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Denver-based oil and gas company K P Kauffman allegedly violated air pollution laws, emitting volatile organic compounds that form smog in the Denver-Julesburg Basin, an area that wasn’t meeting smog standards. The company settled and agreed to pay $1m in eight installments over four years, but it has not been required to pay its second installment because of the freeze. The company did not respond to requests for comment.

Chris Saeger, director of strategic initiatives at Accountable.US, said: “This is exactly the time to make sure support is flowing to the federal, state and local governments that need a hand with responding to the coronavirus crisis and with the environmental problems that these special interests have caused.”

The companies will not be required to pay penalties before 1 June, although they have the option to do so and at least two companies told the Guardian they made payments despite the extension. The EPA would not respond to inquiries about its policy and or say which companies paid penalties.

One company, Virginia power provider Dominion Energy, settled and agreed to pay $1.4m for allegedly releasing 27.5m gallons of water from a coal ash impoundment that seeped into groundwater along the shore of the James River. Coal ash contains dangerous pollutants, including mercury, cadmium and arsenic, which can cause widespread environmental damage. The company said it plans to pay the settlement penalty once it is finalized.

Another alleged violator, one of the world’s largest steel companies, ArcelorMittal, decided to pay the $5m penalty it agreed to for air quality issues at steel plants in East Chicago, Indiana; Burns Harbor, Indiana; and Cleveland, Ohio, according to a spokesman.

BP was accused of emitting too much particle pollution, which is linked to asthma and heart attacks. The justice department’s assistant attorney general Brian Benczkowski represented BP in the past. BP employees have given $85,000 to Trump campaign groups.

One of the most fundamental problems with recycling is that we don’t really know how much of it actually happens because of an opaque global system that too often relies on measuring the material that arrives at the front door of the facility rather than what comes out

What we do know is that with plastics, at least, the amount being recycled is much less than most of us assumed.

According to the Environmental Protection Agency, two of the most commonly used plastics in America — PET (used in soda bottles) and HDPE (used in milk jugs, among other things) — are “widely recycled,” but the rate is really only about 30 percent

Other plastics, like soft wraps and films, sometimes called No. 4 plastics, are not widely accepted in curbside collections.

The E.P.A. estimates that just 2.7 percent of polypropylene — the hard plastic known as No. 5, used to make furniture and cleaning bottles — was reprocessed in 2018

Crunch the sums, and only around 10 percent of plastics in the United States is recycle

the landfill-happy United States is far worse at recycling than other major economies. According to the E.P.A., America’s national recycling rate, just 32 percent, is lower than Britain’s 44 percent, Germany’s 48 percent and South Korea’s 58 percent.

the scientific research over decades has repeatedly found that in almost all cases, recycling our waste materials has significant environmental benefits

We need clearer labeling of what is and is not actually recyclable and transparency around true recycling rates

Recycling steel, for example, saves 72 percent of the energy of producing new steel; it also cuts water use by 40 percent

Recycling a ton of aluminum requires only about 5 percent of the energy and saves almost nine tons of bauxite from being hauled from mines

Even anti-plastics campaigners agree that recycling plastics, like PET, is better for the climate than burning them — a likely outcome if recycling efforts were to be abandoned.

The economic perks are significant, too. Recycling creates as many as 50 jobs for every one created by sending waste to landfills; the E.P.A. estimates that recycling and reuse accounted for 681,000 jobs in the United States alone.

That’s even more true in the developing world, where waste pickers rely on recycling for income.

before we abandon recycling, we should first try to fix it

Companies should be phasing out products that can’t be recycled and designing more products that are easier to recycle and reuse rather than leaving sustainability to their marketing departments.

Lawmakers can help by passing new laws, as cities like Seattle and San Francisco have done, to help increase recycling rates and drive investment into the sector.

Governments can also ban or restrict many problematic plastics to reduce the amount of needless plastics in our everyday lives, for instance in food packaging

According to a 2015 analysis by scientists at the University of Southampton in England, recycling a majority of commonly tossed-out waste materials resulted in a net reduction in greenhouse gas emissions

Greater safety regulations are needed to reduce toxic chemical contents and microplastic pollution caused by the recycling process.

consumers can do their bit by buying recycled products (and buying less and reusing more).

Yes, recycling is broken, but abandon it too soon, and we risk going back to the system of decades past, in which we dumped and burned our garbage without care, in our relentless quest for more. Do that, and like the recycling symbol itself, we really will be going in circles.

