made some mistakes. “Frankly,” she responded, “I don’t know whether there would be satisfaction if I were to say something that I simply don’t think merely for the sake of admitting error.”

Many of these scholars, he correctly notes, adopted the German model of the research university—but, he claims, only for evil purposes. “As racist ideas jumped off their scholarly pages,” he writes, “American scholars were especially enamored with the German ideal of the disinterested, unbiased pursuit of truth through original scholarly studies, and academic freedom to propagandize African inferiority and European superiority [sic].”

just as Kendi argues in Stamped from the Beginning that the racism of some of the founding fathers irrevocably and permanently brands the United States as a racist nation, he claims that these disciplines cannot be taken seriously because of the racism of some of their founders

Kendi complains in the autobiographical sections of How to Be an Antiracist that his parents often talked the same way to him. Nor does it matter to him that the abolitionists bemoaning the condition of black people under slavery were obviously blaming slavery for it. Any negative picture of any group of black people, to him, simply fuels racism.

Two critical ideas emerge from this article. The first is the rejection of the entire western intellectual tradition on the grounds that it is fatally tainted by racism, and the need for a new academic discipline to replace that tradition.

the second—developed at far greater length in Kendi’s other works—is that anyone who finds European and white North American culture to be in any way superior to the culture of black Americans, either slave or free, is a racist, and specifically a cultural racist or an “assimilationist” who believes that black people must become more like white people if they are to progress.

Kendi, in Stamped from the Beginning, designated Phyllis Wheatley, William Lloyd Garrison, Harriet Beecher Stowe, Sojourner Truth, W. E. B. DuBois, E. Franklin Frazier, Kenneth and Mamie Clark, and other black and white champions of abolition and equal rights as purveyors of racist views. At one time or another, each of them pointed to the backward state of many black people in the United States, either under slavery or in inner-city ghettos, and suggested that they needed literacy and, in some cases, better behavior to advance.

because racism is the only issue that matters to him, he assumes—wrongly—that it was the only issue that mattered to them, and that their disciplines were nothing more than exercises in racist propaganda.

This problem started, he says, “back in the so-called Age of Enlightenment.” Elsewhere he calls the word “enlightenment” racist because it contrasts the light of Europe with the darkness of Africa and other regions.

In fact, the western intellectual tradition of the eighteenth century—the Enlightenment—developed not as an attempt to establish the superiority of the white race, but rather to replace a whole different set of European ideas based on religious faith, the privilege of certain social orders, and the divine right of kings

many thinkers recognized the contradictions between racism and the principles of the Enlightenment—as well as its contradiction to the principles of the Christian religion—from the late eighteenth century onward. That is how abolitionist movements began and eventually succeeded.

Like the last movement of Beethoven’s Ninth Symphony—which has become practically the alternate national anthem of Japan—those principles are not based upon white supremacy, but rather on a universal idea of common humanity which is our only hope for living together on earth.

The western intellectual tradition is not his only target within modern life; he feels the same way about capitalism, which in his scheme has been inextricably bound together with racism since the early modern period.

“To love capitalism,” he says, “is to end up loving racism. To love racism is to end up loving capitalism.” He has not explained exactly what kind of economic system he would prefer, and his advocacy for reparations suggests that he would be satisfied simply to redistribute the wealth that capitalism has created.

Last but hardly least, Kendi rejects the political system of the United States and enlightenment ideas of democracy as well.

I am constantly amazed at how few people ever mention his response to a 2019 Politico poll about inequality. Here it is in full.

To fix the original sin of racism, Americans should pass an anti-racist amendment to the U.S. Constitution that enshrines two guiding anti-racist principals: Racial inequity is evidence of racist policy and the different racial groups are equals. The amendment would make unconstitutional racial inequity over a certain threshold, as well as racist ideas by public officials (with “racist ideas” and “public official”

The DOA would be responsible for preclearing all local, state and federal public policies to ensure they won’t yield racial inequity, monitor those policies, investigate private racist policies when racial inequity surfaces, and monitor public officials for expressions of racist ideas. The DOA would be empowered with disciplinary tools to wield over and against policymakers and public officials who do not voluntarily change their racist policy and ideas.

