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The House vote requires only a simple majority of lawmakers to agree that the president has, in fact, committed high crimes and misdemeanors; the Senate vote requires a two-thirds majority.

The test, as set by the Constitution, is whether the president has committed “treason, bribery, or other high crimes and misdemeanors.”

Impeachment is one of the weightiest tools the Constitution gives Congress to hold government officials, including the president, accountable for misconduct and abuse of power.

The article cites Mr. Trump’s weekslong campaign to falsely discredit the results of the November election, and it quotes directly from the speech he gave on the day of the siege in which he told his supporters to go to the Capitol. “If you don’t fight like hell,” he said, “you’re not going to have a country anymore.”

The article, drafted by Representatives David Cicilline of Rhode Island, Ted Lieu of California, Jamie Raskin of Maryland and Jerrold Nadler of New York, charges Mr. Trump with “incitement of insurrection,” saying he is guilty of “inciting violence against the government of the United States.”

While the House moved with remarkable speed to impeach Mr. Trump, the Senate trial to determine whether to remove him cannot begin until Jan. 19, his final full day in office.

The Senate could hold a trial for Mr. Trump even after he has left office, though there is no precedent for it. Only two presidents other than Mr. Trump have been impeached — Andrew Johnson in 1868 and Bill Clinton in 1998 — and both were ultimately acquitted and completed their terms in office.

Conviction in an impeachment trial would not automatically disqualify Mr. Trump from future public office. But if the Senate were to convict him, the Constitution allows a subsequent vote to bar an official from holding “any office of honor, trust or profit under the United States.”

There is no precedent, however, for disqualifying a president from future office, and the issue could end up before the Supreme Court.

Democrats who control the House can choose when to send their article of impeachment to the Senate, at which point that chamber would have to immediately move to begin the trial. But because the Senate is not scheduled to hold a regular session until Jan. 19, even if the House immediately transmitted the charge to the other side of the Capitol, an agreement between Senate Republican and Democratic leaders would be needed to take it up before then.

Once the Senate receives the impeachment charge, it must immediately take up the issue, as articles of impeachment carry the highest privilege.

Democrats have argued that Mr. Trump’s offense — using his power as the nation’s leader and commander in chief to incite an insurrection against the legislative branch — is so grave that it must be addressed, even with just a few days remaining in his term.

With only a week left in his term, the House impeached President Trump, but he will leave office before he stands trial in the Senate. Here’s how the process works.

The charge against Trump is ‘incitement of insurrection.’

That vote would require only a simple majority of senators. Such a step could be an appealing prospect not just to Democrats, but also to many Republicans who either have set their sights on the presidency themselves or are convinced that it is the only thing that will purge Mr. Trump from their party. Senator Mitch McConnell of Kentucky, the Republican leader, is said to hold the latter view.

Self-determination, the rule of law between and within countries, liberal economics, and the protection of human rights: the “new world order” that both the George H. W. Bush and the Clinton administrations worked to create was very much in the Wilsonian mold. 

When the Berlin Wall fell, in 1989, it seemed that the opportunity for a Wilsonian world order had finally come. The former Soviet empire could be reconstructed along Wilsonian lines, and the West could embrace Wilsonian principles more consistently now that the Soviet threat had disappeared.

American leaders during and after World War II laid the foundations of what they hoped would be a Wilsonian world order, in which international relations would be guided by the principles put forward in the Universal Declaration of Human Rights and conducted according to rules established by institutions such as the United Nations, the International Court of Justice, and the World Trade Organization.

the order of things

The next stage in world history will not unfold along Wilsonian lines. The nations of the earth will continue to seek some kind of political order, because they must. And human rights activists and others will continue to work toward their goals. But the dream of a universal order, grounded in law, that secures peace between countries and democracy inside them will figure less and less in the work of world leaders. 

Although Wilsonian ideals will not disappear and there will be a continuing influence of Wilsonian thought on U.S. foreign policies, the halcyon days of the post–Cold War era, when American presidents organized their foreign policies around the principles of liberal internationalism, are unlikely to return anytime soon. 

Today, however, the most important fact in world politics is that this noble effort has failed.

Wilsonianism is only one version of a rules-based world order among many.

the pre-Wilsonian European order had moved significantly in the direction of elevating human rights to the level of diplomacy. 

The preservation of the balance of power was invoked as a goal to guide states; war, although regrettable, was seen as a legitimate element of the system. From Wilson’s standpoint, these were fatal flaws that made future conflagrations inevitable. To redress them, he sought to build an order in which states would accept enforceable legal restrictions on their behavior at home and their international conduct. 

Although Wilson was an American, his view of world order was first and foremost developed as a method for managing international politics in Europe, and it is in Europe where Wilson’s ideas have had their greatest success and where their prospects continue to look strongest.