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.

Starting from scratch is usually a bad idea. Too often, we assume innovative ideas and meaningful changes require a blank slate. When business projects fail, we say things like, “Let's go back to the drawing board.” When we consider the habits we would like to change, we think, “I just need a fresh start.” However, creative progress is rarely the result of throwing out all previous ideas and innovations and completely re-imagining of the world.

Some experts believe the feathers of birds evolved from reptilian scales. Through the forces of evolution, scales gradually became small feathers, which were used for warmth and insulation at first. Eventually, these small fluffs developed into larger feathers capable of flight.

The process of human flight followed a similar path. We typically credit Orville and Wilbur Wright as the inventors of modern flight. However, we seldom discuss the aviation pioneers who preceded them like Otto Lilienthal, Samuel Langley, and Octave Chanute. The Wright brothers learned from and built upon the work of these people during their quest to create the world's first flying machine.

The Toaster Project is an example of how we often fail to notice the complexity of our modern world. When you buy a toaster, you don't think about everything that has to happen before it appears in the store. You aren't aware of the iron being carved out of the mountain or the oil being drawn up from the earth.

The standard explanation of this unhinging, repeated in graduate-school classrooms and in advice to politicians, is technological change.

This explanation, known as skill-biased technical change, is so common that economists just call it S.B.T.C. They use it to explain why everyone from the extremely rich to the just-kind-of rich are doing so much better than everyone else.

For all their disagreements, Autor and Mishel are allies of sorts. Both are Democrats who have advised President Barack Obama, and both agree that rampant inequality can undermine democracy and economic growth by fostering despair among workers and corruption among the wealthy

The change came around 1978, Mishel said, when politicians from both parties began to think of America as a nation of consumers, not of workers.

each administration and Congress have made choices — expanding trade, deregulating finance and weakening welfare — that helped the rich and hurt everyone else. Inequality didn’t just happen, Mishel argued. The government created it.

Computers and the Internet, Mishel argued, are just new examples on the continuum and cannot explain a development like extreme inequality, which is so recent. So what happened?

David Autor, one of the country’s most celebrated labor economists, took the stage, fumbled for his own PowerPoint presentation and then explained that there was plenty of evidence showing that technological change explained a great deal about the rise of income inequality. Computers, Autor says, are fundamentally different. Conveyor belts and massive steel furnaces made blue-collar workers comparatively wealthier and hurt more highly skilled crafts­people, like blacksmiths and master carpenters, whose talents were disrupted by mass production. The computer revolution, however, displaced millions of workers from clerical and production occupations, forcing them to compete in lower-paying jobs in the retail, fast-food and home health sectors. Meanwhile, computers and the Internet disproportionately helped people like doctors, engineers and bankers in information-intensive jobs. Inequality was merely a side effect of the digital revolution, Autor said; it didn’t begin and end in Washington.

Levy suggested seeing how inequality has played out in other countries

In Germany, the average worker might make less than an American, but the government has established an impressive apprenticeship system to keep blue-collar workers’ skills competitive.

For decades, the Finnish government has offered free education all the way through college. It may have led to high taxes, but many believe it also turned a fairly poor fishing economy into a high-income, technological nation.

On the other hand, Greece, Spain and Portugal have so thoroughly protected their workers that they are increasingly unable to compete

Inequality has risen almost everywhere, which, Levy says, means that Autor is right that inequality is not just a result of American-government decisions. But the fact that inequality has risen unusually quickly in the United States suggests that government does have an impact

Still, economists certainly cannot tell us which policy is the right one. What do we value more: growth or fairness? That’s a value judgment. And for better or worse, it’s up to us.

“It may not get approved the first time, and it may not get approved the second time, but the Democrats who will try not to approve it” will be at risk, he said,

He described the health law as a catastrophe. “I feel that repeal and replace have to be together, for very simply, I think that the Democrats should want to fix Obamacare,”

After meeting with House Republicans on Tuesday, Mr. Ryan took a similar tone, calling the campaign to repeal the health law “a rescue mission to save families who are getting caught up in the death spiral that has become Obamacare.”

That legislation would take Democratic cooperation to be passed, because Senate Republicans are eight votes short of a filibuster-proof majority.

Far from a “death spiral,” Mr. Obama and congressional Democrats call the Affordable Care Act the best health law since the creation of Medicare and Medicaid in 1965.