In other words, to undo the impact of racism as Kendi understands it, the United States needs a totalitarian government run by unaccountable “formally trained experts in racism”—that is, people like Ibram X. Kendi—who would exercise total power over all levels of government and private enterprise

Kendi evidently realizes that the American people acting through their elected representatives will never accept his antiracist program and equalize all rewards within our society, but he is so committed to that program that he wants to throw the American political system out and create a dictatorial body to implement it.

How did a man pushing all these ideas become so popular? The answer, I am sorry to say, is disarmingly simple. He is not an outlier in the intellectual history of the last half-century—quite the contrary.

The Enlightenment, in retrospect, made a bold claim that was bound to get itself into trouble sooner or later: that the application of reason and the scientific method to human problems could improve human life. That idea was initially so exciting and the results of its application for about two centuries were so spectacular that it attained a kind of intellectual hegemony, not only in Europe, but nearly all over the world.

As the last third of the twentieth century dawned, however, the political and intellectual regime it had created was running into new problems of its own. Science had allowed mankind to increase its population enormously, cure many diseases, and live a far more abundant life on a mass scale.

But it had also led to war on an undreamed-of scale, including the actual and potential use of nuclear weapons

As higher education expanded, the original ideas of the Enlightenment—the ones that had shaped the humanities—had lost their novelty and some of their ability to excite.

last but hardly least, the claimed superiority of reason over emotion had been pushed much too far. The world was bursting with emotions of many kinds that could no longer be kept in check by the claims of scientific rationality.

A huge new generation had grown up in abundance and security.

The Vietnam War, a great symbol of enlightenment gone tragically wrong, led not only to a rebellion against American military overreach but against the whole intellectual and political structure behind it.

The black studies movement on campuses that produced Molefi Kete Asante, who in turn gave us Ibram X. Kendi, was only one aspect of a vast intellectual rebellion

Some began to argue that the Enlightenment was simply a new means of maintaining male supremacy, and that women shared a reality that men could not understand. Just five years ago in her book Sex and Secularism, the distinguished historian Joan Wallach Scott wrote, “In fact, gender inequality was fundamental to the articulation of the separation of church and state that inaugurated Western modernity. . . .Euro-Atlantic modernity entailed a new order of women’s subordination” (emphasis in original). Gay and gender activists increasingly denied that any patterns of sexual behavior could be defined as normal or natural, or even that biology had any direct connection to gender. The average graduate of elite institutions, I believe, has come to regard all those changes as progress, which is why the major media and many large corporations endorse them.

Fundamentalist religion, apparently nearly extinct in the mid-twentieth century, has staged an impressive comeback in recent decades, not only in the Islamic world but in the United States and in Israe

Science has become bureaucratized, corrupted by capitalism, and often self-interested, and has therefore lost a good deal of the citizenry’s confidence.

One aspect of the Enlightenment—Adam Smith’s idea of free markets—has taken over too much of our lives.

in the academy, postmodernism promoted the idea that truth itself is an illusion and that every person has the right to her own morality.

The American academy lost its commitment to Enlightenment values decades ago, and journalism has now followed in its wake. Ju

Another aspect of the controversy hasn’t gotten enough attention either. Kendi is a prodigious fundraiser, and that made him a real catch for Boston University.

No matter what happens to Ibram X. Kendi now, he is not an anomaly in today’s intellectual world. His ideas are quite typical, and others will make brilliant careers out of them as well

We desperately need thinkers of all ages to keep the ideas of the Enlightenment alive, and we need some alternative institutions of higher learning to cultivate them once again. But they will not become mainstream any time soon. The last time that such ideas fell off the radar—at the end of the Roman Empire—it took about one thousand years for their renaissance to begin

We do not as individuals have to give into these new ideas, but it does no good to deny their impact. For the time being, they are here to stay.

The problem is never guns. The problem is abortions. (“When you break up the nuclear family, when you tell a generation of people that life has no value, no meaning, then you do wind up with school shooters.”)

The problem is not guns; it is teaching evolution. It is the theories of Charles Darwin! “Because we’ve taught a whole generation — a couple of generations now — of Americans, that there’s no right or wrong, that it’s about survival of the fittest, and [that] you evolve from the primordial slime. Why is that life of any sacred value? Because there’s nobody sacred to whom it’s owed.”

