When IBM’s Deep Blue computer beat chess world champion Garry Kasparov back in 1997, my reaction was pretty dispassionate: As someone who’s played only a few games of chess in my life, I simply didn’t have a deep understanding of the game or an emotional attachment to it. But when the news came out over the weekend that IBM is programming a supercomputer to play Jeopardy–well, that’s a breakthrough I can relate to. I haven’t watched the venerable game show much in years, but back in the 1980s, I planned my college courses around it to make sure I was home in time to watch (this was before I had a VCR). I get the game’s subtleties–it’s not just about having an encyclopedic knowledge of both serious stuff and pop culture, but also about being able to unpack the meaning of those questions-phrased-as-answers in a split second. And given that countless very smart people have gone on the show and fallen flat on their faces, I’ll be impressed if IBM’s computer manages an unembarrassing third-place finish. But I don’t have any difficulty dealing with the idea that a computer might someday beat any flesh-and-blood Jeopardy player on the planet.
Thinking about the prospect of a computer taking on Alex Trebek, metaphorical buzzer in hand, led me to the conclusion that game shows in general aren’t a bad Turing Test-like gauge of artificial intelligence. They require knowledge–okay, only a little of it in many cases, but some. They’ve got a social component, by definition. They involve thinking on one’s feet, or the simulation thereof.
So how might a really well-programmed supercomputer fare at other famous game shows of the present and (mostly) past?
It’s baseball season, everybody! Finally!
Just days after the American Recovery and Reinvestment Act was signed into law, today IBM announced that it successfully