Obama administration reported on Tuesday that more than 11.5 million people nationwide had signed up for health insurance or been automatically re-enrolled under the Affordable Care Act as of Dec. 24, 2016.

By any reasonable standard, the 2016 election was deeply tainted.

What we’re looking at, all too obviously, is an American kakistocracy — rule by the worst.

We don’t know, although Mr. Trump’s creepy obsequiousness to Vladimir Putin makes it hard to dismiss these allegations

Even given what we do know, however, no previous U.S. president-elect has had less right to the title. So why shouldn’t we question his legitimacy?

he’s lashing out at and threatening anyone and everyone who criticizes him, while refusing even to admit that he lost the popular vote.

Was there even more to it? Did the Trump campaign actively coordinate with a foreign power? Did a cabal within the F.B.I. deliberately slow-walk investigations into that possibility?

just three Republican senators with consciences could do a lot to protect American values.

Congress will be much more likely to stand up to a rogue, would-be authoritarian executive if its members realize that they will face a political price if they act as his enablers.

What this means is that Mr. Trump must not be treated with personal deference simply because of the position he has managed to seize. He must not be granted the use of the White House as a bully pulpit. He must not be allowed to cloak himself in the majesty of office. Given what we know about this guy’s character, it’s all too clear that granting him unearned respect will just empower him to behave badly.

that the election was tainted isn’t a smear or a wild conspiracy theory; it’s simply the truth.

Now, anyone questioning Mr. Trump’s legitimacy will be accused of being unpatriotic — because that’s what people on the right always say about anyone who criticizes a Republican president. (Strangely, they don’t say this about attacks on Democratic presidents.) But patriotism means standing up for your country’s values, not pledging personal allegiance to Dear Leader.

No, we shouldn’t get into the habit of delegitimizing election results we don’t like. But this time really is exceptional, and needs to be treated that way.

So let’s be thankful that John Lewis had the courage to speak out. It was the patriotic, heroic thing to do

At the end of the day, having a white roof cannot hurt. It does keep buildings cooler which translates into lower energy costs

white roofs aren’t always practical, especially because many people have ordinary shingle roofs and while shingles come in very light colors, I’ve never seen any that are white. That, and as has been mentioned, keeping them clean!

white roofs may reduce cooling costs. What about 75 percent of the US where there are more heating degree days (HDD) than cooling degree days (CDD) and a dark colored roof actually provides more benefits by reducing the heating costs…

We have found that white roofs do provide a low-cost solution that can help buildings reduce energy costs, in a wide variety of climates, as well as cool the atmosphere regionally and globally. We have also found disadvantages. The reflective roofs may cause unwanted glare, for example, and may modestly increase heating costs in winter. But answers to these issues are exactly the ones we’re working hard to find.

In our opinion, all of these arguments and studies suggest that selective use of white and other reflective roofs makes sense as part of an integrated strategy

n an urban environment you also have thermal mass to take into account, I don`t have the mathematics to put here, however a simple analogy would be if you painted a piece of concrete black and put it in the sun and had another identical piece painted white, the black piece would still be radiating heat longer after the sun has gone down.

Most urban environment are made of high thermal mass products, Concrete, Bitumen Steel, these all will heat up more if they are darker colors and radiate back into the local environment after dark. Where as if they radiated heat back into the air instead of absorbing it all day, there might be a better chance of a cool down before the sun comes up the next day.

Across Kiev and beyond, personal barriers that once defined the limits of behavior are crumbling, pushing this fractured but, until a few weeks ago, proudly peaceful nation into a spiral of chaos.

“What have humanism and pacifism ever brought to any nation?” he asked, clutching a battered metal shield and a metal rod, his soot-blackened face covered by a brown balaclava. “Revolutions are violent.”

“Nationalism is what I believe in,” said the man, who gave his name only as Nikolo. “The nation is my religion.”

But while the ranks of the protesters are diverse, the young men like Nikolo are the foot soldiers in a deepening civil conflict, the steel that refuses to bend under the pressure of thousands of riot police officers, volleys of live ammunition, snipers on rooftops and the looming threat of martial law.

The sotni provide a quasi-military discipline to the opposition’s street muscle. The commanders of the hundreds meet with other leaders of bands of young men under the umbrella of the Maidan Self Defense organization, which is led by Andri Parubi, a member of the opposition party Fatherland, though his control over some of the right-wing street groups appears tenuous at times.

