Group items tagged

If the House and Senate arrive at different decisions, the law governing the proceedings is unclear about how to reconcile them, with the potential for an unresolvable constitutional deadlock.

The 2000 election was arguably the closest in history, decided by Florida by a margin of one one-hundredth of one percent, so close that we will never know who the true winner of the state was: Media recounts months later concluded that the results would change depending on which counting method was used. Even so, a concession occurred before the second stage.

If a state’s electoral votes are disputed, the House and Senate meet separately to adjudicate the controversy. A potentially small number of representatives or senators can break rank, conceding the election by agreeing to resolve the dispute in favor of the other party. There is a potentially dangerous legal ambiguity here:

The House and Senate could vote on the commission’s recommendation — but if the two houses disagreed, the commission’s decision would stand. The commission first recommended, on an 8-to-7 partisan vote, that Florida’s disputed electoral votes be allocated to the Republican candidate, Rutherford B. Hayes. But while the Republican Senate endorsed the recommendation, the Democratic House rejected it. The pivotal moment came immediately afterward: With the speaker of the House at his side, the vice-president announced that the commission’s decision stood. The Democrats accepted the call; they allowed the count to continue.

Peaceful transitions of power require political will. In the end, people on one side must step back from the brink.

But the most important, most dangerous part of all this was Trump’s successful attempt to convince millions of his supporters that he’d won and was being cheated out of his win—and the fact that many leaders of the Republican Party, at all levels, went along. That claim is somewhat akin to a charge of child abuse—the very accusation is also a demand for immediate action to stop it. The mob that gathered last Wednesday took that accusation seriously, and acted to “stop the steal.”

There is a great desire to blame Trump—who is certainly very much to blame—and move on, without recognizing and responding to the dire reality: that much of the GOP enlisted in his attempt to steal an election.

The legislators were there to count the votes certified by the states—after months of review by election officials, and after endless court challenges were rebuffed—and, instead, they voted to throw them out. They did this after months of lying to the public, saying that the election had been stolen. They crossed every line a democracy should hold dear. To my knowledge, not one of them has yet apologized or recanted for their participation in what even some Republican senators are openly calling the “big lie.”

Some, like Senator Ted Cruz, have tried to cover up their attempt to overturn the election by saying that their constituents (and indeed tens of millions of Americans) believe that the election was stolen, and that they were merely honoring their beliefs. However, it was they, along with the president, who convinced those millions of people that the election was stolen in the first place, and that Joe Biden was not the legitimate president-elect

Some legislators have since tried to argue that they didn’t mean to “overturn” the election, that their action was more akin to a protest vote. This cannot be taken seriously. That’s like pulling a gun on somebody, walking away with their wallet, and then claiming that you never intended to shoot them if they hadn’t turned over their wallet.

A mugging is a mugging, and a mass of legislators claiming that the election was stolen and rejecting the results is an attempt to overturn the election. When the president himself refuses to concede, voting against the recognition of electoral votes cannot simply be a protest, and we don’t have to accept such absurdity at face value.

Some Republicans have raised the fact that the 2016 Democratic presidential candidate, Hillary Clinton, referred to Trump’s presidency as “illegitimate.” That may well be, but that happened long after the election was over and the transition was complete. She called Trump to concede less than 12 hours after the polls closed, and the Obama administration immediately started the transition process. There was no formal challenge that required suspending the session to debate whether to accept the actual results.

Today, by contrast, many GOP legislators have claimed for months that the election was fraudulent or stolen, and have explicitly and repeatedly called on their supporters to stop this fraud. The president not only refused to concede before they took their vote, but even as the storming of the Capitol was still under way, he once again claimed that he had won in a landslide.

A great misunderstanding about democracy is that it can be stolen or damaged only if formal rules are suspended or ignored. In fact, many authoritarian regimes are sticklers about formal rules, even as they undermine their meaning

We’ve already witnessed the hollowing out of some of the core tenets of liberal democracy—equal representation of voters, unimpeded access to the ballot—in many aspects of our electoral system. Republicans have pursued a project of minority rule for decades, exploiting structural features of American politics and opportunistically shaping rules in their own favor.

