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the fact that big cities in battleground states such as Michigan, Pennsylvania and Wisconsin broke for Biden isn't what thwarted Trump's quest for reelection. The suburbs are why the President lost.

"Biden won because he was able to build on the traditional Democratic strength in the big cities by expanding his support into the suburban areas right outside of them," Enten wrote. "There wasn't any grand conspiracy by big city machines. Trump simply got beat because suburban voters were tired of him."

it's stuck to rhetoric as old as Jim Crow, rhetoric that most leaders of the Republican Party are nurturing with their silence: that Black votes shouldn't count.

"This is perhaps the most consequential election for African Americans and people of color since the election of 1860, or at least since 1960 or 1964,"

"What we're seeing in the (Trump) campaign now is the same voter suppression practices we have seen historically to target African Americans and other people of color. But this time, those who promote voter suppression will have the pandemic as both a justification for voter suppression practices and a tool to support the practices."

"Really the themes that we see, that persist, are this: Black people are corrupt, Black people are incompetent and Black people can't be trusted," she said. "That's the narrative that is continually espoused by the Trump campaign and their allies in these lawsuits."

Neither lynching nor the ideology of the Confederacy have been confined to the South

The revision of US history was broad and deliberate. The south lost the war but it won the narrative.

Beginning in the 1890s, across the US, the United Daughters of the Confederacy and the Sons of the Confederate Veterans erected monuments to their fallen heroes, and vilified the era of Reconstruction that granted civil rights to freed African Americans. They received support from the early film industry in Hollywood, which produced hundreds of movies that valorised southern rebels. 

The US began a broad and public reexamination of its history in 2015, after a white supremacist murdered nine people in a black church in Charleston

Until the past week, Europeans have been slow to examine their own histories of racism and colonialism.

one in five Britons regards their former empire as something to be ashamed of. Such nostalgia for empire played a toxic role in Brexit fantasies.

Germans use their history to think about an uncertain future, while Britons use their history to console themselves for a less glorious present.

Monuments are not just a matter of heritage; that’s why we don’t memorialise everything. Monuments are values made visible, embodying ideals we choose to honour. Unless we choose to celebrate their values, statues of slave owners belong in museums, not public streets. We cannot have a just and decent present as long as we refuse to face our pasts. 

It took Germans some time to learn this after the second world war, but they finally invented a concept for it: Vergangenheitsaufarbeitung, which translates as “working off the past”

The rebuilding of Berlin – a long, discursive process in which historians, politicians and citizens debated for more than a decade – was aspirational.

The city’s public space represents conscious decisions about what values the reunited republic ought to hold

In addition to reimagining public space, Germany paid reparations, rewrote school lesson plans to include material against racism and filled its museums with exhibits about the worst aspects of its history

She persuasively pushes the two notions together while addressing the internal wounds that, in America, have failed to clot.

A caste system, she writes, is “an artificial construction, a fixed and embedded ranking of human value that sets the presumed supremacy of one group against the presumed inferiority of other groups on the basis of ancestry and often immutable traits, traits that would be neutral in the abstract but are ascribed life-and-death meaning.”

She observes that caste “is about respect, authority and assumptions of competence — who is accorded these and who is not.”

Wilkerson’s usages neatly lift the mind out of old ruts. They enable her to make unsettling comparisons between India’s treatment of its untouchables, or Dalits, Nazi Germany’s treatment of Jews and America’s treatment of African-Americans.

Each country “relied on stigmatizing those deemed inferior to justify the dehumanization necessary to keep the lowest-ranked people at the bottom and to rationalize the protocols of enforcement.”

What these pundits had not considered, Wilkerson writes, “was that the people voting this way were, in fact, voting their interests. Maintaining the caste system as it had always been was in their interest. And some were willing to accept short-term discomfort, forgo health insurance, risk contamination of the water and air, and even die to protect their long-term interest in the hierarchy as they had known it.”

.She poses the question so many intellectuals and pundits on the left have posed, with increasing befuddlement: Why do the white working classes in America vote against their economic interests?

As if pulling from a deep reservoir, she always has a prime example at hand. It takes resolve and a strong stomach to stare at the particulars, rather than the generalities, of lives under slavery and Jim Crow and recent American experience

Wilkerson has written a closely argued book that largely avoids the word “racism,” yet stares it down with more humanity and rigor than nearly all but a few books in our literature.