But if these groups, whose members are far outnumbered by nonviolent protesters and also by the police, were the only ones driving Ukraine’s opposition to Mr. Yanukovych, the president could easily have defeated them weeks ago. Behind them stands a mass of others who recoil at pugnacious nationalism and scenes of mayhem but who now stand shoulder to shoulder with outfits like Right Sector, enraged that security forces resorted to violence to crack down on what had been a mostly peaceful protest in the mold of the Orange Revolution of 2004.

“We have a genetic memory of fascism here,” said Anatoly Skripnik, a businessman in the eastern city of Dnepropetrovsk.

Many protesters played down the role that the quasi-military nationalist groups, and history, are playing in the confrontation. “Some from the west are nationalists,” said Nikolai Visinski, an artist, standing on a barricade Thursday evening. “But we are all united in wanting a change of government. You don’t hear people yelling about Stepan Bandera. People just want to live in a free country.”

His successors, even those he personally supported, have, sadly, not been his equals. South Africa today faces many challenging problems. Scandalous mismanagement of the H.I.V./AIDS epidemic by Thabo Mbeki brought widespread, unnecessary suffering.

It will be up to a new generation of South African leaders to resolve these problems. All of them will owe a historic debt to Nelson Mandela.

The victory gave the slaves nothing but a sense of the grandeur of their master’s empire. The great victory only reinforced their great slavery.

The chief Russian question is: If the fatherland is a monster, should it be loved or hated? Here everything has run together, inseparably. Long ago, a Russian poet put it this way: “A heart weary of hate cannot learn to love.”

Of course, I wish my homeland victory. But what would constitute a victory for my country? Each one of Hitler’s victories was a defeat for the German people. And the final rout of Nazi Germany was a victory for the Germans themselves, who demonstrated how a nation can rise up and live like human beings without the delirium of war in their heads.

Today, though, Victory Day has nothing to do with the people’s victory or my father’s victory. It is not a day of peace and remembrance for the victims. It is a day for rattling swords, a day of zinc coffins, a day of aggression, a day of great hypocrisy and great baseness.

In the 16th year of his rule, President Vladimir V. Putin has achieved everything a dictator could strive for. His people love him; his enemies fear him. He has created a regime that rests not on the shaky paragraphs of a constitution but on the unshakable laws of the vassal’s personal loyalty to his sovereign, from the bottom to the top of the pyramid of power.

My father was a Russian; my mother, a Ukrainian. But the Putin regime has set our peoples against each other. Sometimes, I think it’s good my parents did not live to see how Russians and Ukrainians are killing one another. Continue reading the main story Write A Comment

It is impossible to breathe in a country where the air is permeated with hatred. Much hatred has always been followed in history by much blood. What awaits my country? Transformation into a gigantic version of Ukraine’s eastern Donbass region?

Once again, the dictatorship is calling on its subjects to defend the homeland, mercilessly exploiting the propaganda of victory in the Great Patriotic War. Russia’s rulers have stolen my people’s oil, stolen their elections, stolen their country. And stolen their victory.

The Greenland government hopes the mine will boost the economy, which is largely dependent on fishing and subsidies from Denmark.

"This is indeed a historic moment for Greenland," said Industry and Minerals Minister Jens-Erik Kirkegaard.

"the largest commercial project to date in Greenland" would boost employment and state revenues - in line with a pledge made by the governing Social Democrats to draw foreign companies to help tap Greenland's resources.

Environmentalists say they want reassurances that the exploitation of the deposits will not come at the cost of extensive environmental damage.

She said the Greenland government should insist that the mine be powered by hydroelectric power rather than diesel, and that there should be safeguards to deal with problems such as the dramatic increase in traffic.

Based on the current trajectory, war between the United States and China in the decades ahead is not just possible, but much more likely than recognized at the moment. Indeed, judging by the historical record, war is more likely than not.

A risk associated with Thucydides’s Trap is that business as usual—not just an unexpected, extraordinary event—can trigger large-scale conflict. When a rising power is threatening to displace a ruling power, standard crises that would otherwise be contained, like the assassination of an archduke in 1914, can initiate a cascade of reactions that, in turn, produce outcomes none of the parties would otherwise have chosen.