His ideas were treated with bitter and cynical contempt by most European statesmen when he first proposed them, but they later became the fundamental basis of the European order, enshrined in the laws and practices of the EU.

the arc of history

The real problem of Wilsonianism is not a naive faith in good intentions but a simplistic view of the historical process, especially when it comes to the impact of technological progress on human social order.

Wilson was the devout son of a minister, deeply steeped in Calvinist teachings about predestination and the utter sovereignty of God, and he believed that the arc of progress was fated

he shared the optimism of what the scholar Herbert Butterfield called “the Whig historians,” the Victorian-era British thinkers who saw human history as a narrative of inexorable progress and betterment. Wilson believed that the so-called ordered liberty that characterized the Anglo-American countries had opened a path to permanent prosperity and peace.

Today’s Wilsonians have given this determinism a secular twist: in their eyes, liberalism will rule the future and bring humanity to “the end of history” as a result of human nature rather than divine purpose

In the early 1990s, leading U.S. foreign policymakers and commentators saw the fall of the Soviet Union through the same deterministic prism: as a signal that the time had come for a truly global and truly liberal world order. On all three occasions, Wilsonian order builders seemed to be in sight of their goal. But each time, like Ulysses, they were blown off course by contrary winds. 

Technical difficulties Today, those winds are gaining strength. Anyone hoping to reinvigorate the flagging Wilsonian project must contend with a number of obstacles

The most obvious is the return of ideology-fueled geopolitics. China, Russia, and a number of smaller powers aligned with them—Iran, for example—correctly see Wilsonian ideals as a deadly threat to their domestic arrangements.

Seeing Wilsonianism as a cover for American and, to some degree, EU ambitions, Beijing and Moscow have grown increasingly bold about contesting Wilsonian ideas and initiatives inside international institutions such as the UN and on the ground in places from Syria to the South China Sea.

These powers’ opposition to the Wilsonian order is corrosive in several ways.

It raises the risks and costs for Wilsonian powers to intervene in conflicts beyond their own borders.

The presence of great powers in the anti-Wilsonian coalition also provides shelter and assistance to smaller powers that otherwise might not choose to resist the status quo

Finally, the membership of countries such as China and Russia in international institutions makes it more difficult for those institutions to operate in support of Wilsonian norms: take, for example, Chinese and Russian vetoes in the UN Security Council, the election of anti-Wilsonian representatives to various UN bodies, and the opposition by countries such as Hungary and Poland to EU measures intended to promote the rule of law. 

Biological and technological research, by contrast, are critical for any country or company that hopes to remain competitive in the twenty-first century. An uncontrollable, multipolar arms race across a range of cutting-edge technologies is on the horizon, and it will undercut hopes for a revived Wilsonian order. 

The irony is that Wilsonians often believe that technological progress will make the world more governable and politics more rational—even if it also adds to the danger of war by making it so much more destructive. Wilson himself believed just that, as did the postwar order builders and the liberals who sought to extend the U.S.-led order after the Cold War. Each time, however, this faith in technological change was misplaced

As seen most recently with the rise of the Internet, although new technologies often contribute to the spread of liberal ideas and practices, they can also undermine democratic systems and aid authoritarian regimes.

Meanwhile, the torrent of technological innovation and change known as “the information revolution” creates obstacles for Wilsonian goals

It also makes it harder for national leaders to pursue the compromises that international cooperation inevitably requires and increases the chances that incoming governments will refuse to be bound by the acts of their predecessors. 

Wilsonians prioritize arms control not just because nuclear warfare could destroy the human race but also because, even if unused, nuclear weapons or their equivalent put the Wilsonian dream of a completely rules-based, law-bound international order out of reach. Weapons of mass destruction guarantee exactly the kind of state sovereignty that Wilsonians think is incompatible with humanity’s long-term security. One cannot easily stage a humanitarian intervention against a nuclear power. 

What is more, the technological progress that underlies the information revolution significantly exacerbates the problem of arms control. The development of cyberweapons and the potential of biological agents to inflict strategic damage on adversaries—graphically demonstrated by the COVID-19 pandemic—serve as warnings that new tools of warfare will be significantly more difficult to monitor or control than nuclear technology.

Today, as new technologies disrupt entire industries, and as social media upends the news media and election campaigning, politics is becoming more turbulent and polarized in many countries.

it’s not for everybody One of the central assumptions behind the quest for a Wilsonian order is the belief that as countries develop, they become more similar to already developed countries and will eventually converge on the liberal capitalist model that shapes North America and western Europe

The Wilsonian project requires a high degree of convergence to succeed; the member states of a Wilsonian order must be democratic, and they must be willing and able to conduct their international relations within liberal multilateral institutions. 

Today, China, India, Russia, and Turkey all seem less likely to converge on liberal democracy than they did in 1990. These countries and many others have developed economically and technologically not in order to become more like the West but rather to achieve a deeper independence from the West and to pursue civilizational and political goals of their own. 

