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Former President Franklin D. Roosevelt loved the prayer so much that in 1945 he had it engraved in the mantel above a stone fireplace in the State Dining Room.

These sentiments about honor and wisdom, shared for over two centuries by our best presidents, are now at the center of this year's presidential contest.

Within a decade, faith in the federal government as a whole dropped 41 points.

Faith in elected leaders rose to 55% in 2002, but by 2015 -- just before Trump took office -- it had dropped again, this time to only 19% of Americans saying they trusted the federal government all or most of the time.

Washington Post cataloging his over 20,000 false or misleading statements.

And a recent Pew poll measuring international sentiments across 13 countries found that the international community was more trusting of Russian President Vladimir Putin and Chinese President Xi Jinping than of Trump.

Indeed, I believe that the restoration of trust should be the single highest priority of our next president. Everything else will flow from there.

First, our next president should set a new tone in the White House on day one, proclaiming that honesty, dignity and respect for others will be the new marching orders.

Ford proclaimed "that truth is the glue" that holds us all together. He believed it and soon his followers did, too.

Second, our next president needs every department to review and refresh its ethics codes and then require every new political appointee to attend no-nonsense briefings on what is in bounds and what is out of bounds.

Third, our next president needs to review and overhaul those who now serve as inspectors general across the federal landscape.

In writing his magisterial biography of Harry Truman, historian David McCullough concluded that character is the single most important quality a president must have.

So, the question before us is simple: Will the wise and the honest prevail over the next four years? The answer really rests with you, the voters. You are the ultimate stewards of our democracy.

In the bid to lock in new rules before Jan. 20, Mr. Trump’s team is limiting or sidestepping requirements for public comment on some of the changes and swatting aside critics who say the administration has failed to carry out sufficiently rigorous analysis.

Every administration pushes to complete as much of its agenda as possible when a president’s term is coming to an end, seeking not just to secure its own legacy but also to tie the hands of any successor who tries to undo its work.

If Democrats take control of Congress, they will have the power to reconsider some of these last-minute regulations, through a law last used at the start of Mr. Trump’s tenure by Republicans to repeal certain rules enacted at the end of the Obama administration.

Two main hallmarks of a good regulation is sound analysis to support the alternatives chosen and extensive public comment to get broader opinion

Administration officials said they were simply completing work on issues they have targeted since Mr. Trump took office in 2017 promising to curtail the reach of federal regulation.

Editors’ Picks

But the Trump administration is also working to fill key vacancies on scientific advisory boards with members who will hold their seats far into the next presidential term, committees that play an important role in shaping federal rule making

almost

Workers across the country deserve a chance to fully examine and properly respond to these potentially radical changes,

The Departments of Labor and Homeland Security are using a tactic known as an interim final rule, more typically reserved for emergencies, to skip the public comment period entirely and to immediately enact two regulations that put much tougher restrictions on work visas for immigrants with special skills. The rule change is part of the administration’s longstanding goal of limiting immigration.

The Homeland Security Department is also moving, again with an unusually short 30-day comment period, to adopt a rule that will allow it to collect much more extensive biometric data from individuals applying for citizenship, including voice, iris and facial recognition scans, instead of just the traditional fingerprint scan.

A third proposed new Homeland Security rule would require sponsors of immigrants to do more to prove they have the financial means to support the individual they are backing, including three years’ worth of credit reports, credit scores, income tax returns and bank records.

Unlike most of the efforts the administration has pushed, the rules intended to tighten immigration standards would expand federal regulations, instead of narrowing them

The Environmental Protection Agency, which since the start of the Trump administration has been moving at a high speed to rewrite federal regulations, is expected to complete work in the weeks that remain in Mr. Trump’s term on two of the nation’s most important air pollution rules: standards that regulate particulates and ozone emitted by factories, power plants, car exhaust and other sources.