The Senate is structurally dominated by a minority—less than 20 percent of the population elects a majority of its members. Through gerrymandering and the uneven distribution of the population, the GOP does about 6 percent better in the median House district than it does in the national popular vote.

Already, there are signs that many in the GOP intend to respond to their loss in the Senate by doubling down on disenfranchising voters in the name of fighting the “election fraud” they falsely convinced millions is widespread

The Republicans who backed Trump’s effort to overturn the election may have known that it didn’t have a high chance of success, but that doesn’t change the nature of the attempt, especially given their lack of remorse or apology. Unless they are convinced that it was a mistake—unless they pay such a high political price for it that neither they nor anyone else thinks of trying again—they are likely to seize the next available opportunity to do the same. If a future election comes down to one state instead of three, if a future presidential candidate uses lawsuits and coercion more competently, or if a few election officials succumb to threats more easily, they’ll be in the game.

A line must be drawn. The increasing entrenchment of minority rule and democratic backsliding in almost every level of government was terrible enough, but now we’ve even moved past that.

Democrats will soon control the House, the Senate, and the presidency, making it possible for them to undertake crucial reforms on voting rights and electoral integrity. Perhaps some Republicans will decide to join them; if there ever were a time for putting country over party, this is surely it.

Trump’s press secretary said Dillon’s remark reminded her of an “appalling” statement that former Democratic nominee Hillary Clinton made in August. Clinton had said that Biden “should not concede under any circumstances” because she believed the election was “going to drag out, and eventually I do believe he will win if we don’t give an inch.” 

“We believe this will be a landslide, and for the Biden campaign to come out and double down on Hillary Clinton’s egregious statement that under no circumstance should you concede just tells you all you need to know,” she said. “They’re in a pinch. It’s why they’re out on the campaign trail, even today as voters go to the polls.”

Fox News also aired a snippet during the segment of Trump talking about Biden campaigning on Election Day, which he claimed was because the former vice president is “worried.”

McEnany emphasized that the Biden campaign is simply “trying to catch up with President Trump” but that “voters see through that act and that charade.”

Trump, who had questioned the validity of the election before votes had even been cast, is continuing to dig in his heels on unsupported legal challenges lodged by his allies

"I concede NOTHING! We have a long way to go."

Trump also continued to blame his loss on debunked theories about the 2020 election

The tweets from Trump followed a Saturday spent golfing and tweeting similar false conspiracy theories, and driving by a crowd of his supporters who gathered in Washington, DC, to protest the election results on the basis of his lies and propaganda.

But on Twitter this weekend, the President launched baseless conspiracy theories and false statements to his nearly 90 million followers online.

Trump has repeatedly claimed without evidence that his chance at a second term in office was stolen from him with corrupt votes

Trump's former national security adviser, John Bolton, said Sunday that he thinks the President is "stunned" by his loss.

"I think he's stunned by it. I think that's why he's been silent really for so long. He's lived in his own dream world and been successful at it these last four years," Bolton told CNN's Fareed Zakaria.

Biden's incoming White House chief of staff, Ron Klain, said Sunday that Trump's tweet that the former vice president won is "further confirmation of the reality," but added that the President's Twitter feed doesn't determine an election.

"I accept it as a further confirmation of the reality that Joe Biden won the election -- and not through any of the rest of that tweet, not through fraud or anything else the President is baselessly alleging. He won because he got more votes, OK, that's why he won," Klain said

he won the same number of electoral votes that President Trump himself called a landslide four years ago.

Sanders told Tapper that it's "beyond belief" that the President "continues to deny reality."

"Trump will have the distinction of doing more than any person in the history of this country in undermining American democracy," Sanders added. "The idea that he continues to tell his supporters that the only reason he may have lost this election is because of fraud is an absolutely disgraceful, un-American thing to do."

