In early 2011, Ken Jennings looked like humanity’s last hope. Watson, an artificial intelligence created by the tech giant IBM, had picked off lesser Jeopardy players before the show’s all-time champ entered a three-day exhibition match. At the end of the first game, Watson—a machine the size of 10 refrigerators—had Jennings on the ropes, leading $35,734 to $4,800. On day three, Watson finished the job. “I for one welcome our new computer overlords,” Jennings wrote on his video screen during Final Jeopardy.

Watson was better than any previous AI at addressing a problem that had long stumped researchers: How do you get a computer to precisely understand a clue posed in idiomatic English and then spit out the correct answer (or, as in Jeopardy, the right question)? “Not a hit list of documents where the answer may be,” which is what search engines returned, “but the very specific answer,” David Ferrucci, Watson’s lead developer, told me. His team fed Watson more than 200 million pages of documents—from dictionaries, encyclopedias, novels, plays, the Bible—creating something that sure seemed like a synthetic brain. And America lost its mind over it: “Could Watson be coming next for our jobs in radiology or the law?” NPR asked in a story called “The Dark Side of Watson.” Four months after its Jeopardy win, the computer was named Person of the Year at the Webby Awards. (Watson’s acceptance speech: “Person of the Year: ironic.”)

But now that people are once again facing questions about seemingly omnipotent AI, Watson is conspicuously absent. When I asked the longtime tech analyst Benedict Evans about Watson, he quoted Obi-Wan Kenobi: “That’s a name I’ve not heard in a long time.” ChatGPT and other new generative-AI tools can furnish pastiche poetry and popes wearing Balenciaga, capabilities that far exceed what Watson could do a decade ago, though ones still based in the ideas of natural-language processing that helped dethrone Jennings. Watson should be bragging in its stilted voice, not fading into irrelevance. But its trajectory is happening all over again; part of what doomed the technology is now poised to chip away at the potential of popular AI products today.

The first thing to know about Watson is that it isn’t dead. The machine’s models and algorithms have been nipped and tucked into a body of B2B software. Today IBM sells Watson by subscription, folding the code into applications like Watson Assistant, Watson Orchestrate, and Watson Discovery, which help automate back-end processes within customer service, human resources, and document entry and analysis. Companies like Honda, Siemens, and CVS Health hit up “Big Blue” for AI assistance on a number of automation projects, and an IBM spokesperson told me that the company’s Watson tools are used by more than 100 million people. If you ask IBM to build you an app that uses machine learning to optimize something in your business, “they’ll be very happy to build that, and it will probably be perfectly good,” Evans said.

From the very beginning, IBM wanted to turn Watson into a business tool. After all, this is IBM—the International Business Machines Corporation—a company that long ago carved out a niche catering to big firms that need IT help. But what Watson has become is much more modest than IBM’s initial sales pitch, which included unleashing the machine’s fact-finding prowess on topics as varied as stock tips and personalized cancer treatments. And to remind everyone just how revolutionary Watson was, IBM put out TV commercials in which Watson cheerfully bantered with celebrities like Ridley Scott and Serena Williams. The company soon struck AI-centric deals with hospitals such as Memorial Sloan Kettering and the MD Anderson Cancer Center; they slowly foundered. Watson the machine could play Jeopardy at a very high level; Watson the digital assistant, essentially a swole Clippy fed on enterprise data and techno-optimism, could barely read doctors’ handwriting, let alone disrupt oncology.

The tech just didn’t measure up. “There was no intelligence there,” Evans said. Watson’s machine-learning models were very advanced for 2011, but not compared with bots like ChatGPT, which have ingested much of what has been published online. Watson was trained on far less information and excelled only at answering fact-based questions like the kind you find on Jeopardy. That talent contained obvious commercial potential—at least in certain areas, like search. “I think that what Watson was good at at the time kind of morphed into what you see Google doing,” Ferrucci said: surfacing precise answers to colloquial questions.

But the suits in charge went after the bigger and more technically challenging game of feeding the machine entirely different types of material. They viewed Watson as a generational meal ticket. “There was a lot of hyperbole around it, and a lot of lack of appreciation for what it really can do and what it can’t do, and ultimately what is needed to effectively solve business problems,” Ferrucci said. He left IBM in 2012 and later founded an AI start-up called Elemental Cognition.

When asked about what went wrong, an IBM spokesperson pointed me to a recent statement from CEO Arving Krishna: “I think the mistake we made in 2011 is that we concluded something correctly, but drew the wrong conclusions from the conclusions.” Watson was “a concept car,” Kareem Yusuf, the head of product management for IBM’s software portfolio, told me—a proof of technology meant to prod further innovation.