But it is nonetheless pushing to have the rule finished before the end of Mr. Trump’s first term, limiting the period of public comment to 30 days, half the amount of time that agencies are supposed to offer.

Mr. Trump signed an executive order last year directing the Transportation Department to enact the rule within 13 months — even before it had been formally proposed.

The change was backed by the railroad and natural gas industry, which has donated millions of dollars to Mr. Trump, after construction of pipelines had been blocked or slowed after protests by environmentalists.

the proposal provoked an intense backlash from a diverse array of prominent public safety officials.

What that index didn't take into account — and what has compounded months of governmental failures — is that even before COVID-19 arrived on its shores, the U.S. was an unusually sick country for its level of wealth and development.

High blood pressure, obesity and metabolic disorders are all on the rise in the U.S.

Healthy life expectancy — the number of years people can expect to live without disability — is 65.5 years in the U.S., more than two decades fewer than in Japan.

65,700 Americans died of drug overdoses in 2019, more than double the number in 2010. Those deaths account for more than half of all drug overdose fatalities worldwide and held down life expectancy in the U.S.

Mortality for mothers and children under 5 is 6.5 per 1,000 live births in the U.S., compared to 4.9 for other wealthy countries.

All in all, more than 40% of American adults have a pre-existing health condition that puts them at higher risk of severe COVID-19.

A study published in August found cardiovascular disease can double a patient's risk of dying from COVID-19, while diabetics — who number more than 30 million in the U.S. — are 1.5 times more likely to die.

Context: Lancet Editor-in-Chief Richard Horton has called COVID-19 a "syndemic" — a synergistic epidemic of a new and deadly infectious disease and numerous underlying health problems. The U.S. is squarely in the heart of that syndemic.

Those conditions are particularly prevalent in minority communities with unequal health care access that have disproportionately suffered from COVID-19.

A report from McKinsey earlier this month estimated that poor health costs the U.S. economy about $3.2 trillion a year

For every $1 invested in targeting population health, the U.S. stands to gain almost $4 in economic benefit, and altogether health improvements could add up to a 10% boost to U.S. GDP by 2040.

The bottom line: There is no excuse for the way the U.S. has mishandled COVID-19, but the seeds of this catastrophe were planted well before the novel coronavirus arrived on American shores.

2. How movement spread COVID-19

What's happening: Researchers in Germany studied the effect of entry bans and mandatory quarantines on COVID-19 mortality, and found the earlier such measures were implemented, the greater the effect they had on limiting deaths.

Of note: The study found mandatory quarantines for incoming travelers were more effective than outright entry bans, largely because such bans often exempted citizens and permanent residents, while quarantines usually applied to everyone.

The U.S. lost track of at least 1,600 people flying in from China in just the first few days after the ban went into effect, according to reporting from the AP.

Border controls are of little use if governments don't track and quarantine travelers coming from infected areas.

The bottom line: A virus only moves with its host. One lesson we should learn for future pandemics is that restricting that movement is key to controlling a new pathogen, even though the costs of such controls will only grow in a globalized world.

In 2000, he became the first Anglophone to win a permanent position at the Collège de France, where he held the chair in the philosophy and history of scientific concepts until he retired in 2006.

His work in the philosophy of science was groundbreaking: He departed from the preoccupation with questions that had long concerned philosophers. Arguing that science was just as much about intervention as it was about representation, be helped bring experimentation to center stage.

Hacking often argued that as the human sciences have evolved, they have created categories of people, and that people have subsequently defined themselves as falling into those categories. Thus does human reality become socially constructed.

His book “The Emergence of Probability” (1975), which is said to have inspired hundreds of books by other scholars, examined how concepts of statistical probability have evolved over time, shaping the way we understand not just arcane fields like quantum physics but also everyday life.

“I was trying to understand what happened a few hundred years ago that made it possible for our world to be dominated by probabilities,” he said in a 2012 interview with the journal Public Culture. “We now live in a universe of chance, and everything we do — health, sports, sex, molecules, the climate — takes place within a discourse of probabilities.”