In truth, Wilsonianism is a particularly European solution to a particularly European set of problems

With the specter of great-power war constantly hanging over them, European states developed a more intricate system of diplomacy and international politics than did countries in other parts of the world.

Although it would take another devastating world war to ensure that Germany, as well as its Western neighbors, would adhere to the rules of a new system, Europe was already prepared for the establishment of a Wilsonian order.

The idea of a single legitimate state with no true international peers is as deeply embedded in the political culture of China as the idea of a multistate system grounded in mutual recognition is embedded in that of Europe. There have been clashes among Chinese, Japanese, and Koreans, but until the late nineteenth century, interstate conflict was rare. 

In human history as a whole, enduring civilizational states seem more typical than the European pattern of rivalry among peer states.

For states and peoples in much of the world, the problem of modern history that needed to be solved was not the recurrence of great-power conflict. The problem, instead, was figuring out how to drive European powers awa

International institutions face an even greater crisis of confidence. Voters skeptical of the value of technocratic rule by fellow citizens are even more skeptical of foreign technocrats with suspiciously cosmopolitan views

After colonialism formally ended and nascent countries began to assert control over their new territories, the classic problems of governance in the postcolonial world remained weak states and compromised sovereignty. 

expert texpert

The recent rise of populist movements across the West has revealed another danger to the Wilsonian project. If the United States could elect Donald Trump as president in 2016, what might it do in the future? What might the electorates in other important countries do? And if the Wilsonian order has become so controversial in the West, what are its prospects in the rest of the world?

Postcolonial and non-Western states often joined international institutions as a way to recover and enhance their sovereignty, not to surrender it, and their chief interest in international law was to protect weak states from strong ones, not to limit the power of national leaders to consolidate their authority

Yet from the standpoint of Wilson and his fellow progressives, the solution to these problems could not be simply to vest power in the voters. At the time, most Americans still had an eighth-grade education or less

The progressives’ answer to this problem was to support the creation of an apolitical expert class of managers and administrators. The progressives sought to build an administrative state that would curb the excessive power of the rich and redress the moral and political deficiencies of the poor.

The Internet and social media have undermined respect for all forms of expertise. Ordinary citizens today are significantly better educated and feel less need to rely on expert guidance. And events including the U.S. invasion of Iraq in 2003, the 2008 financial crisis, and the inept government responses during the 2020 pandemic have seriously reduced confidence in experts and technocrats, whom many people have come to see as forming a nefarious “deep state.”

Wilson lived in an era when democratic governance faced problems that many feared were insurmountable. The Industrial Revolution had divided American society, creating unprecedented levels of inequality.

when it comes to international challenges such as climate change and mass migration, there is little evidence that the cumbersome institutions of global governance and the quarrelsome countries that run them will produce the kind of cheap, elegant solutions that could inspire public trust. 

what it means for biden

For all these reasons, the movement away from the Wilsonian order is likely to continue, and world politics will increasingly be carried out along non-Wilsonian and in some cases even anti-Wilsonian lines

the international order will increasingly be shaped by states that are on diverging paths. This does not mean an inevitable future of civilizational clashes, but it does mean that global institutions will have to accommodate a much wider range of views and values than they have in the past.

Non-Wilsonian orders have existed both in Europe and in other parts of the world in the past, and the nations of the world will likely need to draw on these examples as they seek to cobble together some kind of framework for stability and, if possible, peace under contemporary conditions. 

For U.S. policymakers, the developing crisis of the Wilsonian order worldwide presents vexing problems that are likely to preoccupy presidential administrations for decades to come. One problem is that many career officials and powerful voices in Congress, civil society organizations, and the press deeply believe not only that a Wilsonian foreign policy is a good and useful thing for the United States but also that it is the only path to peace and security and even to the survival of civilization and humanity.

Those factions will be hemmed in by the fact that any internationalist coalition in American foreign policy must rely to a significant degree on Wilsonian voters. But a generation of overreach and poor political judgment has significantly reduced the credibility of Wilsonian ideas among the American electorate.

But American foreign policy is always a coalition affair. As I wrote in my book Special Providence, Wilsonians are one of four schools that have contended to shape American foreign policy since the eighteenth century.

Hamiltonians and Wilsonians largely dominated American foreign-policy making after the Cold War, but Obama began to reintroduce some Jeffersonian ideas about restraint, and after the Libyan misadventure, his preference for that approach clearly strengthened.

Trump, who hung a portrait of President Andrew Jackson in the Oval Office, sought to build a nationalist coalition of Jacksonians and Jeffersonians against the globalist coalition of Hamiltonians and Wilsonians that had been ascendant since World War II. 

Even as the Biden administration steers American foreign policy away from the nationalism of the Trump period, it will need to re-adjust the balance between the Wilsonian approach and the ideas of the other schools in light of changed political conditions at home and abroad.

Saving the planet from a climate catastrophe and building a coalition to counter China are causes that many Wilsonians will agree both require and justify a certain lack of scrupulosity when it comes to the choice of both allies and tactics. 