In its suggestion that we need something akin to South Africa’s Truth and Reconciliation Commission, her book points the way toward an alleviation of alienation. It’s a book that seeks to shatter a paralysis of will.

I thought often of a pair of sentences from Colson Whitehead’s novel “The Underground Railroad.” “The Declaration [of Independence] is like a map,” he wrote. “You trust that it’s right, but you only know by going out and testing it for yourself.”

In her novel “Americanah,” Chimamanda Ngozi Adichie suggested that “maybe it’s time to just scrap the word ‘racist.’ Find something new. Like Racial Disorder Syndrome. And we could have different categories for sufferers of this syndrome: mild, medium and acute.”

“Caste” deepens our tragic sense of American history

In almost every state, property tax assessments were higher in areas with more black and Hispanic residents

The gap between white families and minority households remains large — 10 percent — when you combine data for Hispanic and black families

“We’ve always considered that in addition to paying your regular tax, there was a black tax that goes along with it,”

“It’s almost like it’s in the soil,” he said. “It stretches all across the board. It’s not just real estate. It’s not just housing. It’s not just food deserts. It’s not just racism on the street. It’s not just that you can’t get a cab at night. It’s everything.”

“The structure of the property tax system operates to disadvantage black Americans,” she said. “That’s how structural racism is. It’s built into the system. The property tax system itself discriminates against black Americans.”

One in five black households have reported missing a mortgage payment since mid-March, compared with about 1 in 20 white ones

Facing the accumulated disadvantages of centuries of repression and systemic racism, black Americans are likely to earn less than similar white workers in lower-paying service jobs, a dynamic that makes it more difficult to buy a home. Now, by hitting those jobs first and hardest, the coronavirus pandemic has made a bad situation worse

“During the Jim Crow era, local white officials routinely manipulated property tax assessments to overburden and punish black populations and as a hidden tax break to landowning white gentry,”

white officials going to extreme lengths to hike black taxes. In one such case in 1932, a black North Carolina resident was taxed for the value of two stray dogs that had been seen on her property.

Many county assessors intentionally overvalued black properties, sometimes in direct retaliation for black political action

As early as 1901, W.E.B. Du Bois showed that because of their unequal tax burden, black people paid more in taxes than they received in public education funds,

The fiction that “black people take services but they don’t pay taxes” remains widespread,

The values of black-owned homes tend to grow more slowly than values of white-owned ones. The white people who make up the vast majority of home buyers tend to avoid black neighborhoods, which cuts black sellers off from many potential buyers.

Given that difference in price appreciation, if an assessor assumes a black-owned home gains value as quickly as a white-owned home, the assessed value of the black-owned home will quickly outstrip its market value.

Nearby white families benefit from the opposite trend: Their homes increase in value more rapidly than their assessments, giving them an ever-growing tax break.

the appeals process illustrates how much of the property tax system functions in a way that penalizes black wealth, even as it appears neutral on its face.

While neighborhood and race are the biggest drivers of the property tax gap, the economists found others

As part of their study, the economists reviewed 3.4 million property tax appeals from Chicago and surrounding Cook County and found black homeowners were significantly less likely to appeal their property tax assessments. When they did appeal, black homeowners were less likely to win. And when they won, they earned smaller assessment reductions.

“White people feel more comfortable working within the system that was set up to make them succeed,”

“It makes sense that a black family who has been disenfranchised from these systems wouldn’t challenge it.” It is also difficult to work within the system for Latinos, many of whom do not speak English as a first language, she added.

was not taught about appealing property taxes or any of the other small strategies white homeowners have used to accumulate generational wealth.

“They feel their property taxes were being used to push them out of their places, especially when communities started gentrifying,” Avenancio-León said. It helped him see how property taxation can be used as a means of social engineering.

the duo, then working on doctorate degrees at the University of California at Berkeley, combined 118 million real estate transactions and assessments from 2005 to 2016 with maps of more than 75,000 local taxing entities — such as counties, school districts, airport authorities and utility districts.

They used the maps to sort homes into areas that faced the same property tax burdens, identified the races of homeowners using federal mortgage data, and looked at every time a dwelling was assessed and then sold in the same year. That allowed them to compare a home’s assessed value and its market value, alongside the homeowner’s race and ethnicity.

The property tax gaps are worst for low earners, but even the highest-earning black Americans pay more on average in property taxes than similarly well-off white peers living nearby.