Whatever the subject, whatever the audience, one idea that pervades all his work is that “science is a human enterprise,” Ragnar Fjelland and Roger Strand of the University of Bergen in Norway wrote when Professor Hacking won the Holberg Prize. “It is always created in a historical situation, and to understand why present science is as it is, it is not sufficient to know that it is ‘true,’ or confirmed. We have to know the historical context of its emergence.”

Regarding one such question — whether unseen phenomena like quarks and electrons were real or merely the theoretical constructs of physicists — he argued for reality in the case of phenomena that figured in experiments, citing as an example an experiment at Stanford that involved spraying electrons and positrons into a ball of niobium to detect electric charges. “So far as I am concerned,” he wrote, “if you can spray them, they’re real.”

“I have long been interested in classifications of people, in how they affect the people classified, and how the effects on the people in turn change the classifications,” he wrote in “Making Up People

“I call this the ‘looping effect,’” he added. “Sometimes, our sciences create kinds of people that in a certain sense did not exist before.”

In “Why Race Still Matters,” a 2005 article in the journal Daedalus, he explored how anthropologists developed racial categories by extrapolating from superficial physical characteristics, with lasting effects — including racial oppression. “Classification and judgment are seldom separable,” he wrote. “Racial classification is evaluation.”

Similarly, he once wrote, in the field of mental health the word “normal” “uses a power as old as Aristotle to bridge the fact/value distinction, whispering in your ear that what is normal is also right.”

In his influential writings about autism, Professor Hacking charted the evolution of the diagnosis and its profound effects on those diagnosed, which in turn broadened the definition to include a greater number of people.

Encouraging children with autism to think of themselves that way “can separate the child from ‘normalcy’ in a way that is not appropriate,” he told Public Culture. “By all means encourage the oddities. By no means criticize the oddities.”

His emphasis on historical context also illuminated what he called transient mental illnesses, which appear to be so confined 0cto their time 0c 0cthat they can vanish when times change.

“hysterical fugue” was a short-lived epidemic of compulsive wandering that emerged in Europe in the 1880s, largely among middle-class men who had become transfixed by stories of exotic locales and the lure of trave

His intellectual tendencies were unmistakable from an early age. “When he was 3 or 4 years old, he would sit and read the dictionary,” Jane Hacking said. “His parents were completely baffled.”

He wondered aloud, the interviewer noted, if the whole universe was governed by nonlocality — if “everything in the universe is aware of everything else.”“That’s what you should be writing about,” he said. “Not me. I’m a dilettante. My governing word is ‘curiosity.’”

even after the 7 October massacre had stirred memories of the bleakest chapters of the Jewish past – and prompted a surge in antisemitism across the world – Jews were being told exactly how they can and cannot speak about their pain. We’re not to mention the Holocaust, one scholar advised, because that would be “weaponising” it. Historical context about the Nakba, the 1948 dispossession of the Palestinians, is – rightly – deemed essential. But mention the Nazi murder of 6 million Jews – the event that finally secured near-universal agreement among the Jewish people, and the United Nations in 1947, that Jews needed a state of their own – and you’ve broken the rules. Because it’s impossible that both sides might have suffered historic pain.

Instead, a shift is under way that has been starkly revealed during these past three weeks. It squeezes the Israel-Palestine conflict into a “decolonisation” frame it doesn’t quite fit, with all Israelis – not just those in the occupied West Bank – defined as the footsoldiers of “settler colonialism”, no different from, say, the French in Algeria

They have been framed as the modern world’s ultimate evildoer: the coloniser.

