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To the legions of passers-by who owners say want to touch their Cybertrucks, sit on their Cybertrucks, and take selfies with their Cybertrucks, the vehicle isn’t a political or cultural flashpoint. Instead it’s something rarer: A genuinely novel piece of mass design

Women, however, own Cybertrucks, too. In an email, Dr. Helen Raynham, a dermatologist in Massachusetts, said that she had reserved her Cybertruck more than four years ago and had put a custom license plate on her new vehicle: “GRLBOS.” She added that she surrounded the plate with diamonds.

In some circles, the vehicle’s unique appearance has made it into a coveted status symbol and an object of considerable fascination. Celebrities like Kim Kardashian and Serena Williams have both been spotted in Cybertrucks. On YouTube, there is a robust, seemingly nonpartisan culture around modifying Cybertrucks and testing out their unusual features.

What is A.I. even for?

“A.I. slop”: often uncanny, frequently misleading material, now flooding web browsers and social-media platforms like spam in old inboxes. Years deep into national hysteria over the threat of internet misinformation pushed on us by bad actors, we’ve sleepwalked into a new internet in which meaningless, nonfactual slop is casually mass-produced and force-fed to us by A.I.

It has already helped drive down the cost and drive up the performance of next-gen batteries and solar photovoltaic cells, whose performance can also be improved, even after the panels have been manufactured and installed on your roof, by as much as 25 percent

while the internet was never perfectly trustworthy, one epoch-defining breakthrough of Google was that it got us pretty close. Now the company’s chief executive acknowledges that hallucinations are “inherent” to the technology it has celebrated as a kind of successor for ranked-order search results, which are now often found far below not just the A.I. summary but a whole stack of “sponsored” results as well.

Where not long ago we used to find the very best results for Google searches, we can now find instead potentially plagiarized and often inaccurate paragraph summaries of answers to our queries

Machine learning may help make our electricity grid as much as 40 percent more efficient at delivering power as it is today, when many of its routing decisions are made by individual humans on the basis of experience and intuition

This month, KoBold Metals announced the largest discovery of new copper deposits in a decade — a green-energy gold mine, so to speak, delivered with the help of its own proprietary A.I., which integrated information about subatomic particles detected underground with century-old mining reports and radar imagery to make predictions about where minerals critical for the green transition might be found.

.I. is designing new proteins, rapidly accelerating drug discovery and speeding up clinical trials testing new medicines and therapies.

perhaps that a more optimistic perspective can be drawn by analogy to what economists call the “environmental Kuznets curve,” which suggests that, as nations develop, they tend to first pollute a lot more and then, over time, as they grow richer, they ultimately pollute less.

Even in describing regular old pollution, this framework has its shortcomings, especially because it treats as automatic eventual progress that has always required tooth-and-nail fights against some very stubborn bad actors

A.I. is generating an awful lot of genuine pollution, too — both Google and Microsoft, which each pledged in 2019 to reach zero emissions by 2030, have instead expanded their carbon footprints by nearly 50 percent in the interim.

As a young State Department policy planner in the 2000s, she was a lonely voice in Washington raising the alarm about the rise of China. She pushed for tariffs and against trade agreements before it was cool, and was an author of a book called “War by Other Means” about how blind faith in free markets put the United States at a geopolitical disadvantage. For years, she felt like an oddball in Washington, where both parties were still in thrall to neoliberalism.

The Hewlett Foundation hired her as the head of an initiative that has given away $140 million so far to people who are devising a new economic philosophy. Then she served a stint in the White House. Today, she’s an intellectual leader of a growing, bipartisan consensus

She fell in love with economics and studied it at Wake Forest. After she joined a student delegation to a NATO summit in Prague in 2002, a faculty adviser on that trip offered her a job in Washington working at the National Intelligence Council. In those early years, she believed what everyone else in Washington believed about the economy — that governments ought not meddle with it.

if Mr. Trump correctly identified a problem — “China is eating our lunch” — he did not solve it, beyond putting tariffs on Chinese products. His tax cut for the rich hurt rather than helped matters.

It’s the Biden administration that came in with a plan to build an economy that was good for workers, not just shareholders, using some strategies Ms. Harris had been talking about for years.

The thinking behind it goes like this: Unquestioning belief in the free market created a globalism that funneled money to the 1 percent, which has used its wealth to amass political power at the expense of everyone else. It produced free trade agreements that sent too many U.S. factories to China and rescue plans after the 2008 financial crisis that bailed out Wall Street instead of Main Street.

It was her job to track China’s use of subsidies, industrial espionage and currency manipulation to fuel its rise as a manufacturing powerhouse. Ms. Harris argued that tariffs on China were a necessary defense. Nobody agreed. “I was kind of just banging my head against this wall,” she told me. “The wall was a foreign policy establishment that saw markets as sacrosanct.”

Barack Obama campaigned on a pledge to renegotiate NAFTA, but he struck up a new trade deal instead — the Trans-Pacific Partnership. Ms. Harris argued against it. “We didn’t have the foggiest idea” of what it would do to our economy, she told me. Nobody listened.

it sent Democrats back to the intellectual drawing board. Larry Kramer, then the president of the Hewlett Foundation, recruited her in 2018 to promote alternatives to ideas that had guided U.S. policy for decades. He hoped she could do for free-market skepticism what Milton Friedman and his allies had done for free-market fundamentalism, which became policy under the Reagan administration and eventually was embraced by both parties as truth.