The preeminent geostrategic challenge of this era is not violent Islamic extremists or a resurgent Russia. It is the impact that China’s ascendance will have on the U.S.-led international order, which has provided unprecedented great-power peace and prosperity for the past 70 years. As Singapore’s late leader, Lee Kuan Yew, observed, “the size of China’s displacement of the world balance is such that the world must find a new balance. It is not possible to pretend that this is just another big player. This is the biggest player in the history of the world.”

More than 2,400 years ago, the Athenian historian Thucydides offered a powerful insight: “It was the rise of Athens, and the fear that this inspired in Sparta, that made war inevitable.

Note that Thucydides identified two key drivers of this dynamic: the rising power’s growing entitlement, sense of its importance, and demand for greater say and sway, on the one hand, and the fear, insecurity, and determination to defend the status quo this engenders in the established power, on the other.

However unimaginable conflict seems, however catastrophic the potential consequences for all actors, however deep the cultural empathy among leaders, even blood relatives, and however economically interdependent states may be—none of these factors is sufficient to prevent war, in 1914 or today.

Four of the 16 cases in our review did not end in bloodshed. Those successes, as well as the failures, offer pertinent lessons for today’s world leaders. Escaping the Trap requires tremendous effort

Lee Kuan Yew, the world’s premier China watcher and a mentor to Chinese leaders since Deng Xiaoping. Before his death in March, the founder of Singapore put the odds of China continuing to grow at several times U.S. rates for the next decade and beyond as “four chances in five.

Could China become #1? In what year could China overtake the United States to become, say, the largest economy in the world, or primary engine of global growth, or biggest market for luxury goods?

Could China Become #1? Manufacturer: Exporter: Trading nation: Saver: Holder of U.S. debt: Foreign-direct-investment destination: Energy consumer: Oil importer: Carbon emitter: Steel producer: Auto market: Smartphone market: E-commerce market: Luxury-goods market:   Internet user: Fastest supercomputer: Holder of foreign reserves: Source of initial public offerings: Primary engine of global growth: Economy: Most are stunned to learn that on each of these 20 indicators, China has already surpassed the U.S.

In 1980, China had 10 percent of America’s GDP as measured by purchasing power parity; 7 percent of its GDP at current U.S.-dollar exchange rates; and 6 percent of its exports. The foreign currency held by China, meanwhile, was just one-sixth the size of America’s reserves. The answers for the second column: By 2014, those figures were 101 percent of GDP; 60 percent at U.S.-dollar exchange rates; and 106 percent of exports. China’s reserves today are 28 times larger than America’s.

On whether China’s leaders are serious about displacing the United States as the top power in Asia in the foreseeable future, Lee answered directly: “Of course. Why not … how could they not aspire to be number one in Asia and in time the world?” And about accepting its place in an international order designed and led by America, he said absolutely not: “China wants to be China and accepted as such—not as an honorary member of the West.”

As the United States emerged as the dominant power in the Western hemisphere in the 1890s, how did it behave? Future President Theodore Roosevelt personified a nation supremely confident that the 100 years ahead would be an American century. Over a decade that began in 1895 with the U.S. secretary of state declaring the United States “sovereign on this continent,” America liberated Cuba; threatened Britain and Germany with war to force them to accept American positions on disputes in Venezuela and Canada; backed an insurrection that split Colombia to create a new state of Panama (which immediately gave the U.S. concessions to build the Panama Canal); and attempted to overthrow the government of Mexico, which was supported by the United Kingdom and financed by London bankers. In the half century that followed, U.S. military forces intervened in “our hemisphere” on more than 30 separate occasions to settle economic or territorial disputes in terms favorable to Americans, or oust leaders they judged unacceptable

When Deng Xiaoping initiated China’s fast march to the market in 1978, he announced a policy known as “hide and bide.” What China needed most abroad was stability and access to markets. The Chinese would thus “bide our time and hide our capabilities,” which Chinese military officers sometimes paraphrased as getting strong before getting even.

With the arrival of China’s new paramount leader, Xi Jinping, the era of “hide and bide” is over

Many observers outside China have missed the great divergence between China’s economic performance and that of its competitors over the seven years since the financial crisis of 2008 and Great Recession. That shock caused virtually all other major economies to falter and decline. China never missed a year of growth, sustaining an average growth rate exceeding 8 percent. Indeed, since the financial crisis, nearly 40 percent of all growth in the global economy has occurred in just one country: China

What Xi Jinping calls the “China Dream” expresses the deepest aspirations of hundreds of millions of Chinese, who wish to be not only rich but also powerful. At the core of China’s civilizational creed is the belief—or conceit—that China is the center of the universe. In the oft-repeated narrative, a century of Chinese weakness led to exploitation and national humiliation by Western colonialists and Japan. In Beijing’s view, China is now being restored to its rightful place, where its power commands recognition of and respect for China’s core interests.