That matters because, in this conception, justice can only be done once the colonisers are gone

What’s more, such a framing brands all Israelis – not just West Bank settlers – as guilty of the sin of colonialism. Perhaps that explains why those letter writers could not full-throatedly condemn the 7 October killing of innocent Israeli civilians. Because they do not see any Israeli, even a child, as wholly innocent.

the late Israeli novelist and peace activist Amos Oz was never wiser than when he described the Israel/Palestine conflict as something infinitely more tragic: a clash of right v right. Two peoples with deep wounds, howling with grief, fated to share the same small piece of land.

even now, as their stories are being dramatized in a movie and shown in theaters across the country, there is a campaign in Oklahoma — this time with legislation — to deter the history from being taught in schools.

The movement to suppress elements of American history extends well beyond Oklahoma. According to an analysis by The Washington Post, more than two dozen states have adopted laws that make it easier to remove books from school libraries and to prevent certain teaching on race, gender and sexuality

In 2023, PEN America, which defends freedom of speech, reported that book bans in U.S. public school classrooms and libraries had surged 33 percent over the previous school year, with more than 3,000 recorded removals; among them are classics by the Nobel laureate Toni Morrison (banned in 30 school districts) and Margaret Atwood (banned in 34). School curriculums are being revised to mask discomfiting truths — so much so that in Florida students will now be taught that some African Americans benefited from slavery because it gave them “skills.”

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.

Things that were long big fun now overwhelm, exhaust and annoy. The holiday season is an extended exercise in excess and loud, often sleazy sweaters.

Which means it is nothing of the sort. This is the drag equivalent of fun and suggests that fun is done.

Adults assiduously record themselves appearing to have something masquerading as “fun,” a fusillade of Coachellic micro social aggressions unleashed on multiple social media platforms. Look at me having so much FUN!

Vacations are overscheduled with too many activities, FOMO on steroids, a paradox of choice-inducing decision fatigue, so much so that people return home exhausted and in need of another one.

Weddings have morphed into multistage stress extravaganzas while doubling as express paths to insolvency: destination proposals for the whole family, destination bachelorette and bachelor blowouts, destination weddings in remote barns with limited lodging, something called a “buddymoon” (bring the gang!) and planners to help facilitate the same custom cocktailsness of it all.

What could be a greater cause for joy or more natural than having a baby? Apparently, not much these days. Impending parenthood is overthought and over-apped, incorporating more savings-draining events that didn’t exist a few decades ago: babymoons and lethal, fire-inducing, gender-reveal gatherings and baby showers so over-the-top as to shame weddings.

Retirements must be purposeful. Also, occasions for an acute identity crisis. You need to have a plan, a mission, a coach, a packed color-coded grid of daily activities in a culture where our jobs are our identities, our worth tied to employment.

“I feel like I should be having more fun than I’m actually having,” says Alyssa Alvarez, a social media marketing manager and DJ in Detroit, expressing a sentiment that many share. “There are expectations of what I want people to believe that my life is like rather than what my life is actually like.”

“The world is so much less about human connection,” says Amanda Richards, 34, who works in casting in Los Angeles and is a graduate of Cudworth’s course. “We do more things virtually. People are more isolated. And there’s all this toxic positivity to convince people of how happy you are.”

For eons, early adulthood was considered an age of peak fun. Now, according to several studies, it’s a protracted state of anxiety and depression.

Because there is now a coach for everything, Alvarez hired the “party coach” Evan Cudworth, taking his $497 course this fall on how to pursue “intentional fun.” (It now costs $555.)

Blame it on an American culture that values work, productivity, power, wealth, status and more work over leisure

Blame it on technological advances that tether us to work without cessation

Blame it on the pandemic, which exacerbated so much while delivering Zoomageddon.

Blame it on 2004, with the advent of Facebook, which led to Twitter (okay, X), Instagram, Threads, TikTok and who-knows-what lurking in the ether.

Blame it again on 2004 and the introduction of FOMO, our dread of missing out, broadcast through multiple social media spigots

“So many people are retreating into their phones, into anxiety,” says Cudworth, 37, from Chicago. “I’m helping people rediscover what fun means to them.”