"It's clear, that certainly based on what we know now, that Joe Biden is the President-elect and that transition, for the country's sake, it's important for a normal transition to start through,"

The greatest failure of the GOP is not realizing that Obama is a president they could have worked with on policy grounds, and whose relationship with them could have actually defused some of the very traits that suburban voters and most generations under 40 still find so disturbing in the GOP base.

Reform conservatives believe that the GOP should put forward serious and credible policies that directly address the issue of family formation and breakdown. It will be good for the economy, good for people, and is a prerequisite to shrinking government over the long term since voters will not acquiesce to shrinking public handouts if they do not feel that they have private safety nets available, first among which is the family

The alternative scenario would go something like this: Don’t address middle income voters’ day-to-day concerns seriously, don’t make family formation more affordable -> concede the field to Democrats -> increase economic and social insecurity -> increase demand for government -> lose elections -> government grows bigger -> social pathologies get worse -> keep conceding the field -> increase demand for government -> etc. 2012 was Act I of that nightmare scenario.

I endorsed Ross’ and Reihan’s book, but took longer than they did to let go of my libertarian instincts in the face of yawning social inequality. It’s only been since the impact of the Great Recession sank in that I have truly come to terms with the fact that, say, flat taxes are irrelevant right now to our major problems, or that publicly subsidized private health insurance is an important response to a middle class facing an epic (if much predicted) employment and economic crisis.

there’s a core agreement: the times demand a different response than that imprinted on so many of us under Reagan-Thatcher; and encouraging self-government is the best way to keep big government at bay. If the GOP were to accept the principles of Romneycare/Obamacare, for example, they could then help reform the architecture to control costs better, empower individual choices more, and win people like me back.

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

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

Political analysts say it's an obvious attempt to try to rehabilitate his image when his legacy is at stake.

Trump campaigned on a promise to crack down on immigration. The clearest example of that was his promise to build a "big, beautiful wall" along the U.S.-Mexico border — a core issue for his base.

Most mainstream Republicans would prefer if Trump just faded away quietly,

But Walsh said this trip makes clear that Trump does not plan to do that. And Walsh is concerned that Trump could actually make things worse by picking such a hot button issue

the political backlash from the Capitol riot is likely too great for Trump to overcome. He said the president's refusal to concede the election and willingness to stoke conspiracy theories all but ensured that he will be remembered for the bitter end to his time in office instead of his policy accomplishments, such as tax cuts and naming three Supreme Court judges.

"I think until Donald Trump properly concedes the election and recognizes Joe Biden as the president-elect, he's not going to be able to talk about anything else,"

“Whether they liked each other or not, they would ride together for the show of unity,”

“Harry Truman didn't like Eisenhower, but he rode up to the Hill with him. Nixon rode with LBJ. Ford rode with Carter. Reagan beat Carter and rode with him. … Everybody did that. Even Trump rode with Obama.”

But this will not be the case this year, as President Donald Trump has said he will not attend the inauguration of Joe Biden.

“It's a celebration of American democracy, it’s a celebration of how we peacefully transfer power,” he said. “The symbolism and the imagery of it is critical.”

The 2000 election between George W. Bush and Al Gore was one of the most contentious in American history, with the Supreme Court having to ultimately settle a recount dispute before Gore would concede.

“You can see his lips are pursed, and in that little moment it had to be incredibly painful for him on every level,” Kennerly said. “He's giving up the presidency. No one's ever done it that way, and he was a disgraced leader and he was leaving under duress.

The President’s absence isn’t the only reason that this inauguration will be unlike any we have ever seen. The celebrations have been significantly pared down because of the coronavirus pandemic, and Biden’s inaugural committee — trying to keep crowds to a minimum — has urged Americans not to travel to Washington, DC. The National Mall will also be closed to the general public because of security concerns, according to an official familiar with discussions.