Last November, in a seminal meeting of the entire Chinese political and foreign-policy establishment, including the leadership of the People’s Liberation Army, Xi provided a comprehensive overview of his vision of China’s role in the world. The display of self-confidence bordered on hubris. Xi began by offering an essentially Hegelian conception of the major historical trends toward multipolarity (i.e. not U.S. unipolarity) and the transformation of the international system (i.e. not the current U.S.-led system). In his words, a rejuvenated Chinese nation will build a “new type of international relations” through a “protracted” struggle over the nature of the international order. In the end, he assured his audience that “the growing trend toward a multipolar world will not change.”

Given objective trends, realists see an irresistible force approaching an immovable object. They ask which is less likely: China demanding a lesser role in the East and South China Seas than the United States did in the Caribbean or Atlantic in the early 20th century, or the U.S. sharing with China the predominance in the Western Pacific that America has enjoyed since World War II?

At this point, the established script for discussion of policy challenges calls for a pivot to a new strategy (or at least slogan), with a short to-do list that promises peaceful and prosperous relations with China. Shoehorning this challenge into that template would demonstrate only one thing: a failure to understand the central point I’m trying to make

What strategists need most at the moment is not a new strategy, but a long pause for reflection. If the tectonic shift caused by China’s rise poses a challenge of genuinely Thucydidean proportions, declarations about “rebalancing,” or revitalizing “engage and hedge,” or presidential hopefuls’ calls for more “muscular” or “robust” variants of the same, amount to little more than aspirin treating cancer. Future historians will compare such assertions to the reveries of British, German, and Russian leaders as they sleepwalked into 1914

The rise of a 5,000-year-old civilization with 1.3 billion people is not a problem to be fixed. It is a condition—a chronic condition that will have to be managed over a generation

Success will require not just a new slogan, more frequent summits of presidents, and additional meetings of departmental working groups. Managing this relationship without war will demand sustained attention, week by week, at the highest level in both countries. It will entail a depth of mutual understanding not seen since the Henry Kissinger-Zhou Enlai conversations in the 1970s. Most significantly, it will mean more radical changes in attitudes and actions, by leaders and publics alike, than anyone has yet imagined.

China’s economy depends heavily on cheap coal-fired electricity, and the country has a history of balking at outside reviews of its industries. China has also been plagued by major corruption cases, particularly among coal companies.

Domestic and external pressures have driven the Chinese government to take firmer action to curb emissions from fossil fuels, especially coal. Growing public anger about the noxious air that often envelops Beijing and many other Chinese cities has prompted the government to introduce restrictions on coal and other sources of smog, with the side benefit of reducing carbon dioxide pollution.

The climate deal will be a substantial, if rare, bright spot in a wide-ranging summit meeting that is expected to be dominated by potential sources of friction between Mr. Obama and Mr. Xi.

The president plans to raise a number of contentious topics on Friday, White House aides said, including cyberattacks on American companies and government agencies, China’s increasingly aggressive reclamation of islands and atolls in disputed areas of the South China Sea, and Mr. Xi’s clampdown on dissidents and lawyers in China.

Under a cap-and-trade system, a concept created by American economists, governments place a cap on the amount of carbon pollution that may be emitted annually. Companies can then buy and sell permits to pollute. Western economists have long backed the idea as a market-driven way to push industry to cleaner forms of energy, by making polluting energy more expensive.

why is diversity good? Diversity isn't good in and of itself; it's good because it allows us to expand our horizons, to break out of the boxes – by they cultural, ethnic, or religious – in which we find ourselves. To think about other values, other beliefs, other lifestyles, to make judgements upon those values and beliefs and lifestyles. To enter, in other words, into a dialogue, a debate, through which a more universal language of citizenship can arise. It is precisely such dialogue and debate that multiculturalism as a political process undermines and erodes in the name of "respect" and "tolerance".