The Biden administration can also make use of other techniques that past presidents have used to gain the support of Wilsonians

Even as the ultimate goals of Wilsonian policy become less achievable, there are particular issues on which intelligent and focused American policy can produce results that Wilsonians will like

International cooperation to make money laundering more difficult and to eliminate tax havens is one area where progress is possible.

Concern for international public health will likely stay strong for some years after the COVID-19 pandemic has ended.

Promoting education for underserved groups in foreign countries—women, ethnic and religious minorities, the poor—is one of the best ways to build a better world,

however problematic Wilson’s personal views and domestic policies were, as a statesman and ideologist, he must be counted among the most influential makers of the modern world

Kevin D. Greeson, 55, of Athens, Ala., was standing in a throng of fellow Trump loyalists on the west side of the Capitol when he suffered a heart attack and fell to the sidewalk. He was talking on the phone with his wife at the time.

Rosanne Boyland, 34, of Kennesaw, Ga., posted fervently in support of President Trump on social media, followed the baseless conspiracy theories of QAnon and latched onto Mr. Trump’s false claims that he had won the election, family members told The Associated Press.

How she died remained unclear on Monday

Mr. Philips died of a stroke in Washington, those who accompanied him to the Capitol told the newspaper. The exact circumstances of his death were still unclear, and his family could not be reached for comment.

A police officer was beaten, a rioter was shot, and three others died during the rampage.

One had dreamed of becoming a police officer and was injured in a clash with rioters. One was an Air Force veteran and a fervent supporter of President Trump who was shot by the police. Three others were Trump loyalists — including one who sold kangaroos dressed like the president — who suffered what the authorities called “medical emergencies.”

Law enforcement officials said he had been “physically engaging with protesters” and was struck in the head with a fire extinguisher.

Her last moments, captured from multiple angles on video, show Ms. Babbitt, a Trump flag knotted around her neck, being hoisted to the window as others in the mob shout. Moments later, a shot rings out and Ms. Babbitt falls back, blood pouring from her mouth

Mr. Greeson had high blood pressure and she had not wanted him to travel to Washington. But she said Mr. Greeson believed the election had been stolen and saw the Jan. 6 rally as “a monumental event.”

Mr. Giuliani expressed frustration with the way the news media was keeping its distance, and said he would have preferred to have pushed out the materials earlier.“I would have loved to have had this six months ago,” he said in a recent interview. “It would have solved a lot of my problems.”

Mr. Guo and Mr. Bannon began working together after Mr. Bannon left the White House in 2017, quickly bonding over their mutual antipathy toward the Chinese Communist Party.

Mr. Guo, who is also known as Miles Kwok, left China in 2014, as the government there began leveling corruption allegations against his business associates and eventually Mr. Guo. He moved to New York, buying a $67.5 million apartment along Central Park and spending time aboard the Lady May.

Mr. Bannon asserted that the effort to limit the spread of the New York Post’s articles on social media had backfired, drawing more attention to them. “Social media overplayed this and did us a favor,” Mr. Bannon said.

At the same time Mr. Bannon and Mr. Giuliani were shopping the purported hard drive, two other efforts were afoot to disseminate related information on Hunter Biden.

the First Step Act would release more than 3,100 federal prison inmates and said its retroactive sentencing reform had led to nearly 1,700 sentence reductions. The Sentencing Project said last year that Black Americans made up 91 percent of everyone receiving reductions.

Trump reinstituted the federal death penalty. Seven people have been executed this year under the policy — five were white, one was Native American and the other was Black. And there are 55 federal death-row prisoners. Twenty-five are African Americans, 22 are white, seven are Latino and one is Asian.

Under the Trump administration, the Black unemployment rate steadily improved, dropping to 5.4 percent at its bottom in August 2019, compared to 7.5 percent when Trump took office in January 2017. But that achievement is attributable to economic growth that was already revving when Trump took office, economists say.

Black workers did not see employment levels ever go “above the trend.”

The bill is a 10-year renewal of funding. During Obama’s eight years in office, mandatory HBCU funding ranged from almost $80 million to $85 million per year. The same has been true during Trump’s administration.

Even with record-low unemployment rates in 2019, Black Americans still had fewer jobs than their white counterparts — even for those with college or advanced degrees — according to research by EPI.

In April, when unemployment peaked at 14.7 percent — the highest level seen since the Great Depression — the unemployment rate for Black workers was even higher, at 16.7 percent. By September, the share of unemployed Black workers still struggling to find a job only dropped to 12.1 percent.

Many banks limited their initial application pool for the small business rescue Paycheck Protection Program to previous customers, a staff report by the House coronavirus subcommittee found. Democrats and non-profits argue that shut out many minority-owned businesses that lacked business banking relationships from the program, which offered forgivable loans to companies that kept their workers on the payroll.

when the labor market is tight, like it was in first three years of the Trump administration, discrimination tends to decline.