She has since rejoined the Hewlett Foundation, where she funds people who are proposing new solutions to economic problems. One grantee, the conservative think tank American Compass, promotes the idea of a domestic development bank to fund infrastructure — an idea with bipartisan appeal.

But the work that Ms. Harris and others in the Biden administration have done is unfinished, and poorly understood. The terms “Bidenomics” and “Build Back Better” don’t seem to resonate

Ms. Harris acknowledges that these ideas haven’t yet taken hold in the broader electorate, and that high interest rates overshadow the progress that’s been made. It’s too early for voters to feel it, she told me: “The investments Biden has pushed through aren’t going to be felt in a month, a year, two years.”

she celebrates the fact that leaders across the political spectrum are embracing the idea that Americans need to “get back to building things in this country.” This election has no candidates blindly promoting the free market. The last one didn’t either. In the battle of ideas, she has already won.

A closer look, however, would have revealed that individual journalists at BNN published lengthy stories as often as multiple times a minute, writing in generic prose familiar to anyone who has tinkered with the A.I. chatbot ChatGPT.

How easily the site and its mistakes entered the ecosystem for legitimate news highlights a growing concern: A.I.-generated content is upending, and often poisoning, the online information supply.

The websites, which seem to operate with little to no human supervision, often have generic names — such as iBusiness Day and Ireland Top News — that are modeled after actual news outlets. They crank out material in more than a dozen languages, much of which is not clearly disclosed as being artificially generated, but could easily be mistaken as being created by human writers.

Now, experts say, A.I. could turbocharge the threat, easily ripping off the work of journalists and enabling error-ridden counterfeits to circulate even more widely — as has already happened with travel guidebooks, celebrity biographies and obituaries.

The result is a machine-powered ouroboros that could squeeze out sustainable, trustworthy journalism. Even though A.I.-generated stories are often poorly constructed, they can still outrank their source material on search engines and social platforms, which often use A.I. to help position content. The artificially elevated stories can then divert advertising spending, which is increasingly assigned by automated auctions without human oversight.

NewsGuard, a company that monitors online misinformation, identified more than 800 websites that use A.I. to produce unreliable news content.

Low-paid freelancers and algorithms have churned out much of the faux-news content, prizing speed and volume over accuracy.

Former employees said they thought they were joining a legitimate news operation; one had mistaken it for BNN Bloomberg, a Canadian business news channel. BNN’s website insisted that “accuracy is nonnegotiable” and that “every piece of information underwent rigorous checks, ensuring our news remains an undeniable source of truth.”

this was not a traditional journalism outlet. While the journalists could occasionally report and write original articles, they were asked to primarily use a generative A.I. tool to compose stories, said Ms. Chakraborty and Hemin Bakir, a journalist based in Iraq who worked for BNN for almost a year. They said they had uploaded articles from other news outlets to the generative A.I. tool to create paraphrased versions for BNN to publish.

Mr. Chahal’s evangelism carried weight with his employees because of his wealth and seemingly impressive track record, they said. Born in India and raised in Northern California, Mr. Chahal made millions in the online advertising business in the early 2000s and wrote a how-to book about his rags-to-riches story that landed him an interview with Oprah Winfrey.

Mr. Chahal told Mr. Bakir to focus on checking stories that had a significant number of readers, such as those republished by MSN.com.Employees did not want their bylines on stories generated purely by A.I., but Mr. Chahal insisted on this. Soon, the tool randomly assigned their names to stories.

This crossed a line for some BNN employees, according to screenshots of WhatsApp conversations reviewed by The Times, in which they told Mr. Chahal that they were receiving complaints about stories they didn’t realize had been published under their names.

According to three journalists who worked at BNN and screenshots of WhatsApp conversations reviewed by The Times, Mr. Chahal regularly directed profanities at employees and called them idiots and morons. When employees said purely A.I.-generated news, such as the Fanning story, should be published under the generic “BNN Newsroom” byline, Mr. Chahal was dismissive.“When I do this, I won’t have a need for any of you,” he wrote on WhatsApp.Mr. Bakir replied to Mr. Chahal that assigning journalists’ bylines to A.I.-generated stories was putting their integrity and careers in “jeopardy.”

This was a strategy that Mr. Chahal favored, according to former BNN employees. He used his news service to exercise grudges, publishing slanted stories about a politician from San Francisco he disliked, Wikipedia after it published a negative entry about BNN Breaking and Elon Musk after accounts belonging to Mr. Chahal, his wife and his companies were suspended o

The increasing popularity of programmatic advertising — which uses algorithms to automatically place ads across the internet — allows A.I.-powered news sites to generate revenue by mass-producing low-quality clickbait content

Experts are nervous about how A.I.-fueled news could overwhelm accurate reporting with a deluge of junk content distorted by machine-powered repetition. A particular worry is that A.I. aggregators could chip away even further at the viability of local journalism, siphoning away its revenue and damaging its credibility by contaminating the information ecosystem.