I think the very notion of multiculturalism is an irrational one. It assumes from the start that societies are composed of cultures that somehow relate to each other externally, as it were. Here is one culture, here's another, and there's another, and these cultures then interact with each other. In fact cultures aren't like that: cultures are living, organic entities that constantly change. There is no such thing as a multicultural society. There are societies with a variety of cultural forms, beliefs, lifestyles, values – in fact, virtually every society embodies such diversity – but to say that is to say something very different thing to the claim that a society is "multicultural".

Societies have always been conflictual, riven by class differences, generational differences, gender differences, ideological differences. But today we tend to see social clashes in a very narrow way, in terms of religion, faith and culture, because we have come to see identity in very narrow ways. The debate about multiculturalism is a debate in which certain differences – culture, ethnicity and faith – have come to be regarded as important and others – such as class, say, or generation – as less relevant.

There are two ways over the past half-century in which we've stopped treating people as citizens. One is through racism. The racist says "you're not a citizen, you don't have full rights in this society because you have a different skin colour, you are foreign", etc. The second is multiculturalism. The multiculturalist says: "we treat you not as an individual citizen, but as a Muslim or a Hindu or a Sikh or a black". The irony is that multiculturalism developed as an attempt to combat the problems created by racism. But it has recreated many of the problems by treating people not as citizens but as members of groups, and by formulating public policy in relation to those groups and not in relation to the needs of individual citizens.

we have to say that the multicultural policies were flawed from the very beginning: it wasn't as if this was a good set of policies that somehow eroded over time. The fact is that it was a lot easier to combat racism by saying to people "go on, follow your own values, cultures, lifestyles, beliefs, we will fund your festival, your dance troupe, your cultural centre"... we used to call it the "saree, samosa and steel band brigade".

What has happened is that the very notion of equality has transformed over the last twenty years. Equality used to mean that everybody was treated the same despite their differences. Now it's come to me that everybody is treated differently because of those differences.

There are two problems with granting people rights by virtue of their belonging to a group, as opposed to their being citizens with specific social, economic and other needs. First, the group becomes a focus not only for providing rights, but also for prejudice: you deal not with the problems of individual Roma, but the imputed problems of Roma as a whole. Second, you deny the same rights to other groups, to others who don't happen to be in that group, such as Muslims.

As for the relationship between multiculturalism and constraints on free speech, an argument has developed that runs something like this: we live in a society where there are lots of different peoples and cultures, each with deeply set, often irreconcilable, views and beliefs. In such a society we need to restrict what people say or do in order to minimize friction between cultures and to guarantee respect for people embedded in different cultures.

it is precisely because we live in a plural society that we need the most robust defence of free speech possible. It seems to me that in a plural society, the giving of offence is both inevitable and necessary. It is inevitable because we do have societies with deep-seated, conflicting views. But it's far better to have those conflicts out in the open than to suppress them in the name of respect and tolerance. But most importantly, the giving of offence is necessary because no kind of social change or social progress is possible without offending some group of other. When people say, "you are offending me", what they are really saying is, "you can't say that because I don't want my beliefs to be questioned or ridiculed or abused." That seems to me deeply problematic.

The real issue is not actually the threat of violence from Islamists. It is something much more internal to western societies, the sense that it is morally wrong to give offence to other groups and cultures. People are frightened of doing things because they fear the repercussions, but they are also frightened of doing things because they think it is morally wrong to offend other people and other cultures. And I think that is a much greater problem. We should say it is morally right to offend people. That is what a plural society is. If we want to live in a plural society, the price of a plural society – though I don't see it as a price, I think it is the value of the plural society – is that we confront each other. That is what is good about plural society.

We also need to make a distinction between colour blindness and racism blindness. The two have become confused, so that in France, for instance, arguments against multiculturalism have become an argument in defence of racism. Discriminatory policies, and not just against the Roma, but also against Muslims and others, have been defended on the basis that they are necessary for assimilation. The law outlawing the burqa, for instance. In one sense assimilation means treating individuals as citizens and not as members of a particular group. That seems to me to be a very good thing. But that is not what assimilation has come to mean in practice somewhere like France, where policies of assimilation have re

sulted in the authorities treating different groups of people differently by pointing up their differences, insisting that certain groups – Muslims or the Roma, for example – cannot belong to our culture, to our society, because their culture, their values, their ways of life are so different and inimical to ours. That is the way assimilation policies have developd and I think that is very dangerous.