His mandate is redefining fun: cutting back on bingeing screen time, eradicating envy scrolling, getting outside, moving, dancing. “With technology, we don’t allow ourselves to be present. You’re always thinking ‘something is better around the corner,’” Cudworth says, the now squandered in pursuit of the future.

Instead of this being the most wonderful time of the year, we battle holiday fatigue, relentless beseeching for our money and, if Fox News is to be believed, a war on Christmas that is nearing its third decade.

ow do Americans spend their leisure hours when they might be having fun with others, making those vital in-person connections? Watching television, our favorite free time and “sports activity” (yes, that’s how it’s classified), according to the Bureau of Labor Statistics, an average of 2.8 hours daily.

“That’s way more television than you really need. We put play on the back burner,” says Pat Rumbaugh, 65, of Takoma Park, Md. She’s “The Play Lady,” who organizes unorganized play for adults

Catherine Price, the author of “The Power of Fun: How to Feel Alive Again,” believes “we’re totally misdoing leisure” and “not leaving any room for spontaneity.”

To Price, True Fun is the confluence of connection (other people, nature), playfulness (lightheartedness, freedom) and flow (being fully engaged, present), which is not as challenging as it sounds. “You can have fun in any context. Playfulness is about an attitude,”

Back in the day, co-workers were friends. (Sometimes, more.) After hours, they gathered for drinks, played softball. Today, because of email, Slack and remote work, offices are half empty and far quieter than libraries.

“We go to work and there’s no sense of connection and camaraderie,” says Davis, who was long employed by his city’s department of parks and recreation. “People feel emotionally disconnected. Healthy conversations are the precursor of fun. We’ve lost the art of communication. Our spirit comes home with us. If you don’t communicate at work, what are you coming home with?”

It is action in service of change, not information in service of outrage.

“The people thinking strategically about how to win the 2022 election are the ones doing the most for democracy,” said Daniel Ziblatt, a political scientist at Harvard and one of the authors of “How Democracies Die.”

“I’ve heard people saying bridges don’t save democracy — voting rights do. But for Democrats to be in a position to protect democracy, they need bigger majorities.”

There are people working on a Plan B

He spends his days obsessing over mayoral races in 20,000-person towns, because those mayors appoint the city clerks who decide whether to pull the drop boxes for mail-in ballots and small changes to electoral administration could be the difference between winning Senator Ron Johnson’s seat in 2022 (and having a chance at democracy reform) and losing the race and the Senate. Wikler is organizing volunteers to staff phone banks to recruit people who believe in democracy to serve as municipal poll workers, because Steve Bannon has made it his mission to recruit people who don’t believe in democracy t

The difference between those organizing at the local level to shape democracy and those raging ineffectually about democratic backsliding — myself included — reminds me of the old line about war: Amateurs talk strategy; professionals talk logistics. Right now, Trumpists are talking logistics.

“We do not have one federal election,” said Amanda Litman, a co-founder of Run for Something, which helps first-time candidates learn about the offices they can contest and helps them mount their campaigns. “We have 50 state elections and then thousands of county elections. And each of those ladder up to give us results.

While Congress can write, in some ways, rules or boundaries for how elections are administered, state legislatures are making decisions about who can and can’t vote. Counties and towns are making decisions about how much money they’re spending, what technology they’re using, the rules around which candidates can participate.”

Protecting democracy by supporting county supervisors or small-town mayors — particularly ones who fit the politics of more conservative communities — can feel like being diagnosed with heart failure and being told the best thing to do is to double-check your tax returns and those of all your neighbors.

These races get zero national attention. They hardly get local attention. Turnout is often lower than 20 percent. That means people who actually engage have a superpower. You, as a single dedicated volunteer, might be able to call and knock on the doors of enough voters to win a local election.”

“One thing I was really struck by when I first started getting involved in politics is how much power there is in just showing up to things,” she said. “If you love libraries, libraries have board meetings. Go to the public meeting. See where they’re spending their money. We’re supposed to be participating. If you want to get involved, there’s always a way.”