The Nixon transition was a moment Kennerly said he will never forget. “For drama, that’s definitely top five in my life — that moment, the only time an American president resigned,” he said.

Kennerly was on a press riser with other photographers and had only a few seconds to immortalize the historic spectacle. It was a quick sequence of photos as Nixon waved farewell before boarding his helicopter.

“It’s not just to pay off the people who supported you,” he said. “It’s to show the people of the United States that we can do this the right way and that’s why we’re different than so many other places.”

“But once again, it was a peaceful transition. A few minutes later, Ford was sworn in as president of the United States. No guns were fired, no coup was attempted, and as President Ford put it in his remarks, ‘Our long national nightmare is over.’ “

“These are photos that can give you more insight behind the scenes,” he said. “And it really boils down to the access of the presidential photographers. Everything's so locked down. This time, (the security) will be insane. There won't be very much behind the scenes, outside the personal photographer to Biden. That is my guess.”

So we likely won’t be seeing many of the great photos we’ve seen from past inaugurations. There will be an emptiness about the day, as the celebration is mostly intended to be a virtual event viewed on television.

Rice doesn't represent a swing district.

"Compared to the often raucous members of the state's congressional delegation, Rice has been more low-profile and focused on his legislative work,"

But Rice hadn't made a mistake or accidentally pressed the wrong button. His vote to impeach was real -- and without question, the most surprising of the 10 Republicans who bucked the President.

"Once the violence began, when the Capitol was under siege, when the Capitol Police were being beaten and killed, and when the Vice President and the Congress were being locked down, the President was watching and tweeted about the Vice President's lack of courage.

"... It has been a week since so many were injured, the United States Capitol was ransacked, and six people were killed, including two police officers. Yet, the President has not addressed the nation to ask for calm. He has not visited the injured and grieving. He has not offered condolences. Yesterday in a press briefing at the border, he said his comments were 'perfectly appropriate.'"

The combination of Trump's incitement of the crowd, his attacks on Vice President Mike Pence during the riot itself and his total lack of remorse over his role in the overrunning of the Capitol added up to be more than Rice could take.

While Rice did vote in favor of the Electoral College objections raised by Republicans in Arizona and Pennsylvania, he expressed some misgivings about doing so in the wake of the Capitol violence. "I am incredibly disappointed in the President," Rice told a local TV station last Wednesday. "The President needs to step up right now and say this election is over. I'm tired of it. He needs to concede. He needs to say that this election is over and tell these folks to calm down."

"Donald Trump was backed by an overwhelming majority in my district and in South Carolina," Rice said. "And while I don't necessarily agree with his tactics, I agree with 95% of his policies."

"People don't pay me for smiling," Rice said. "They pay me to get results."That's not the typical quote from a politician. And as Rice showed with his vote on Wednesday, he's no normal politician.

The truth or falsity of most political ads is not so easy.

During Game 7 of the World Series on Wednesday, the Trump campaign ran a television ad claiming that he has created six million jobs and half a million manufacturing jobs. Is that statement true or false? Was there a net gain of 500,000 more manufacturing jobs in the United States since Jan. 20, 2017? Or is that a gross number, waiting to be reduced by some number of manufacturing jobs lost?

Is the ad’s use of the active voice, saying that President Trump is creating those jobs, honest? Is Mr. Trump directly responsible? Or did the momentum of the economic recovery since 2010 push manufacturers to add those positions? Should Facebook block the ad if one of seven claims is false? Vetting such claims takes time and effort, and might not be possible at all.

Facebook could also defend political ads by conceding that it must continue the practice to maintain its status and markets

Ad fact-checking can’t be done consistently in the United States. It definitely can’t be done at a global scale — 2.8 billion users of all Facebook-owned services posting in more than 100 languages

Given the task of policing for truth on Facebook, it’s unrealistic and simplistic to demand veracity from a system that is too big to govern.

