FINAL JEOPARDY

Are you ready for machines to take over the world? How about just a game show to start with?

That’s just the scenario of BusinessWeek senior technology writer Baker’s (The Numerati, 2008) account of the difficult birth of Watson, the IBM computer that just won a championship round on Jeopardy. Cleverly, the author’s narrative works regardless of the outcome—for either way, the setup is the same: After the birth of Deep Blue, the supercomputer that beat grandmaster Garry Kasparov in a game of chess in 1997, IBM scientists set about building another machine. This one, like all machines, basically knows nothing—but, intriguingly, can approximate thought all the same. Imagine, as Baker describes it, how we might parse this clue: “This facial ware made Israel’s Moshe Dayan instantly recognizable worldwide.” You’d have to know something about who Dayan was and probably have been around in the day when the monocular Yul Brynner look-alike walked the earth, whereas Watson would merely go through millions of iterations of binary data by way of a process that, as Baker notes, is “scandalously wasteful of computing resources” to arrive at the correct answer: eyepatch. Scandalously wasteful, perhaps. But imagine a few generations down the line, when Watson will have spawned machines that, to name just one real-world application, can store the texts of every medical-journal article ever written—weighing the newer ones more favorably than those from, say, Victorian England—to aid diagnosticians in their work. But how to get the machine to be able to parse real-world data and skirt the shoals of puns, subtleties, metaphors and all the other tricks human language allows? There’s the rub, and Baker provides a fine, often entertaining account of the false steps that led Watson, ever the literalist, to read Malcolm X as “Malcolm Ten” and to confuse Charles Dickens’s Oliver Twist with the Pet Shop Boys. Like Tracy Kidder’s Soul of a New Machine (1981), Baker’s book finds us at the dawn of a singularity. It’s an excellent case study, and does good double duty as a Philip K. Dick scenario, too.