Whether or not these gaps were caused by explicit racism, Brown said, “you should be just as outraged that this is going on, and we should find a way to fix it.”

Wilson was raised in Augusta, Georgia during the Civil War, the son of Joseph Ruggles Wilson, leading light of the Presbyterian Church of the Confederacy who made his name through the publication of his popular sermon arguing for the Biblical sanction of slavery.

Wilson’s father enrolled him at another Presbyterian, Southern-friendly college in Princeton, New Jersey which, unlike Harvard, Yale, Dartmouth, or Brown, refused to admit African-Americans. Two thirds of Princeton’s students came from the former Confederacy, but Wilson was confronted with non-Southerners for the first time, an experience that bolstered his reactionary politics and Southern identity. He took up the secessionist side in debates with classmates, and nearly came to blows with some Northern students during the contested 1876 election.

He condemned Reconstruction — the effort to enforce the civil and political emancipation of African-Americans in the occupied South — and said allowing Blacks to vote was a “carnival of public crime.”

The mass slaughter of Black people by white terrorists in Hamburg, Vicksburg, Colfax, New Orleans and other cities went unmentioned, as did attacks occurring in dozens of South Carolina towns right under Wilson’s nose the whole time he was coming of age.

“A History of the American People,” a poorly written and shoddily researched five-volume, illustrated tome published in 1902.

It furthered the white supremacist arguments in “Division and Reunion,” calling freed slaves “dupes” and the KKK a group formed “for the mere pleasure of association [and] private amusement” whose members accidentally discovered they could create “comic fear” in the Blacks they descended on. Immigrants were a problem because they were no longer “of the sturdy stocks of the North of Europe” but contained “multitudes of men of the lowest classes from the South of Italy and men of the meaner sort out of Hungary and Poland” and Chinese people, “with their yellow skin and strange, debasing habits of life,” who seemed “hardly fellow men at all, but evil spirits” and who provoked understandable mass killings by white mobs.

Wilson won the 1912 election with less than 42 percent of the vote, becoming the first Deep Southerner to hold the presidency.

It’s said that the South lost the war, but won the peace, but it was Wilson’s presidency that sealed the victory. Wilson presided over the segregation of the federal government, with Black civil servants directed to use only certain bathrooms and to eat their lunches there too so as to not sully the cafeterias

The president famously ejected Black civil rights leader William Monroe Trotter from the Oval Office for having temerity to tell him that his delegation came to him not as “wards” but as “full-fledged American citizens” demanding equality of citizenship.

Threatened with bankruptcy, Dixon turned to his old friend to intervene. Wilson screened the film in the White House for his Cabinet, and the following day Supreme Court Justice Edward Douglass White — whose statues in Louisiana and the U.S. Capitol are also subject of current protests — agreed to show it to the other justices and congressional leaders because he himself had been in the Klan and loved the film’s message. These tacit endorsements from the highest levels of power turned the tide and the film went on to be a massive financial success and was until very recently celebrated as a great work of art.

his plans for the world order presided over by the League of Nations paralleled his vision of the United States. He promoted the principles of democracy and national self-determination, but only for European nations and Anglo-Saxon settler countries like the U.S., Canada, and Australia. Czechs, Romanians, and Serbs deserved their own national states, African, Arab, Indian, and Pacific Island peoples did not

Japan, an allied power in the war, introduced a measure to include the principle of racial equality in the League’s mandate. Wilson opposed it because it would have compelled the U.S. to ensure equal treatment to Japanese, Haitian, or Liberian citizens in hotels, restaurants, and transport across the Jim Crow South. The measure passed anyway, 11-5, but Wilson, who chaired the proceedings, unilaterally and arbitrarily declared the measure had failed because it was not unanimous

In the major scale used to measure “racial resentment,” participants are asked to respond to questions like “Irish, Italians, Jewish, and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors,” and “It’s really a matter of trying hard enough; if blacks would only try harder that would be as well off as whites.” People who answer yes are more likely to harbor racial resentment than others.

this reasoning, in turn, “undergirded contentions that African Americans’ cultural deficiencies was the cause of their poverty—assertions that delegitimized blacks’ demands for structural changes in the political economy and stigmatized their utilization of welfare state entitlements.”

Even as he avoids the words black or African American, that charge—that black deficiency (or even pathology) drives black disadvantage—is the core of Sullivan’s inquiry. And his argument, unstated but clear as the blue sky, is that black Americans have only themselves and their culture to blame for continued racial inequality.