Might Facebook ban political ads altogether, like Twitter has? Mr. Zuckerberg could concede that it’s not an easy task. What’s not political? If an ad calling for a carbon tax is political, is an ad promoting the reputation of an oil company political?

Those are the false positives we know of. We have no idea how many false negatives Facebook has let slip through.

imagine Facebook’s contracted fact checkers doing that sort of research and interrogation for millions of ads from 22 presidential candidates in the United States, from candidates for 35 Senate seats, 435 House of Representatives seats and thousands of state legislative races.

Over all, Facebook has no incentive to stop carrying political ads. Its revenue keeps growing despite a flurry of scandals and mistakes. So its leaders would lose little by being straight with the public about its limitations and motives. But they won’t. They will continue to defend their practices in disingenuous ways until we force them to change their ways.

We should know better than to demand of Facebook’s leaders that they do what is not in the best interests of the company. Instead, citizens around the world should demand effective legislation that can curb Facebook’s power.

The key is to limit data collection and the use of personal data to ferry ads and other content to discrete segments of Facebook users — the very core of the Facebook business model.

here’s something Congress could do: restrict the targeting of political ads in any medium to the level of the electoral district of the race. Tailoring messages for African-American voters, men or gun enthusiasts would still be legal, as this rule would not govern content. But people not in those groups would see those tailored messages as well and could learn more about their candidates.

Currently, two people in the same household can receive different ads from the same candidate running for state senate. That means a candidate can lie to one or both voters and they might never know about the other’s ads. This data-driven obscurity limits accountability and full deliberation.

A reason to be concerned about false claims in ads is that Facebook affords us so little opportunity to respond to ads not aimed at us personally. This proposal would limit that problem.

The overall regulatory goal should be to install friction into the system of targeted digital political ads

This process would not be easy, as political incumbents and powerful corporations that sell targeted ads (not just Facebook and Google, but also Verizon, AT&T, Comcast and The New York Times, for example) are invested in the status quo.

We can’t expect corporate leaders to do anything but lead their corporations. We can’t expect them to be honest with us, either. We must change their businesses for them so they stop undermining our democracies.

“We were very proud of the work that we were doing. Very proud of letting the president be the president because he was elected as the president,” he said. “But again, all of that changed on Wednesday and I don’t know why.”

He continued Tuesday to make unfounded allegations about the integrity of the process, and vowed more legal action.

Trump and Murphy faced increasing pressure to kickstart the transition process.

he shift comes as Trump's nearly impossible path to overturning the election outcome looks even more improbable.

The New York Times reported that White House chief of staff Mark Meadows, White House counsel Pat Cipollone and Trump's personal lawyer, Jay Sekulow, all urged the president to allow the transition to begin.

Over the weekend, a federal judge issued a blistering order, dismissing the Trump campaign's bid to delay certification of votes in Pennsylvania. Biden leads Trump in the state by more than 81,000 votes.

Trump also failed to prevent the state of Michigan from certifying Biden's win there.

More Republican lawmakers are also calling on Trump to accept the election results.

"When you are in public life, people remember the last thing you do,"

The move by GSA will allow the Biden transition team to access millions of dollars in federal funding, as well as to begin meeting with government agencies to discuss policy ahead of the presidential inauguration on Jan. 20, 2021.

Trump's vote count makes him the second-highest vote earner in American history.

the President has refused to concede the race and continues to make baseless claims about widespread voter fraud.

Biden won 306 electoral votes, while Trump has 232. Two hundred and seventy electoral votes are needed to become president.

A number of states have certified their election results, including Pennsylvania, Wisconsin, Nevada, Georgia and Michigan.

The campaign has mounted legal challenges that have failed to gain any traction, with many of the cases being dismissed by judges for lack of evidence.

Despite Trump's refusal to concede, Biden has continued to build out his administration and has named several key nominees and appointees to top roles in his administration.

On Tuesday, Biden introduced a diverse economic team, including Janet Yellen, who would be the first woman as Treasury secretary if confirmed by the Senate.