And yet to others, IBM may have seemed more concerned with building a showroom for its flashy convertible than figuring out how to design next year’s model. Part of IBM’s problem was structural. Richer, nimbler companies like Google, Facebook, and even Uber were driving the most relevant AI research, developing their own algorithms and threading them through everyday software. “If you were a cutting-edge machine-learning academic,” Evans said, “and Google comes to you and Meta comes to you and IBM comes to you, why would you go to IBM? It’s a company from the ’70s.” By the mid-2010s, he told me, Google and Facebook were leading the pack on machine-learning research and development, making big bets on AI start-ups such as DeepMind. Meanwhile, IBM was producing a 90-second Academy Awards spot starring Watson, Carrie Fisher, and the voice of Steve Buscemi.

In a sense, IBM’s vision for a suite of business tools built around machine learning and natural-language processing has come true—just not thanks to IBM. Today, AI powers your search results, assembles your news feed, and alerts your bank to possible fraud activity. It hums in the background of “everything you deal with every day,” Rosanne Liu, a senior research scientist at Google and the co-founder of ML Collective, a research nonprofit, told me. This AI moment is creating even more of a corporate clamor for automation as every company wants a bot of its own.

Although Watson has been reduced to a historical footnote, IBM is still getting in on the action. The most advanced AI work is not happening in IBM’s Westchester, New York, headquarters, but much of it is open-source and has a short shelf life. Tailoring Silicon Valley’s hand-me-downs can be a profitable business. Yusuf invoked platoons of knowledge workers armed with the tools of the 20th century. “You’ve got people with PDFs, highlighters,” he said. IBM can offer them programs that help them do better—that bump their productivity a few points, or decrease their error rates, or spot problems faster, such as faults on a manufacturing line or cracks in a bridge.

Whatever IBM makes next won’t fulfill the promise implied by Watson’s early run, but that promise was misunderstood—in many ways by IBM most of all. Watson was a demo model capable of drumming up enormous popular interest, but its potential sputtered as soon as the C-suite attempted to turn on the money spigot. The same thing seems to be true of the new crop of AI tools. High schoolers can generate A Separate Peace essays in the voice of Mitch Hedberg, sure, but that’s not where the money is. Instead, ChatGPT is quickly being sanded down into a million product-market fits. The banal consumer and enterprise software that results—features to help you find photos of your dog or sell you a slightly better kibble—could become as invisible to us as all the other data we passively consume. In March, Salesforce introduced Einstein GPT, a product that uses OpenAI’s technology to draft sales emails, part of a trend that Evans recently described as the “boring automation of boring processes in the boring back-offices of boring companies.” Watson’s legacy—a big name attached to a humble purpose—is playing out yet again.

The future of AI may still prove to be truly world-changing in the way that Watson once suggested. But the only business that IBM has managed to disrupt is its own. On Monday, International Workers’ Day, it announced that it would pause hiring for roughly 7,800 jobs that it believes AI could perform in the coming years. Vacating thousands of roles in the name of cost-saving measures has rarely sounded so upbeat, but after years of positive spin, why back down now? Yusuf swore that IBM’s future is just around the corner, and this time would be different. “Watch this space,” he said.

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With 18 months to go before the 2024 election, a Trump-Biden rematch seems imminent, a sharp reversal of expectation from as recently as this March. Trump’s resurgence is a reminder of what has become a nonnegotiable trait for presidential contenders—and the electorate’s Achilles’ heel.

First, here are four new stories from The Atlantic:

A country governed by fear The only way out of the child-gender culture war Ted Lasso has lost its way. The outer limits of liberalism A Good Show

Donald Trump becoming the 2024 Republican front-runner wasn’t always a foregone conclusion. When various Trump-endorsed candidates lost their races in November’s midterms, it appeared that the stench of MAGA had putrefied into surefire voter repellant. But by spring, something had changed. Florida Governor Ron DeSantis, briefly the heir presumptive of Trump’s GOP, came under new scrutiny. Once again, this would be Trump’s nomination to lose.

Set aside that he has achieved the dubious distinction of becoming the first former U.S. president to be indicted on criminal charges (a hiccup that, some polling has shown, may have actually boosted his electoral prospects among Republicans). Forget the fact that this particular milestone landed amid a tangle of legal challenges so numerous that Trump himself appears barely able to keep track of them. Forget his tacit endorsement of incarcerated January 6 seditionists, or that he is currently standing trial in a federal civil court over a rape accusation by the writer E. Jean Carroll. Trump has something going for him that DeSantis and other would-be leaders of his party simply don’t: The man is very funny.

Worse, he knows it. Whether or not the 45th president has ever believed himself to be a “very stable genius,” for instance, that now notorious 2018 soundbite is just one of a bottomless supply of examples suggesting the reflexive hijinks of a practiced class clown (consider, also, “covfefe”).