The amount of funding for HBCUs is “the same thing that we had under President Obama.”

creating “more than 8,000 opportunities zones, bringing jobs and opportunities to our inner-city families.”

Opportunity zones “are tax incentives to encourage those with capital gains to invest in low-income and undercapitalized communities,” according to the Tax Policy Center.

A feature of the president’s $1.5 trillion tax cuts, the program was intended to benefit Black, Hispanic and low-income communities. But there’s very little data about what’s actually happening in opportunity zones. There isn’t a full accounting of the number of opportunity zone projects, let alone basic information such as what those projects are, why they’re being pursued and who is benefiting from them.

the vast majority of opportunity zone capital appears to be going into real estate rather than operating businesses, meaning that the opportunity zones aren’t creating sustainable, long-term jobs.

he scrapped an Obama rule requiring localities to track patterns of segregation or lose federal funding.

The U.S. Department of Housing and Urban Development replaced the 2015 Affirmatively Furthering Fair Housing Act with a much weaker rule in July, using a waiver to exempt the new regulation from public-comment requirements. Public comments allow people to weigh in on proposed rules before they’re finalized. But by bypassing that critical step, the agency essentially expedited a months-long process without any public input.

baseless fear of crime and decreased property value as attempted triggers to get at white anxiety about living with people of color — and African Americans in particular — and the idea of integration itself,”

new rule in September overhauling the Obama administration’s 2013 “disparate impact” rule. The new rule would have required plaintiffs to meet a higher threshold to prove unintentional discrimination — known as disparate impact — and given defendants more leeway to rebut the claims.

A federal court intervened this month -- the day before the rule was set to take effect last week -- issuing a preliminary nationwide injunction to bar HUD from implementing the new regulation until the merits of a lawsuit brought by civil rights advocates have been decided.

Election experts have calculated that, in a 20-year period, fraud involving mailed ballots has affected 0.00006 percent of individual votes, or one case per state every six or seven years.

Among the billions of votes cast from 2000 to 2012, there were 491 cases of absentee-ballot fraud, according to an investigation conducted at Arizona State University’s journalism schoo

intentional voter fraud is extremely uncommon and rarely organized, according to decades of research.

In June, The Washington Post and the nonprofit Electronic Registration information Center analyzed data from three vote-by-mail states and found 372 possible cases of double voting or voting on behalf of dead people in 2016 and 2018, or 0.0025 percent of the 14.6 million mailed ballots.

Mr. Trump’s effort to discredit mail-in voting follows decades of disinformation about voter impersonation, voting by noncitizens and double voting, often promoted by Republican leaders.

Voting by mail under normal circumstances does not appear to give either major party an advantage, according to a study this spring by Stanford University’s Institute for Economic Policy Research.

But many conservative outlets have promoted the idea that fraud involving mailed ballots could tip the scales in favor of Democrats.

Mr. Stedman said right-leaning outlets sometimes conflated fraud with the statistically insignificant administrative mishaps that occur in every American election

In a similar cycle, the Fox News host Sean Hannity and conservative publications magnified the reach of a deceptive video released last month by Project Veritas, a group run by the conservative activist James O’Keefe. The video claimed without named sources or verifiable evidence that the campaign for Representative Ilhan Omar, a Minnesota Democrat, was collecting ballots illegally.

Stephen J. Stedman, a senior fellow at the Freeman Spogli Institute for International Studies at Stanford, said he thought “about disinformation in this country as almost an information ecology — it’s not an organic thing from the bottom up.”

Breitbart, The Washington Examiner and others amplify false claims of rampant cheating in what a new Harvard study calls a “propaganda feedback loop.”

The Washington Examiner, Breitbart News, The Gateway Pundit and The Washington Times are among the sites that have posted articles with headlines giving weight to the conspiracy theory that voter fraud is rampant and could swing the election to the left, a theory that has been repeatedly debunked by data.

“EXCLUSIVE: California Man Finds THOUSANDS of What Appear to be Unopened Ballots in Garbage Dumpster — Workers Quickly Try to Cover Them Up — We are Working to Verify.” The envelopes turned out to be empty and discarded legally in 2018. Gateway Pundit later updated the headline, but not before its original speculation had gone viral.

Pennsylvania’s elections chief that the discarded ballots were a “bad error” by a seasonal contractor, not “intentional fraud.” Mr. Trump cited the discarded Pennsylvania ballots several times as an example of fraud, including in last month’s presidential debate.

“FEDS: Military Ballots Discarded in ‘Troubling’ Discovery. All Opened Ballots were Cast for Trump.” Headlines on the same issue in The Washington Times were similar: “Feds investigating discarded mail-in ballots cast for Trump in Pennsylvania” and “FBI downplays election fraud as suspected ballot issues found in Pennsylvania, Texas.” A Washington Times opinion piece on the matter had the headline “Trump ballots in trash, oh my.”