The reason we call this racial resentment and not simple “racism” is that it stems from different psychological processes. Less a belief in biological inferiority and more a moral and cultural judgment, what political scientists Donald Kinder and David Sears called “a blend of anti-black affect and the kind of traditional American moral values embodied in the Protestant Ethic … a moral feeling that blacks violate such traditional American values as individualism and self-reliance, the work ethic, obedience, and discipline.”

Had Sullivan written about the biological inferiority of black Americans, there’s no doubt it would have raised red flags among his editors. But to frame the subject as a question of black culture, well, that’s just being provocative.

A July Reuters-Ipsos poll found that 78 percent “support teaching high school students about the impacts of slavery” and 73 percent support teaching high school students about the impacts of racism.

If critical race theory isn’t being taught to children — and in a technical sense, it isn’t — then it’s hardly illogical to suppose that some other concern may be afoot.

The problem lies in the name “critical race theory.” It’s a no-brainer that the legal doctrine developed decades ago by scholars such as the Harvard Law professor Derrick Bell and the Columbia University and U.C.L.A. law professor Kimberlé Crenshaw is not being taught to tots.

today, this isn’t what most voters mean when they object to critical race theory, and to participate in this debate as if otherwise is quibbling at best, and a smoke screen at worst.

consider the cultural critic Helen Pluckrose’s — fair, I think — summary of the original body of critical race theory work:C.R.T. is not just talking about historical and contemporary racism with a view to overcoming it — something that all approaches to addressing racism do — but a set of core beliefs that racism is ordinary and/or permanent; that white supremacy is everywhere; that white people don’t oppose racism unless it suits them; that there is a unique voice of color that just so happens to be the one that agrees with C.R.T.; that lived experience and story-telling are primary ways of revealing racism; that liberalism and the civil rights movement approach are bad; and that working for social justice means using the critical theories of race set out above.

this “critical” approach has trickled down, in broad outline, into the philosophy of education-school pedagogy and administration — call it C.R.T.-lite or, if you prefer, C.R.T. Jr. — and from there migrated into the methods used by graduates of those education programs into the way they wind up running schools.

Under this approach, what alarms many parents and other observers is that kids will absorb the idea that it is enlightened to see white people as potential oppressors and Black people as perpetual victims of an inherently oppressive system. That it is therefore appropriate to ascribe certain traits to races, rather than individuals, and that education must “center” the battle against power differentials between groups

An implication some educators draw from these tenets is that various expectations of some of their students, based on what are generally thought to be ordinary mainstream assumptions, are instead onerous stipulations from an oppressive white-centric view.

Hence an idea that it is white to be on time, arrive at precise answers and reason from A to B, rather than holistically, etc. Again, this is not what decades-old critical race theory scholarship proposed, but yes, the idea is descended from original C.R.T.’s fundamental propositions about white supremacy.

these guidelines, apparently sanctioned by state departments of education, contradict the notion that concepts derived from critical race theory — or are, at least, C.R.T.-lite — is nowhere near our schools, that the C.R.T.-in-schools debate “isn’t real,” merely a fiction designed to cloak racism.

In some cases, evidence of C.R.T.-lite is easier to spot at various private schools.

Some of those who say that critical race theory isn’t being taught in schools may not be aware of these developments. Others most likely are, and suppose that they are healthy, that this is indeed how education should be.

That’s a respectable stance, but one ought not harbor it in disbelief that any intelligent, morally concerned person could feel differently

One can ardently support that students learn about racism and its legacies in a way that doesn’t crowd out obvious lessons about the history of undeniable racial progress. One can do that while questioning whether students should be immersed in a broader perspective that offers overbroad, clumsy and, frankly, insulting portraits of what is inherently white and what is Black, Latino, Asian American or Native American, and fosters — even if unintentional — a sense of opposition between the groups in question.

The horror of slavery, the hypocrisy of Jim Crow, the terror of lynching, the devastating loss of life and property in Tulsa and in other massacres — no student should get through, roughly, middle school ignorant of these things, and anyone who thinks that is “politics” needs to join the rest of us in the 21st century.

But the insistence that parents opposed to what is being called critical race theory are rising against a mere fantasy and simply enjoying a coded way of fostering denial about race is facile

The experience of nearly 250 years is that the first type of movement generally succeeds: emancipation, suffrage, civil rights, marriage equality. They have aimed to build the country up, and bring Americans more closely together, on foundations already in place.

