Drivers here actually stop at yellow lights. Ticket takers at the ballpark hold up the line by talking with each customer. So far, this is Roger Schank’s only complaint about Chicago: “It’s slow!”
“He’s getting three professorships–that’s almost unheard-of in the academic world–and in unrelated fields,” sniffs Harvey Newquist, publisher of the Arizona-based industry newsletter AI Trends and no buddy of Schank’s. “Basically, either Andersen’s got a guy who’s spread way too thin, or else Northwestern has.”
This is a variation on the “imitation game” proposed by British computer scientist Alan Turing in the early 1950s. Essentially, Turing said that the question “Can a machine think?” is meaningless unless interpreted very concretely. All we can tell is whether its output is distinguishable from a human’s; if it is not, then the machine must be thinking, because we don’t get anything more than output from people either.
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Plenty of perfectly intelligent people can’t play chess and can’t prove the Pythagorean theorem. But you might wonder about someone who went to Burger King and sat down at a table expecting a waiter to bring a menu. You would wonder even more if they had been to a fast-food joint before. People get along “intelligently” in such situations not because they reason them out anew every time, but because they have a “script”–a pattern of routine expectations derived from similar experiences before. (Schank developed the path-breaking “script” idea in a book coauthored with Yale psychologist Robert Abelson in 1977.) Because you’re familiar with a “restaurant script,” you can read “John went to a restaurant. He asked the waitress for coq au vin. He paid the check and left” and understand, without being told, that John ordered from a menu and that he ate the coq au vin. By contrast, Schank points out, a structurally similar story makes no sense if we have no script for it: “John went to the park. He asked the midget for a mouse. He picked up the box and left.”
What does all this–which only seems obvious after someone has pointed it out–have to do with artificial intelligence? Quite a bit. AI turns out to be a kind of two-faced discipline: you need to understand very clearly how people think in order to program a computer to do so–and at the same time, you can check up on your understanding by seeing whether the computer in fact does what you meant it to do. CYRUS, a program Schank and student Janet Kolodner developed at Yale, understood enough of the diplomatic life and travels of then-secretary of state Cyrus Vance to be able to figure out that Vance’s wife and the wife of Israeli premier Menachem Begin had probably met at a state dinner–just from its fund of knowledge about their schedules and about the scripts of such meetings (e.g., banquet at which spouses are present, etc). This kind of reasoning is much closer to what people “intelligently” do every day than calculating the consequences of a chess move at 720,000 positions a second.
The problem has always been that we’re people, and we take too much about ourselves for granted. Because the computer takes nothing for granted, it produces strange results when we fail to make our assumptions explicit. And making these “obvious” assumptions explicit is much harder work than it seems. That’s why Schank likes Edison’s quip about genius being 1 percent inspiration and 99 percent perspiration: “I don’t think we need more ideas. What we need is more execution of ideas. And that turns out to be really tough.”
Here’s the education-department connection again: This is also Schank’s theory of good teaching, whether done person-to-person or computer-to-person. “We remember physics teachers telling their stories visually with great drama,” he writes in a recent paper on education and training. “We remember history teachers telling good stories from history. We remember English teachers telling good stories about former students’ writing problems, or about the lives of famous authors. We often have trouble remembering anything else but the stories. The stuff we were quizzed on has long since vanished.