“DESTROYED: Tons of Trump mail-in ballot applications SHREDDED in back of tractor-trailer headed for Pennsylvania.” The material was actually printing waste from a direct mail company.

RIGGED ELECTION!” He linked to a Breitbart article that included a transcript of Attorney General William P. Barr’s telling the Fox News host Maria Bartiromo that voting by mail “absolutely opens the floodgates to fraud.”

West Wing aides, shaken by polls showing the president badly trailing Joseph R. Biden Jr., worried that they were living through the final days of the Trump administration

Late in the day, the stock market collapsed when Mr. Trump abruptly called off talks for a congressional coronavirus relief bill after the Fed chair, Jerome H. Powell, said such a stimulus was badly needed.

Some White House staff members wondered whether Mr. Trump’s behavior was spurred by a cocktail of drugs he has been taking to treat the coronavirus, including dexamethasone, a steroid that can cause mood swings and can give a false level of energy and a sense of euphoria.

Prominent supporters of the administration said Mr. Trump should have stayed at the hospital until he was no longer infectious or should remain confined to his residence.

There were no answers, either, on when Mr. Trump last tested negative for the virus — a crucial piece of information that the White House and Dr. Conley have refused to answer and would establish the known state of Mr. Trump’s health before the presidential debate last Tuesday or before he attended a fund-raiser in New Jersey on Thursday. The White House first made public that Mr. Trump had tested positive early last Friday.

he intends to banish to the sunken place longstanding doctrines protecting the right to vote. But Kavanaugh, at the very least, rejects some parts of the nihilistic approach shared by Justices Clarence Thomas, Samuel Alito, and Neil Gorsuch.

her approach to constitutional questions resembles that of Thomas and Gorsuch. Chief Justice John Roberts, who is himself frequently hostile to voting rights law, has written that he thinks his conservative colleagues are going too far i

was most visible in Andino v. Middleton, a recent decision that reinstated a South Carolina law requiring absentee voters to have another person sign their ballot as a witness.

he did not embrace the extreme position of Justices Thomas, Alito, and Gorsuch,

Kavanaugh handed down another opinion suggesting that, while he is not as hostile to voting rights as his most conservative colleagues, he still wants to make radical changes that would profoundly impact American democracy.

appears to be torn between a belief that well-established rules governing election disputes should be abandoned, and a competing understanding that it is unfair to disenfranchise voters who followed the rules that were in place at the time when those voters cast their ballots.

Purcell v. Gonzales (2006), a case which — at least according to Kavanaugh — established that “federal courts ordinarily should not alter state election rules in the period close to an election.”

“The Constitution ‘principally entrusts the safety and the health of the people to the politically accountable officials of the States,’” Kavanaugh wrote. Therefore, “it follows that a State legislature’s decision either to keep or to make changes to election rules to address COVID–19 ordinarily ‘should not be subject to second-guessing by an ‘unelected federal judiciary,’

Let state legislatures decide how elections will be conducted in each state, for better or for worse. And don’t intervene even if those decisions are likely to disenfranchise voters.

that the Supreme Court should take unprecedented steps to overrule state judges and other state officials who try to make it easier to vote. But he also did not join a recent opinion by Alito that suggested that the Court may step in after the election to toss out ballots

Thomas, Alito, and Gorsuch took the extraordinary position that voters who failed to anticipate that the Supreme Court would change the rules after their unwitnessed ballot was already cast should have their ballots tossed out.

Democratic National Committee v. Wisconsin State Legislature, a case that determined that ballots that arrive after Election Day in Wisconsin shall not be counted, Kavanaugh pointed to a provision of the Constitution that provides that “the rules for Presidential elections are established by the States ‘in such Manner as the Legislature thereof may direct.’”

“in accordance with the State’s prescriptions for lawmaking, which may include the referendum and the Governor’s veto.”

the Supreme Court of the United States has the final word on questions of federal law, but state supreme courts have the final say on questions of their own state’s law.

It could mean that a state governor cannot veto a state election law (because the governor is not the “legislature”). Or that a state constitution may not empower an independent commission to draw un-gerrymandered legislative maps (because the commission is not the “legislature”).

Kavanaugh appears to be largely indifferent to voting rights, and is willing to give state legislatures a great deal of leeway to disenfranchise voters.

On Wednesday night, the Supreme Court handed down orders in Republican Party of Pennsylvania v. Boockvar and Moore v. Circosta, which concern whether late-arriving ballots should be counted in Pennsylvania and North Carolina. In both cases, state officials — but not the state legislature — decided that ballots that are mailed before Election Day and that arrive during a brief window after the election should be counted.

but they didn’t exactly tell the GOP “no,” either. The Court denied the GOP’s request to order, in advance of the election, that late-arriving ballots will not be counted. But an ominous opinion by Alito suggests that the Court might revisit this question after the election.

Alito wrote in a concurring opinion in Republican Party, which was joined by Thomas and Gorsuch. Nevertheless, he added that the case “remains before us” and could be decided “under a shortened schedule” after the election takes place.