The second type — from the Confederacy to the white supremacy of the Jim Crow era to militant Black nationalism in the 1960s — always fails. These movements want to tear things down, divide Americans, reject and replace our national foundations.

What’s wrong with a movement that, on its narrowest terms, aims to make Americans more aware of racial injustices, past and present? Nothing. In cases like those of Eric Garner, George Floyd and Ahmaud Arbery, non-Black America has had a long-overdue education about the fact that Black lives can still be subject to the same casual cruelties of a century ago.

like many movements that overspill their initial causes of action, Wokeness now connotes much more than an effort to reform the police or denounce racial injustice when it occurs. It is, instead, an allegation that racism is a defining feature, not a flaw, of nearly every aspect of American life, from its inception to its present, in the books we read, the language we speak, the heroes we venerate, the roads we drive, the way we do business, the way we select for merit and so on.

The insult turns to injury when it comes to the solutions Wokeness prescribes, and in the way that it prescribes them.

The problem with the allegation isn’t that it’s flatly wrong: America’s past is shot through with racism and, as Faulkner put it, “The past is never dead. It’s not even past.” But the allegation is also incomplete, distorted, ungenerous to former generations that advanced America’s promise, and untrue to the country most Americans know today.

it is a prescription, not for genuine dialogue and reform, but for indoctrination and extirpation, based on a relentless form of race consciousness

It operates as if, in city after city, American police forces aren’t led by Black police chiefs and staffed by officers of diverse backgrounds. It operates as if white supremacy is still being systemically enforced, while ignoring the fact that a previously marginalized ethnic minority, namely Asian Americans, enjoys higher income levels than white Americans.

Above all, Wokeness pretends that incidents such as George Floyd’s murder, which are national scandals, are actually national norms

Most Americans, I suspect, not only sense the falseness of the allegation. They are, increasingly, insulted by it.

Wokeness operates as if there had been no civil rights movement, and that white Americans hadn’t been an integral part of it. It operates as if 60 years of affirmative action never happened, and that an ever-growing percentage of Black Americans don’t belong to the middle and upper class (and that they are, incidentally, concentrated in the American South). It operates as if we didn’t twice elect a Black president and recently bury a Black general as an American icon.

A typical example: The American Medical Association recently published its “Guide to Language, Narrative and Concepts,” which includes such recommendations as replacing the term “disadvantaged” with “historically and intentionally excluded,” “social problem” with “social injustice,” “vulnerable” with “oppressed,” and “blacklist” and “blackmail” with words that don’t suggest an association between the word “black” and “suspicion or disapproval.”

This isn’t silly. It’s Orwellian. It’s a blunt attempt to turn everyday speech into a perpetual, politicized and nearly unconscious indictment of “the system.” Anyone who has spent time analyzing how the totalitarian regimes of the 20th century operated will note the similarities.

Ultimately, though, Americans are still free to reject the Woke ethos, even if they sometimes have to leave their institutions as a result.

This is why Wokeness will fail. For every attempt to cancel certain writers, others will publish them. For every diktat to fix language by replacing some words with others, people will merely find more subversive ways to say the same thing.

In the long run, Americans have always gotten behind protest movements that make the country more open, more decent, less divided. What today is called Woke does none of those things. It has no future in the home of the free.

This early trauma, Guelzo argues, caused young Robert to value stability, security and self-control. The fear of what might happen if his private demons were unleashed compelled Lee to hold ever tighter to a life of probity.

Robert E. Lee opposed erecting statues to himself and his brothers-in-arms. His wish is now being fulfilled. As Guelzo reports, since the violent confrontations in Charlottesville, Va., in August 2017, the removal of the representations of Confederate heroes, and of Lee in particular, has accelerated. Their names are also vanishing from schools, public parks and thoroughfares.

It is belated recognition that between 1890 (the year Lee’s equestrian statue was dedicated on Richmond’s Monument Avenue) and the present, these memorials represented less historical tributes to the Lost Cause than contemporary exclamation points to Jim Crow and white supremacy

Their presence distorted the past and, therefore, poisoned the present. Allen C. Guelzo’s fine biography is an important contribution to reconciling the myths with the facts.