Mr. Biden, the Democratic presidential nominee, echoed the “dark winter” language during the most recent presidential debate, and he is already using his bully pulpit to promote and reinforce a culture of mask wearing.

He could use his authority under federal transit law to require masks on public transportation. He could also prod governors who are resisting mask mandates to at least require masks in public buildings in their states.

Instead of making it about the president’s coercive authority under law it should be about whether the president can support a norm that supports public health, which is in people’s self interest

Experts say there is growing scientific evidence that face masks can considerably reduce the transmission of respiratory viruses like the one that causes Covid-19.

Research also shows that states that have passed mask mandates have had lower growth rates of Covid-19, beginning on the day the mandate was passed

the Institute for Health Metrics and Evaluation at the University of Washington estimated that “universal mask use” — when 95 percent of people wear masks in public — could prevent nearly 130,000 deaths from Covid-19 in the coming months, though those numbers are based on certain assumptions and could change if people alter their behavior

any hint of a sweeping federal requirement would “go over like a lead balloon” and “divide and harden areas of the country in opposition,”

that has not produced the kind of compliance that public health experts say is necessary to reduce the spread of the virus

Some public health experts fear that Mr. Trump — who routinely mocks Mr. Biden for wearing masks and whose aides often forgo them even as the White House has become its own coronavirus hot spot — has so poisoned the discussion around masks that wearing them will always be construed as a political statement.

She also suggested that insurance industry executives might be persuaded to adjust their policies to require that businesses mandate mask wearing by customers and employees in order to receive coverage.

“There’s a presumption that a mask mandate would have to be backed up with fines and set off scuffles with law enforcement,

There is some evidence that norms are changing.

“What’s absolutely critical is for people to understand how long of a con this actually has been, that it is not the case that these narratives have only emerged in the wake of Biden’s victory,” Ms. Phillips said. “Donald Trump himself and all of his surrogates and the media that supports him have been seeding this narrative for months and months and months, talking about voting irregularities long before any votes were cast.”

The Federalist published an article on Tuesday stating that there was “increasingly good evidence of large-scale voter fraud in key states” and linked to four social media posts to support the claim.

The right-wing sites’ claims have been bolstered by Republican leaders and Trump administration officials, including Senator Lindsey Graham of South Carolina, Senator Mitch McConnell of Kentucky and Secretary of State Mike Pompeo, who have declined to publicly recognize Mr. Biden’s victory at the polls.

Some right-leaning news outlets seemed to accept the Trump loss, but often inconsistently and halfheartedly.

Some of the right-wing sites’ postelection coverage has hit on the same theme: a frustration with Fox News, which projected Mr. Biden as the winner at 11:40 a.m. on Saturday and whose anchors have referred to him as the president-elect. “What is happening to Fox News?”

They thought he would grow into the normalcy of the presidency. He didn’t. He took their silence as license. And by the time they thought they needed to confront him, he had grown too strong for them to do so.

Trump is once again taking Republicans’ silence as license, and by the time they speak up, he could be too invested in the idea of resisting the Election Day reality.

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.

It is the policy of the government of North Korea, in my judgment, to use its capacity to do harm to elicit support from those who might be harmed by actions they would agree not to take

The criticism of the Bush administration would be that it, in all of this tough talk and rebuffing the Sunshine Policy, that they have failed to get to the negotiating table and that things have only gotten worse.

The Sunshine Policy, we now know, involves a lot less sunshine, a lot less light than heat -- massive payments, as I understand it -- in order to stage meetings that have political ramifications within South Korea, without any significant movement by the North Koreans in any direction that's any way helpful. So the Sunshine Policy has simply not succeeded. It's a failure.

I think that we had a different view of what the 21st century could be like, with much more of a sense, from our perspective, of trying to have an interdependent world, looking at solving regional conflicts, having strength in alliances, operating within some kind of a sense that we were part of the international community and not outside of it. And I just think that basically many of them, saw the world quite differently.