For example, a school board can remove the book Maus from its eighth-grade curriculum (because of profanity and mouse nudity), but should it? A school board can remove To Kill a Mockingbird (for alleged racial insensitivity) from a required reading list, but should it? 

In Board of Education v. Pico, a 1982 Supreme Court case that cast doubt on the ability of public schools to ban library books on the basis of their ideas alone, the court’s plurality described a purpose of public education as preparing “individuals for participation as citizens," and as vehicles for "inculcating fundamental values necessary to the maintenance of a democratic political system.”

Systematically suppressing ideas in public education does not help our students learn liberty, nor does it prepare them for pluralism. It teaches them to seek protection from ideas and that the method for engaging with difference is through domination. 

Our nation is a diverse pluralistic constitutional republic, and as James Madison noted in Federalist No. 10, we cannot respond to the inevitable rise of competing factions by suppressing liberty, tempting as that always is. Madison was shrewd and realistic enough to recognize that liberty empowers factions. As he put it, “Liberty is to faction what air is to fire, an aliment without which it instantly expires.”

At the same time, however, “it could not be less folly to abolish liberty, which is essential to political life, because it nourishes faction, than it would be to wish the annihilation of air, which is essential to animal life, because it imparts to fire its destructive agency.”

I mounted a Christian defense of American classical liberalism, and I made the case that–while no system of government is perfect–American classical liberalism does possess two cardinal virtues. Its protections of liberty recognize both the dignity and the imperfection of man. 

And few liberties encompass both that dignity and imperfection more than the right to speak. The violation of that right–the deprivation of that dignity–can inflict a profound moral injury on a citizen and it can help perpetuate profound injustices in society and government. As Douglass noted, free speech is the “dread of tyrants.”

Moreover, as John Stuart Mill’s argument for free speech demonstrates, free speech rests on a foundation of humility.

Summarizing Mill, Greg articulates “three possibilities in any given argument:

You are wrong, in which case freedom of speech is essential to allow people to correct you.

You are partially correct, in which case you need free speech and contrary viewpoints to help you get a more precise understanding of what the truth really is.

You are 100% correct, in which unlikely event you still need people to argue with you, to try to contradict you, and to try to prove you wrong. Why? Because if you never have to defend your points of view, there is a very good chance you don’t really understand them, and that you hold them the same way you would hold a prejudice or superstition. It’s only through arguing with contrary viewpoints that you come to understand why what you believe is true.

In short, I value free speech, not so much because I’m right and you need to hear from me, but rather because I’m very often wrong and need to hear from you. Free speech rests upon a foundation of human fallibility.

As American animosity rises, we simply cannot censor our way to social peace or unity. We can, however, violate the social compact, disrupt the founding logic of our republic, and deprive American students and American citizens of the exchange of ideas and of the liberty that has indeed caused, as Douglass prophesied, “thrones, dominions, principalities, and powers, founded in injustice and wrong” to tremble in the face of righteous challenge.

During the last election the government pledged to change this, and it is now hammering out a new Constitution. The stakes are high: This is happening as Prime Minister Recep Tayyip Erdogan tries to end a long campaign by Kurdish nationalists, sometimes peaceful and sometimes not, calling for a devolution of power and the right to think of themselves not as Turks but as Kurds.

Globalization helps drive these patterns to new extremes. Money flows into suburbs like San Marino and Palos Verdes, where Asian immigrants buy up expensive properties and generously donate their time and money to the local schools. Money flows out of poorer suburbs like South Gate, Bell and Huntington Park, all heavily Latino, where disposable income is tight and many families export remittances to a home country. New poverty builds upon old impoverishment. Infrastructure is stretched as renters crowd into dwellings that were modest to begin with. The toxic footprint of departed industries is left behind for new residents to contend with.