Part of the problem of multiculturalism is that the distinction between the public and the private realms have become eroded. We need to defend the right of people to pursue their values, their lifestyles, their beliefs in private. By "private", I don't mean in the privacy of their homes, but in those areas of life distinct from the state and state institutions. But we also need to ensure that, in the public realm, the state does not treat people differently because of their particular values, beliefs or lifestyles. The ideal plural society is one where people have perfect freedom to pursue their beliefs, values and lifestyles in private but in public are treated as citizens, whatever those lifestyles, beliefs and values are. Multiculturalism has come to mean the very opposite: people are treated differently in the public realm because of their values, beliefs and lifestyles, but at the same time restrictions are placed upon the private realm, on what one can say or do, because of fear of giving offence.

Fighting racism doesn't mean I have to limit freedom of expression. I hate racist jokes, but I would protect the right of people to tell them. They are really ugly and stupid, but I wouldn't dream of regulating it by law. Actually, I do not believe in collective rights. I think everyone should be treated equally, but people also need to be free to live how they prefer. Fighting violent racism is something that should be done by law enforcement authorities. But it is also the responsibility of the cultural elites: to make racism something one should be ashamed of. It's a matter of education, I think. Not of laws limiting free speech.

The point about free speech is this: who is it that benefits from censorship? Is it those in power, or is it those without power? It seems to me that the only people to benefit from censorship are those with the power to enforce that censorship and the need to do so. Those who have no power are much better served by as little censorship as possible. Free speech is always the weapon in the hands of those who want to challenge power and censorship is always a weapon in those who want to preserve their power. That's why I think anyone who wants to challenge racism should support of the greatest extension of free speech possible.

The pressure on prices has been significant. Continue reading the main story Related Coverage China’s Slowdown Tarnishes Economic Boom in Copper-Rich ZambiaDEC. 2, 2015 A Global Chill in Commodity Demand Hits America’s HeartlandOCT. 23, 2015 Glencore Isn’t Out of the Woods YetOCT. 1, 2015 Prices for iron ore, the crucial steelmaking ingredient, have fallen by about 40 percent this year. The Brent crude oil benchmark is now hovering around $40 a barrel, down from more than a $110 since the summer of 2014.

Companies are caught in the downdraft.A number of commodity-related businesses have either declared bankruptcy or fallen behind in their debt payments

Even more common are the cutbacks. Nearly 1,200 oil rigs, or two-thirds of the American total, have been decommissioned since late last year. More than 250,000 workers in the oil and gas industry worldwide have been laid off, with more than a third coming in the United States.

The international mining company Anglo American is pulling back broadly, with a goal to reduce the company’s size by 60 percent. Along with the layoffs announced on Tuesday, the company is suspending its dividend, halving its business units, as well as unloading mines and smelters.

China looms large in the commodities equation.Between 2000 and last year, companies invested hundreds of billions of dollars to expand their production capacity to satisfy China in a period of rapid economic expansion. Much of the corporate growth was fueled by debt.

But the only thing this reflexive complaining does is divide the country further and make a coherent response to Islamic State more difficult.

There, I met Dale “Red” Robinson, a Pearl Harbor survivor and a staff sergeant in the infantry who was later part of the Normandy landing. He recalled the national unity of that war

“Nothing like this, these days. It’s sad, kind of sad, my friend.”

Robinson said he feels “sorry for all of the soldiers” serving today, let down by their political leaders.

That’s what Monday afternoon’s ceremony was about. A sailor rang a bell at 1:57 p.m. Eastern time, the moment 74 years earlier when Japanese planes struck

ater, while the band played “America the Beautiful,” the veterans, some wheeled, some walking with support, made a slow procession around the memorial’s pool to place wreaths

We live all of us today with the prosperity and the security built on the shoulders of these heroes,”

That’s our challenge — and we’re failing.

“The difference is the uncertainty of today, and it’s a big difference,”

“I thought they were more loyal, more concerned about the nation than their position,” he said.

Mays complained about the sharp partisan divisions in Congress. “How can we bring unity when you have that?”

Now, our representatives can’t even manage to come up with a resolution authorizing the use of military force against the Islamic State — and they’ve been at it for a year.

“just a half-hearted attempt to defend and distract from a failing policy.” Ryan said we are “one step behind our enemy.”

and the constant sniping at each other does nothing to defeat the Islamic State. As those old soldiers on the Mall taught us, victory comes from unity.