According to Jonathan Katz, a freelance journalist, Hanania’s organization, the Center for the Study of Partisanship and Ideology, has received at least $700,000 in support through anonymous donations. He is also a visiting scholar at the Salem Center at the University of Texas at Austin — funded by Harlan Crow.

A whole coterie of Silicon Valley billionaires and millionaires have lent their time and attention to Hanania, as well as elevated his work. Marc Andreessen, a powerful venture capitalist, appeared on his podcast. David Sacks, a close associate of Elon Musk, wrote a glowing endorsement of Hanania’s forthcoming book. So did Peter Thiel, the billionaire supporter of right-wing causes and organizations. “D.E.I. will never d-i-e from words alone,” wrote Thiel. “Hanania shows we need the sticks and stones of government violence to exorcise the diversity demon.” Vivek Ramaswamy, the Republican presidential candidate, also praised the book as a “devastating kill shot to the intellectual foundations of identity politics in America.”

why an otherwise obscure racist has the ear and support of some of the most powerful people in Silicon Valley? What purpose, to a billionaire venture capitalist, do Hanania’s ideas serve?

Look back to our history and the answer is straightforward. Just as in the 1920s (and before), the idea of race hierarchy works to naturalize the broad spectrum of inequalities, and capitalist inequality in particular.

If some groups are simply meant to be at the bottom, then there are no questions to ask about their deprivation, isolation and poverty. There are no questions to ask about the society which produces that deprivation, isolation and poverty. And there is nothing to be done, because nothing can be done: Those people are just the way they are.

the idea of race hierarchy “creates the illusion of cross-class solidarity between these masters of infinite wealth and their propagandist and supporter class: ‘We are of the same special breed, you and I.’” Relations of domination between groups are reproduced as relations of domination between individuals.

This, in fact, has been the traditional role of supremacist ideologies in the United States — to occlude class relations and convert anxiety over survival into the jealous protection of status

worked in concrete ways to bound the two things, survival and status, together; to create the illusion that the security, even prosperity, of one group rests on the exclusion of another

it comes at a time when “a confluence of at least four political and technological developments will make its practical effect significant.”

First, technological advances, as used in the Milligan case, make it easier to find new V.R.A. districts that can be reasonably configured.

Second, minority-preferred candidates can win with lower minority voting-age populations (falling from estimates as high as 65 percent in the 1990s to below 45 percent now), which means more minority voters are available to create additional V.R.A. districts.

Third, the private bar has become extremely well resourced to pursue these cases.

Fourth, the debates over partisan gerrymandering in the last decade brought many new strong social scientists into this area, in which expert analysis of maps and voting patterns plays a critical role.

John Roberts’s majority opinion is particularly important because it rejects the argument that race-based remedial districting is unconstitutional:Alabama further argues that, even if the Fifteenth Amendment authorizes the effects test of section 2, that Amendment does not authorize race-based redistricting as a remedy for section 2 violations. But for the last four decades, this Court and the lower federal courts have repeatedly applied the effects test of section 2 as interpreted in Gingles and, under certain circumstances, have authorized race-based redistricting as a remedy for state districting maps that violate section 2.In that context, Roberts continued, “we are not persuaded by Alabama’s arguments that section 2 as interpreted in Gingles exceeds the remedial authority of Congress.”

My best guess is that Roberts and Kavanaugh thought it best to proceed cautiously and bide their time. The court as an institution can only take so many bombshells at a time. The issue will come back to the court soon enough.

But, Tribe continued, “Allen v. Milligan remains highly significant as an essential reminder that the court doesn’t exist in an isolation booth, unaffected by public reactions to its decisions that venture too far from the mainstream of legal and social thought.”

Roberts and Kavanaugh, in Tribe’s view, chose not to press the case against race-based redistricting in part because of “the controversy unleashed by the court in its shattering abortion ruling in Dobbs last June, coupled with other unrestrained shocks to the system delivered by the court in the landmark cases involving guns and climate change, and aggravated by the ethical stench swirling about the court as a result of improprieties.”

These developments, Tribe continued, “almost certainly had an impact, however subconscious, on the chief justice and on Justice Kavanaugh, who has increasingly sought to distance himself from the hard right.”

In the Court’s majority opinion, Chief Justice John Roberts held that “eliminating racial discrimination means eliminating all of it”—a new version of his old affront that “the way to stop discrimination on the basis of race is to stop discriminating on the basis of race.”