Many of Los Angeles’s middling suburbs have also slipped, especially those ravaged by plant closures since the 1980s. The southern section of blue-collar suburbs was hit especially hard. Here, suburbia transformed from comfortable communities housing unionized workers with well-paying jobs in local factories that gave them access to a middle-class lifestyle to fiscally strained communities housing immigrants working in low-paying, nonunion jobs.

Outer suburbs have fared little better. As home costs skyrocketed in recent decades, families chased “affordable” housing to the exurbs. They took on outsize mortgages and monster commutes, and they took with them congested roads, smog and sprawl. Compounding these strains, tax revenues lagged behind the cost of schools, roads, parks and libraries — the very infrastructure necessary to sustain middle-class life. This edifice came crashing down in the recession.

Policies to redress suburban inequality must focus not only on factors like income but also on tax equity across metro areas and regional planning that fairly distributes resources and responsibilities (like affordable housing). We should limit the mortgage-interest deduction for second homes and for values above the regional median. These steps would reduce distortions that inflate housing prices and concentrate wealth in what are already wealthy places.

Republicans say they plan to use the occasion to demand deep federal spending cuts, with House Speaker John A. Boehner (Ohio) insisting on a dollar reduction in federal spending for every dollar increase in the nation’s borrowing limit.

But the White House says President Obama will not negotiate this point, because the debt ceiling represents a limit to obligations that Congress already has promised to pay. “What he will not do — as he has made clear — is negotiate with Congress over Congress’s sole responsibility to pay the bills that Congress has already incurred,” White House press secretary Jay Carney said Monday. “Nobody forced Congress to rack up the bills that it incurred. And it is an abdication of responsibility to say that we’re going to let the country default and cause global economic calamity simply because we’re not getting what we want in terms of our ideological agenda.”

Attracts students from North-West Frontier Province and tribal areas where militant groups are strong

Library named in honour of Osama Bin Laden

Staff at the website paid tribute to their murdered colleague, and vowed to continue to stand up to militant groups.

"His death is the grim reminder that whoever raises voice against Taliban [and other militant groups] in Pakistan will not be spared. And when they have to murder, they never fail."

There is, as Adam Smith said, “a great deal of ruin in a nation.” But there is also a great deal to love in our own, if you choose to look for it. There is abuse, addiction, abandonment — and kindness, courtesy and compassion

I fully expect the next generation to be a source of renewal, because I am confident that certain core ideals and institutions best fit human beings and allow them to flourish. I believe that our children and grandchildren will be brave, free and daring in pursuit of ageless ideals — and that teaching them to despair would be the true source of national ruin.

For a certain kind of right-wing nationalist, it always comes down to this. “Our people” must be preserved from invasion, rape and machete attacks by other people whose arrival would cause “a country, a people, a civilization” to die.

Trump has achieved one good thing in our politics. He has revealed motives that used to be hidden by “political correctness.” They were also hidden by human decency. In terms Decius would understand: This is playing with fire!

What’s less discussed is the polarization of culture, and the new echo chambers within which we hear about and experience today’s cultural hits

There’s just about nothing as popular today as old sitcoms were; the only bits of shared culture that come close are periodic sporting events, viral videos, memes and occasional paroxysms of political outrage (see Meryl Streep’s Golden Globes speech and the aftermath).

we’re returning to the cultural era that predated radio and TV, an era in which entertainment was fragmented and bespoke, and satisfying a niche was a greater economic imperative than entertaining the mainstream.

“We’re back to normal, in a way, because before there was broadcasting, there wasn’t much of a shared culture,

Because it featured little choice, TV offered something else: the raw material for a shared culture. Television was the thing just about everyone else was watching at the same time as you. In its enforced similitude, it became a kind of social glue, stitching together a new national identity across a vast, growing and otherwise diverse nation.

“For most of the history of civilization, there was nothing like TV. It was a really odd moment in history to have so many people watching the same thing at the same time.”

As the broadcast era morphed into one of cable and then streaming, TV was transformed from a wasteland into a bubbling sea of creativity. But it has become a sea in which everyone swims in smaller schools.