Voters, in other words, might mail their ballots close to Election Day, believing that they can rely on state officials and lower courts that have said that these ballots will be counted, only to have the Supreme Court change the rules after the election is over — and order these ballots tossed out.

But Kavanaugh hasn’t yet shown the same willingness to disenfranchise people who followed the rules — or, at least, who followed the rules that were in place when those voters cast their ballots.

It may be a Biden blowout, or a fair-and-square Trump win. But if it’s close, and if Pennsylvania or North Carolina is pivotal, these are the competing considerations that Kavanaugh, likely the swing vote, will be wrestling with.

The alert also ramped up the urgency of government warnings. After playing the incident down — President Trump has said nothing and Secretary of State Mike Pompeo deflected the hacking as one of the many daily attacks on the federal government,

President Biden first announced the rules in September as part of a broader strategy from his administration to combat the spread of the Delta variant, which drove a surge of infections toward the end of the summer. 

The Supreme Court was asked to intervene last month and swiftly held oral arguments to weigh the emergency requests.

"As a result of the court's decision, it is now up to states and individual employers to determine whether to make their workplaces as safe as possible for employees, and whether their businesses will be safe for consumers during this pandemic by requiring employees to take the simple and effective step of getting vaccinated," Mr. Biden said. "The court has ruled that my administration cannot use the authority granted to it by Congress to require this measure, but that does not stop me from using my voice as president to advocate for employers to do the right thing to protect Americans' health and economy."

The Biden administration estimated that more than 80 million employees could be impacted by the policy.

The Supreme Court received more than a dozen requests for emergency action in cases challenging the requirement after the 6th U.S. Circuit's ruling, with business associations, Republican-led states and private businesses covered by the rule arguing OSHA lacked the power to issue the vaccine requirement.

"Permitting OSHA to regulate the hazards of daily life — simply because most Americans have jobs and face those same risks while on the clock — would significantly expand OSHA's regulatory authority without clear congressional authorization," the court said.

The second rule examined by the Supreme Court was issued by the Centers for Medicare and Medicaid Services (CMS) in November and laid out vaccine requirements for staff at a wide range of facilities that participate in Medicare and Medicaid. The requirement does not have a daily or weekly testing option for unvaccinated workers, but does include medical and religious exemptions.

. Then, in a separate case brought by 14 states, a federal district court in Louisiana blocked the rule from taking effect nationwide, but the 5th Circuit narrowed the scope of the order to the 14 states that together sued the Biden administration. 

"After all, ensuring that providers take steps to avoid transmitting a dangerous virus to their patients is consistent with the fundamental principle of the medical profession: first, do no harm," the Supreme Court said.

"The omnibus rule is undoubtedly significant — it requires millions of healthcare workers to choose between losing their livelihoods and acquiescing to a vaccine they have rejected for months. Vaccine mandates also fall squarely within a state's police power, and, until now, only rarely have been a tool of the federal government," Thomas wrote. "If Congress had wanted to grant CMS authority to impose a nationwide vaccine mandate, and consequently alter the state-federal balance, it would have said so clearly. It did not."

Last month, President Biden’s trade representative, Katherine Tai, notified the World Trade Organization that the American government no longer supported a proposal it once spearheaded that would have exported the American laissez-faire approach to tech. Had that proposal been adopted, it would have spared tech companies the headache of having to deal with many different domestic laws about how data must be handled, including rules mandating that it be stored or analyzed locally. It also would have largely shielded tech companies from regulations aimed at protecting citizens’ privacy and curbing monopolistic behavior.

The move to drop support for that digital trade agenda has been pilloried as disaster for American companies and a boon to China, which has a host of complicated restrictions on transferring data outside of China. “We have warned for years that either the United States would write the rules for digital trade or China would,” Senator Mike Crapo, a Republican from Idaho, lamented in a press statement. “Now, the Biden administration has decided to give China the pen.”

While some of this agenda is reasonable and good for the world — too much regulation stifles innovation — adopting this agenda wholesale would risk cementing the advantages that big American tech companies already enjoy and permanently distorting the market in their favor.

who used to answer the phone and interact with lobbyists at the U.S. trade representative’s office. The paper includes redacted emails between Trump-era trade negotiators and lobbyists for Facebook, Google, Microsoft and Amazon, exchanging suggestions for the proposed text for the policy on digital trade in the United States-Mexico-Canada Agreement. “While they were previously ‘allergic to Washington,’ as one trade negotiator described, over the course of a decade, technology companies hired lobbyists and joined trade associations with the goal of proactively influencing international trade policy,” Ms. Li wrote in the Socio-Economic Review.