But the situation is quite different here, in that a strike on Yongbyon is likely to produce another Korean War, with hundreds of thousands, if not over a million, people dead.Well, we don't know whether it would produce another Korean War. But that's a risk.

Well, just a much more zero-sum view of the world. ...

The so-called "Perry approach" was focused primarily on WMD -- did not embrace changes in the conventional force alignment, or did not embrace human rights issues.

because what we are insisting on is that the regional powers get more involved.

Now, this is a tough issue because there's no question that the Chinese should be interested in whether there's a nuclear Korean peninsula, and I know that one of the things the administration wants to do is to get the Chinese to take more responsibility for this.

what should happen is that the North Koreans should freeze whatever they're doing, and we should freeze whatever military buildup and various things we're doing in the area in order to negotiate something new, which would be beyond the Agreed Framework.

The Bush administration is saying we shouldn't have to give them anything. They're violating the Nuclear Nonproliferation Treaty, they're in defiance of the world. They should be held to task; that appeasement leads to more aggressive behavior.

It's not a concession. ... I think that I would not give concessions. There's no reason to. What you do is that you have various quid pro quos in any agreement, but if you decide up front that just having the direct talks is a concession, you're pretty much stuck. That's the problem.

A concession, at least to me, is if one side concedes and the other doesn't. I mean, I think that there are ways that there are things we want, and there are things that they want.

They wanted that reiterated. As far as I know, we have no hostile intent towards North Korea. Why would it have been such a big deal just to reiterate that? It's things like that where this administration has kind of dug its heels in and said anything that we did vis-a-vis North Korea is appeasement.

I completely disagree because I believe that it is essential to see whether there's a way to have some agreements. We talked to Stalin, we talked to Mao, we talked to Khrushchev, and Brezhnev. We made agreements. I don't consider talking appeasement

One of the lines of debate in pursuing Korean policy is whether our focus should be on nonproliferation or whether our focus should be on regional stability. These are two different ways of looking at the North Korean problem.

I think that's an exaggeration. The clear policy of our government is that we find nuclear weapons in North Korea to be unacceptable and intolerable. Nobody wants nuclear weapons in North Korea. So why not talk to them?

I believe the [Agreed Framework] would have been more effective if other players had been more directly involved.

They just want to talk to the United States.Well, do we have to give them what they want all the time?

I was surprised. I'm not surprised some people in the administration thought that. I'm surprised they'd take that policy approach to North Korea. I thought it was counterproductive.

t may be therapeutic for us to to talk that way, but does not accomplish our objectives, and does not enhance our security. Indeed, as it's turning out, I think it's putting it in some danger

I think it's quite possible that the North Koreans have already decided that they're going to become a declared nuclear state and that no amount of dialogue will stop them from that.

The world is running out of time.

For us to strike militarily at North Korea, given the risk that we would be incurring for South Korea, would be one of the most immoral acts conceivable. So we are left then, with only the option of engaging with them.

But, yes, it's extortion, and we're rewarding bad behavior. But much of diplomacy is rewarding bad behavior. You're trying to figure out how you can stop the worst of the behavior at the lowest-possible price

I think they've not accomplished much that's good.

preemptive war, preventive war -- kind of runs up against its match in the Korean peninsula?

Why are we doing in Iraq what we're not trying to do in North Korea?

And that's the whole problem with one, the axis of evil concept and two, the doctrine, if it is a doctrine, of preemptive deterrence. That there are some things that you can't preemptively deter. And North Korea I think is a classic example. ...

Those who criticize the deal because they cheated on it, I think are not understanding the nature of international politics. We have done deals with people who we expected might well cheat. And indeed, the Soviet Union cheated on all kinds of deals, massively in the biological weapons convention. You look at the deal and say

I think they're worried about the survival of their regime, independent of what we would do, because they know that they are in deep trouble, in terms of their economy.

I think the North Koreans are truly concerned about their security.