This glib framing, and the school of thinking it represents, established a pernicious, false moral equivalence. Those who preserved and protected Jim Crow — the institution that defended America’s old racial hierarchy — were and are something altogether different from those who fought and who continue fighting for a more just America.

Those uprooting affirmative action seem content to leave intact systems that compound privilege, exacerbating inequality — like legacy admissions policies that disproportionately favor wealthy, white applicants — resulting in lower-income students and families of all races losing out.

I find it regrettable that, over 40 years ago, Justice Lewis Powell introduced the American public to the imperative of diversity in the shallow manner that he did.

I was a freshman in college when his seminal opinion in Regents of the University of California v. Bakke (1978) invited some to equate the benefits of diversity with unfairness

the idea that necessary diversity initiatives are somehow reverse discrimination or that they correlate with lower standards or lesser outcomes.

The data suggests exactly the opposite. Study after study demonstrates that, across organizations, diversity enhances critical thinking, creativity and collaboration, as well as productivity, profitability and performance.

we should tell the truth about why diversity is now controversial: Opponents of diversity are opponents of any racial consciousness. They want to prevent us from understanding the ways that the past informs the present, from wrestling with the fullness and richness and complexity of our history.

Stephen Budiansky sets out to revive Holmes’s reputation and relevance as a model of intellectual humility for our polarized age

Holmes learned from his service in the Civil War that moralism leads to intolerance — “when you know that you know, persecution comes easy,”

More than most judges, Holmes managed to set aside his prejudices and partisan loyalties because of his philosophical skepticism about the impossibility of ever being confident that one is right. “To have doubted one’s own first principles,” as he put it, “is a mark of a civilized man.”

This philosophical skepticism led him to uphold most laws against constitutional challenges; as he put it in his most famous dissenting opinion, “A constitution is not intended to embody a particular economic theory . . . it is made for people of fundamentally differing views.”

Holmes achieved both ambitions, writing a book, “The Common Law,” that revolutionized legal thinking by arguing that judges made policy rather than simply applying the law, and that rather than embodying absolute moral principles, law reflected changing social norms.

Holmes took from his service in the Army, which Budiansky describes in vivid detail, the idea that fighting for ideals was senseless; as Louis Menand famously wrote, the war “made him lose his belief in beliefs.”

“I don’t care to boss my neighbors and to require them to want something different from what they do,” he told Harold Laski, “even when, as frequently, I think their wishes more or less suicidal.”

Holmes came to believe that life is a struggle and the only thing that can redeem it is ceaseless hard work — mastery of a subject, a discipline or a job for its own sake, without being able to control the result.

The subject Holmes chose to master was law, and he worked harder at it than anyone else of his generation

He told a cousin that he had resolved to write a classic work on the law before the age of 40 and that he hoped after that to become a Supreme Court justice

The same philosophical skepticism, however, eventually persuaded him to write some of the greatest defenses of free speech of his time, on the grounds that a functioning democracy needs broad tolerance for what he famously called “the thought we hate.”

This view, which conservatives today denounce as sociological jurisprudence, led Holmes to a constitutional philosophy not of judicial activism but of radical judicial restraint.

A constitution, he wrote, “is a frame of government for men of opposite opinions and for the future, and therefore [we should] not hastily import into it our own views, or unexpressed limitations derived merely from the practices of the past.”

He followed the same philosophy on the U.S. Supreme Court, asking not whether the Constitution specifically authorized the federal or state governments to act but whether it specifically forbade them from doing so

He rejected the idea of the conservative textualists and originalists of his day, who argued that the Constitution should be strictly enforced according to its original public meaning. In his view, they were simply substituting their own political preferences and ascribing them to the Constitution’s framers.

Holmes’s radical devotion to judicial restraint led him to vote to uphold not only progressive economic legislation but also some of the most illiberal laws of his day, including mandatory-sterilization laws and laws disenfranchising African American voters in the Jim Crow South.

he was not indifferent to all violations of constitutional rights. In 1914, he began to write the dissents that would define his judicial legacy, and they included cases where Holmes was outraged by what he viewed as clear violations of the rule of law by racist mobs.

While Brandeis emphasized his faith that truth would emerge from thoughtful deliberation, Holmes emphasized what Budiansky calls “the importance of tolerance for opposing views, not just as a bedrock foundation of democracy but as a reflection of fundamental skepticism about certainty.”

“Certitude is not the test of certainty,” Holmes wrote in developing his mature view on free speech. “We have been cocksure of many things that were not so.”

