AI People Play Nice? Nice?
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A Trivia Nerd’s Quizbowl Quest Sheds Light on When to Trust Computers, or Ourselves
BY C H R I S CA R R O L L
P H OTO CO L L AG E S BY VA L E R I E M O R G A N
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he May 2019 showdown between people and artificial intelligence (AI) at the University of Maryland wasn’t exactly a “Terminator”-style last stand for humanity—just a quiz game. Yet it represented, in a sense, the final days of an era when flesh-and-blood competitors could beat silicon-based ones built to relentlessly pursue trivia wins. That day, humankind was represented by four visiting “Jeopardy!” champions. As the game unfolded, the computer buzzed in at least as quickly and accurately as the humans with answers about straightforward facts, like the birthdate of a pop star or the melting point of an element. But other questions required creative logic to link, say, cryptic clues about gender norms to others about religion. “What I call squishy questions, the kind that require lateral thinking, tripped up the system sometimes,” says Roger Craig, a “Jeopardy!” Tournament of Champions winner who held the record for one-day winnings ($77,000) for nearly a decade. Thanks to that limitation, he and past winners Aaron Lichtig, Kristin Sausville and Monica Thieu prevailed 190-160. “It wasn’t a nail-biter, but not a blowout either. If we’d played multiple times, I think we would have won maybe 60% of the time.”
But the balance of power in the game they were playing—quizbowl—has shifted. AI technology has evolved by leaps and bounds since that match; the advent of powerful and uncanny large language models behind popular chatbots and image generators is the prime example. People, though, have pretty much stayed the same. “When it comes to raw accuracy, the computer is now better at answering questions than humans, and I mean humans who are good at this,” says Jordan Boyd-Graber, a UMD computer science professor who hosted the 2019 contest and has been developing the system used in the match, QANTA (Question Answering is Not a Trivial Activity), for nearly 15 years. As one rough measure of the current state of AI, the system answered a recent set of quizbowl questions he and his research team used in a study with 70% accuracy, while humans managed about 55%. Even on “adversarial” questions crafted by AI experts to exploit its weaknesses and give the advantage to humans, computers are catching up. Although he built a system that can reliably beat the smartest people on earth, Boyd-Graber’s goal isn’t AI dominance, or to fuel predictions of AI-induced utopias or apocalyptic visions of humanity rendered obsolete.
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