Only around 12 percent of television households, or about 14 million to 15 million people, regularly tuned into “NCIS” and “The Big Bang Theory,” the two most popular network shows of the 2015-16 season, according to Nielsen. Before 2000, those ratings would not even have qualified them as Top 10 shows

HBO’s “Game of Thrones” is the biggest prestige drama on cable, but its record-breaking finale drew only around nine million viewers

Netflix’s biggest original drama last year, “Stranger Things,” was seen by about 14 million adults in the month after it first aired. “Fuller House,” Netflix’s reboot of the broadcast sitcom “Full House,” attracted an audience of nearly 16 million. (These numbers are for the entire season, not for single episodes.)

For perspective, during much of the 1980s, a broadcast show that attracted 14 million to 16 million would have been in danger of cancellation.

As people pull back from broadcast and cable TV and jump deeper into streaming, we’re bound to see more shows with smaller audiences.

It’s possible we’re not at the end of the story. Some youngsters might argue that the internet has produced its own kind of culture, one that will become a fount of shared references for years to come. What if “Chewbacca Mom” and the blue and black/white and gold dress that broke the internet one day become part of our library of globally recognized references

What happens if the incoming administration directs that the “Russia did it” file be closed? Would standing intelligence requirements to learn more about this be eliminated? And if they were, what would the agency do with relevant data that would inevitably come through its collection network?

And what about the statute that requires the CIA and the rest of the intelligence community to keep Congress “fully and currently informed” about all significant intelligence activities? Data on a foreign power manipulating the federal electoral process would certainly qualify. What will the White House position be when the agency is asked by Congress if it has learned anything more on the issue?

His future workforce will be looking for clues about his willingness to defend them against charges of incompetence and politicization simply for saying what their craft tells them to be true.

“! Keep Anna Chennault working on” South Vietnam, Haldeman scrawled, recording Nixon’s orders. “Any other way to monkey wrench it? Anything RN can do.”

Nixon told Haldeman to have Rose Mary Woods, the candidate’s personal secretary, contact another nationalist Chinese figure — the businessman Louis Kung — and have him press Thieu as well. “Tell him hold firm,” Nixon said.

Throughout his life, Nixon feared disclosure of this skulduggery. “I did nothing to undercut them,” he told Frost in their 1977 interviews. “As far as Madame Chennault or any number of other people,” he added, “I did not authorize them and I had no knowledge of any contact with the South Vietnamese at that point, urging them not to.” Even after Watergate, he made it a point of character. “I couldn’t have done that in conscience.”

Nixon had cause to lie. His actions appear to violate federal law, which prohibits private citizens from trying to “defeat the measures of the United States.”

Time has yielded Nixon’s secrets. Haldeman’s notes were opened quietly at the presidential library in 2007, where I came upon them in my research for a biography of the former president.

They contain other gems, like Haldeman’s notations of a promise, made by Nixon to Southern Republicans, that he would retreat on civil rights and “lay off pro-Negro crap” if elected president

When Johnson got word of Nixon’s meddling, he ordered the F.B.I. to track Chennault’s movements. She “contacted Vietnam Ambassador Bui Diem,” one report from the surveillance noted, “and advised him that she had received a message from her boss … to give personally to the ambassador. She said the message was … ‘Hold on. We are gonna win. … Please tell your boss to hold on.’ ”

In a conversation with the Republican senator Everett Dirksen, the minority leader, Johnson lashed out at Nixon. “I’m reading their hand, Everett,” Johnson told his old friend. “This is treason.”“I know,” Dirksen said mournfully.

A second type of algorithm can also see the consequences of particular moves far, far in advance of the game by playing millions and millions or perhaps even billions of combinations of moves. In contrast, human Go experts have their experience to rely on, but it is fuzzy by comparison. Think of this as an intellectual version of John Henry and the jackhammer.