But the problem is never the gun. Hearts stop all the time, for myriad reasons. They are vulnerable to poverty and despair and anxiety, and the United States has all of those in ample supply.

Obviously the problem is the human heart. The human heart cannot stand the strain of living in the United States (a nice place, were it not for the nagging suspicion that any time you gather in a public place you might be gruesomely murdered with a gun). The human heart was not built for this low whine of anxious terror.

The problem is not guns. It’s not weapons. We have to protect ourselves. (From what, Mike? From what?) We must have our guns, to protect ourselves. (Then what are we arming the police like this for? Why are they laden with all this military-grade equipment, if protecting myself is not something I’m supposed to be outsourcing to them?)

The problem is the human heart. It breaks a little bit each time we see another mass shooting. If only they were a harder target. That is the problem. That so many hearts are aching for something to change, for a framework of laws that does not accept gun violence as inevitable.

I had gone to graduate school in Lebanon, then moved back there in an attempt to better understand how Hezbollah had evolved into Israel’s most capable foe. My research revealed as much about Israeli missteps and weaknesses as it did about Hezbollah’s strengths.

If Israel is going to have any strategic success against Hamas, it needs to do three things differently from conflicts past.

Hezbollah took everything Israel could throw at it for a month and was still standing.

As noted earlier, Israel has an unfortunate tendency to lay out maximalist goals—very often for domestic consumption—that it then fails to meet

In 2006, for example, Israel’s then–prime minister, Ehud Olmert, told the country he was going to destroy Hezbollah, return the bodies of two Israeli prisoners, and end the rocket attacks on Israel.

Israel did none of the three. And although Lebanon was devastated, and Hezbollah’s leader, Hassan Nasrallah, publicly apologized for the raid that started the conflict, most observers had little doubt about who had won the conflict.

Strategic Humility

Hezbollah clearly does not want to enter this conflict in any meaningful way. It knows that the pressure will grow to do so if Israel has any real success in Gaza, but for the moment, it doubts that Israel will accomplish any such thing.

Nasrallah addressed the Arabic-speaking world for the first time since the start of this conflict on Friday. Significantly, he declared that although fighting still rages, Hamas became the conflict’s winner as soon as Israel claimed that it would destroy the militant group, which he confidently predicted it would not.

As Eliot Cohen has pointed out, the other side also has maximalist goals. Hamas and Hezbollah want nothing less than the destruction of Israel. But they are in no rush.

that Israel will destroy Hamas. That just isn’t going to happen, especially because no one has any idea who, or what, should replace Hamas in Gaza. So tell the world what will happen—and how it will make Israel and the region safer.

Communications Discipline

One of the things that struck me was the almost profane way in which Israeli military spokespeople would often speak, to international audiences no less, about non-Israeli civilians

“Now we are at the stage in which we are firing into the villages in order to cause damage to property … The aim is to create a situation in which the residents will leave the villages and go north.”

The callousness with which Israeli spokespeople too often describe the human suffering on the other side of the conflict, the blunt way in which they described what many Americans would consider war crimes, never fails to offend international audiences not predisposed to have sympathy with Israeli war aims.

much like right-wing American politicians, who sometimes use inflammatory rhetoric about real or perceived U.S. enemies, Israeli officials often resort to language about adversaries and military operations that can be exceptionally difficult for their allies to defend on the international stage:

One minister casually muses about using nuclear weapons on Gaza; another claims that the Palestinians are a fictional people. One can safely assume that people will continue accusing the Israeli government of including genocidal maniacs when they can point to officials in that government talking like, well, genocidal maniacs.

Israel needs to develop a clear communications plan for its conflicts and to sharply police the kind of language that doesn’t go over as well in Johannesburg or Jordan as it does in Jerusalem.

Focus on Iran

Few people have any interest in a regional war. The economic consequences alone would be dire. But had I been in Israel’s position on October 8, I might have been sorely tempted to largely ignore Gaza—where even the best-trained military would struggle to dislodge Hamas without killing tens of thousands of innocent civilians—and focus my efforts much farther east

Israel nevertheless needs to find a way to change Iran’s strategic calculus. Otherwise, Hamas and Hezbollah will only grow stronger.

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.