The most inspiring sign of Holmes’s intellectual humility was that, throughout his long life, from his 20s through his 90s, he never stopped cultivating his faculties of reason and set aside time every day for learning.

At age 21, he began keeping a list of every book he read for pleasure and self-improvement. At the time of his death, the range was inspiring — more than 4,000 books, ranging from philosophy, sociology, religion, economics and science to murder mysteries. In the course of reading more than a book a week, he had a rule that a book had to be finished once started, no matter how arduous.

at a time when progressives and conservatives alike are so sure of their own premises that America is more polarized than at any time since the Civil War, the “skeptical humility,” as Budiansky puts it, that Holmes took from the war seems more elusive, and more urgently needed, than ever.

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.

he raged at the alliance’s eastward expansion. Later, he decried a fictitious “genocide” that he says the West is sponsoring in Ukraine. Mr Putin can’t tell his people that his army is fighting against their Ukrainian brothers and sisters who gained freedom.

Even though Russia has set out to build a fortress economy, the country is still connected to the world and, as the initial 45% fall in Russia’s stockmarket suggests, it will suffer.

Russia is Europe’s main supplier of gas. It exports metals like nickel and palladium and along with Ukraine it exports wheat. All of that will present problems at a time when the world economy is struggling with inflation and supply-chain glitches.

Some will say that it is too risky to challenge Mr Putin in these ways—because he has lost touch with reality, or because he will escalate, miscalculate or hug China

After 22 years at the top, even a dictator with an overdeveloped sense of his own destiny has a nose for survival and the ebb and flow of power.

Even China should see that a man who rampages across frontiers is a threat to the stability it seeks.

They will also signal to Mr Putin that the further he pushes in Ukraine, the more likely he is to end up strengthening NATO’s presence on its border—the very opposite of what he intends.

The spirit of Barabbas — the desire to seize or retain power, through violence if necessary — has been at war with the spirit of Christ ever since. Two millenniums of church history demonstrate a terrible truth: There was nothing uniquely evil about that ancient crowd. Instead it held up a mirror to our own nature, one that is all too eager to wield the sword, to believe that our own power is a prerequisite to justice.

Easter weekend contains more than one example of the spirit of Barabbas. When Christ was arrested, the Apostle Peter — a man who had been by his side for much of his ministry — still could not see the truth. He drew his sword, struck the high priest’s servant, and cut off his ear.

Though he was in the midst of an unjust arrest that would prove prelude to an unjust execution, Christ rebuked Peter, saying, “Put your sword back in its place, because all who take up the sword will perish by the sword.” As he reminded Peter, Jesus had the power to call on “legions of angels” to stop the arrest, but he chose not to. His purpose was to go to the cross, and as Jesus told us, that’s our purpose as well.

There is a difference between the quest for power and the quest for justice. Believers are required to “act justly.” We should not stand idly by in the face of exploitation or oppression. We do not retreat from the public square. But Christian engagement must be distinctive. It cannot emulate the world’s methods or morality.

the example of Jesus dominated the minds of civil rights leaders. “We discussed and debated the teachings of the great teacher, and we would ask questions about what would Jesus do,” said Lewis. “In preparing for the sit-ins, we felt that the message was one of love — the message of love in action: Don’t hate. If someone hits you, don’t strike back. Just turn the other side. Be prepared to forgive.”

The spirit of Barabbas was alive and well in the men who trained their fire hoses on peaceful protesters, who loosed dogs on the Black children of Birmingham. They weren’t trying to seize power, but they were trying to maintain it, through violent, lawless means. Their will to power collided with the quest for justice. It is only through God’s grace and the unimaginable courage and persistence of peaceful protesters that justice prevailed, and Jim Crow laws were overturned.

The spirit of Barabbas tempts Christians even today. You see it when armed Christians idolize their guns, when angry Christians threaten and attempt to intimidate their political opponents, when fearful Christians adopt the tactics and ethos of Trumpism to preserve their power. The spirit of Barabbas most clearly captured the mob on Jan. 6, when praying Americans participated in an insurrection based on a lie.

Christ did not reject earthly rule so that his flawed followers could seize the world’s thrones. His ethos was clear: “You know that the rulers of the gentiles lord it over them, and those in high positions act as tyrants over them. It must not be like that among you. On the contrary, whoever wants to become great among you must be your servant.”