Some critics of the former president might be disinclined to agree with this point, which is their prerogative. But my observation is hardly original. In 2018, Damian Reilly argued in The Spectator that even the then-president’s “most ardent detractors” would have to admit that Trump is not just funny; he’s funny on purpose. And, Reilly added, it was specifically in the humor department that Trump had incontrovertibly bested his 2016 opponent, Hillary Clinton.

The question Is Trump funny? was, by the time of Reilly’s writing, an established soul-searching prompt for pundits across the ideological spectrum. That there would be any hand-wringing or hesitation, on the part of Trump’s many critics, to acknowledge the possibility reveals much about the outsize role of humor in politics. Which is to say: It plays a perhaps larger role than many of us would care to acknowledge.

Wariness at this state of affairs is not unwarranted. After all, the ability to elicit chuckles from a crowd has no bearing on a person’s fitness to lead. Being funny has, nevertheless, become a necessary virtue for those seeking the highest elected office of the land. It cannot be the only virtue a candidate possesses, but it’s a nonnegotiable one.

The NPR correspondent Ari Shapiro noted as much ahead of the 2012 White House Correspondents’ Dinner, when President Barack Obama was vying for his own reelection against Republican challenger Mitt Romney. Shapiro also narrowed in on why humor is so nonnegotiable. “Humor is an essential tool in any politician’s kit—all the more so in an age of instant, constant media,” he explained. “It can disarm an opponent, woo a skeptical voter or pierce an argument.”

Shapiro pointed out that although both candidates had been “the butt of a lot more jokes” than they’d made, it was Romney who faced the steeper uphill trek of “trying to reverse his reputation as a humorless aristocrat.” (Romney’s insistence, in a CNN news hit, that he “live[s] for laughter” did not exactly help his cause.)

My colleague Megan Garber made a similar observation in her March cover story, in which she argued that American politics has come to resemble a kind of 24-hour reality-television feed, accentuating the ever-blurrier boundary between life and fiction. Recounting some constituents’ blasé responses to last fall’s news of New York Representative George Santos’s many biographical fabrications, Megan noticed echoes of an earlier political moment. “Their reactions,” she wrote, “are reminiscent of the Obama voter who explained to Politico, in 2016, why he would be switching his allegiances: ‘At least Trump is fun to watch.’”

Comedic timing is no measure of moral standing, judgment, or intelligence. Most of us would never flex the skill of “clownery” on a job résumé, and for very good reasons—reasons that likewise apply to public-office aspirants. But, as bygone election seasons have shown time and time again, the thrall of a good show can eclipse better judgment. Let the circus begin.

Related:

Is Ron DeSantis flaming out? We’ve lost the plot. Today’s News Former Proud Boys leader Enrique Tarrio and three other members of the group were convicted of seditious conspiracy for their role in the January 6 Capitol attack. Russia claimed that the United States was behind a drone attack on the Kremlin. A jury found that Ed Sheeran did not infringe on the copyright of Marvin Gaye’s song “Let’s Get It On.” Dispatches Up for Debate: Tucker Carlson was wrong in his analysis of the media, Conor Friedersdorf argues.

Explore all of our newsletters here.

Evening Read Phyllis B. Dooney for The Atlantic

The Future of Policing Is a ‘Little Gay Woman’ Named Terry Cherry

By David A. Graham

One Tuesday this past fall, Senior Police Officer Terry Cherry was struggling to connect with some 75 bleary Clemson University students doing their best to stay awake and not make eye contact with the day’s guest speaker. Cherry, who packs a lot of ebullience and authority into a short frame, was deploying nearly all of it to get their attention.

“Who here wants to be a police officer?” she asked. A few tentative hands went up. “Raise your hand if you want to be an FBI agent.” Twenty-some hands went up.

Read the full article.

More From The Atlantic

Republicans’ big rich-city problem This debt crisis is not like 2011’s. It’s worse. What the drone strikes on the Kremlin reveal about the war in Ukraine Culture Break Illustration by Jan Buchczik

Read. Han Kang’s Greek Lessons, a novel in which language hits its limit—and keeps on going.

Watch. A rerun of The Office (streaming on Peacock). Then learn what Rainn Wilson knows about God.

Play our daily crossword.

P.S.

Speaking of “covfefe,” I recommend revisiting that typo turned meme—and what it meant—in this brief yet incisive 2019 salvo by Atlantic executive editor Adrienne LaFrance: “Long after the president’s tweets are stripped of meaning by the passage of time and the rotting of the internet, his severest critics will still have to grapple with the short distance between politics and entertainment in America, and the man who for years toyed so masterfully with a nation’s attention.”

— Kelli

Katherine Hu contributed to this newsletter.