That paper explains how U.S. trade officials came to champion a digital trade policy agenda that was nearly identical to what Google, Apple and Meta wanted: No restrictions on the flow of data across borders. No forced disclosure of source codes or algorithms in the normal course of business. No laws that would curb monopolies or encourage more competition — a position that is often cloaked in clauses prohibiting discrimination against American companies. (Since so many of the monopolistic big tech players are American, rules targeting such behavior disproportionately fall on American companies, and can be portrayed as unfair barriers to trade.)

The truth is that Ms. Tai is taking the pen away from Meta, Google and Amazon, which helped shape the previous policy, according to a research paper published this year by Wendy Li,

This approach essentially takes the power to regulate data out of the hands of governments and gives it to technology companies, according to research by Henry Gao, a Singapore-based expert on international trade.

Many smaller tech companies complain that big players engage in monopolistic behavior that should be regulated. For instance, Google has been accused of privileging its own products in search results, while Apple has been accused of charging some developers exorbitant fees to be listed in its App Store. A group of smaller tech companies called the Coalition for App Fairness thanked Ms. Tai for dropping support for the so-called tech-friendly agenda at the World Trade Organization.

Still, Ms. Tai’s reversal stunned American allies and foreign business leaders and upended negotiations over digital trade rules in the Indo-Pacific Economic Framework, one of Mr. Biden’s signature initiatives in Asia.

The about-face was certainly abrupt: Japan, Singapore and Australia — which supported the previous U.S. position — were left on their own. It’s unfortunate that U.S. allies and even some American officials were taken by surprise. But changing stances was the right call.

The previous American position at the World Trade Organization was a minority position. Only 34 percent of countries in the world have open data transfer policies like the United States, according to a 2021 World Bank working paper, while 57 percent have adopted policies like the European Union’s, which allow data to flow freely but leave room for laws that protect privacy and personal data.

Nine percent of countries have restrictive data transfer policies, including Russia and China.

The United States now has an opportunity to hammer out a sensible global consensus that gives tech companies what they need — clarity, more universal rules, and relative freedom to move data across borders — without shielding them from the kinds of regulations that might be required to protect society and competition in the future.

If the Biden administration can shepherd a digital agreement that strikes the right balance, there’s a chance that it will also restore faith in free trade by showing that trade agreements don’t have to be written by the powerful at the expense of the weak.

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.

Even the relatively favored areas had rainfall of just 20 to 40 centimeters (8 to 15 inches)—where 20 centimeters (8 inches) is regarded as the absolute minimum to sustain agriculture—and the national average was less than 10 centimeters (4 inches)

Considering only “agricultural Syria,” the population is about five times as dense as Ohio or Belgium, but it does not have Ohio’s or Belgium’s other means of generating income.

Syria is not just a piece of land; it is densely populated. When I first visited Syria in 1946, the total population was less than 3 million. In 2010, it reached nearly 24 million.

The bottom line is that the population/resource ratio is out of balance. While there has been a marginal increase of agricultural land and more efficient cropping with better seed, neither has kept up with population growth.

During Ottoman rule the population was organized in two overlapping ways. First, there was no “Syria” in the sense of a nation-state, but rather provinces (Turkish: pashaliqs) that were centered on the ancient cities. The most important of these were Damascus, which may be the oldest permanently settled city in the world today, and Aleppo.

throughout its centuries of rule, the Ottoman Empire generally was content to have its subjects live by their own codes of behavior. It did not have the means or the incentive to intrude into their daily lives. Muslims, whether Turk or Arab or Kurd, shared with the imperial government Islamic mores and law. Other ethnic/religious “nations” (Turkish: millet) were self-governing except in military and foreign affairs.

the same groups also moved into mainly Muslim cities and towns, where they tended to live in more or less segregated neighborhoods that resembled medieval European urban ghettos or modern American “Little Italys” or “Chinatowns.”

Since this system was spelled out in the Quran and the Traditions (Hadiths) of the Prophet, respecting it was legally obligatory for Muslims. Consequently, when the Syrian state took shape, it inherited a rich, diverse, and tolerant social tradition.

the French created a “Greater” Lebanon from the former autonomous adjunct provinces (Turkish: sanjaqs) of Mount Lebanon and Beirut. To make it their anchor in an otherwise hostile Levant, they aimed both to make it Christian-dominated and big enough to exist as a state. But these aims were incompatible: the populations they added, taken from the pashaliq of Damascus, were mainly Muslim, so the French doomed Lebanon to be a precariously unbalanced society.

the French reversed course. They united the country as defined in the mandate but attempted to change its social and cultural orientation. Their new policy aimed to supplant the common language, Arabic, with French, to make French customs and law the exemplar, to promote Catholicism as a means to undercut Islam, and to favor the minorities as a means to control the Muslim majority. It was inevitable that the native reaction to these intrusions would be first the rise of xenophobia and then the spread of what gradually became a European style of nationalism.

When French policies did not work and nationalism began to offer an alternate vision of political life, the French colonial administration fell back on violence. Indeed throughout the French period—in contrast to the relatively laissez-faire rule of the Ottoman Empire—violence was never far below the outward face of French rule.