Why Computers Still Don't Understand People

Gary Marcus writes in the New Yorker about the state of artificial intelligence, and how we take it for granted that AI involves a very particular, very narrow definition of intelligence. A computer's ability to answer questions is still largely dependent on whether the computer has seen that question before. Quoting: "Siri and Google’s voice searches may be able to understand canned sentences like 'What movies are showing near me at seven o’clock?,' but what about questions—'Can an alligator run the hundred-metre hurdles?'—that nobody has heard before? Any ordinary adult can figure that one out. (No. Alligators can’t hurdle.) But if you type the question into Google, you get information about Florida Gators track and field. Other search engines, like Wolfram Alpha, can’t answer the question, either. Watson, the computer system that won “Jeopardy!,” likely wouldn’t do much better. In a terrific paper just presented at the premier international conference on artificial intelligence (PDF), Levesque, a University of Toronto computer scientist who studies these questions, has taken just about everyone in the field of A.I. to task. ...Levesque argues that the Turing test is almost meaningless, because it is far too easy to game. ... To try and get the field back on track, Levesque is encouraging artificial-intelligence researchers to consider a different test that is much harder to game ..."

Comments

Re:Missing the point as usual

[ganv]

One of the great open questions about the future of humanity is which will happen first: A) we figure out how our minds are able to understand the world and solve the problems involved in surviving and reproducing. B) we figure out how to build machines that are better than humans at understanding the world and solving the problems involved in surviving and reproducing.

I think it is not at all clear which one will happen first. I think the article's point is exactly right. It doesn't matter what intelligence is. It only matters what intelligence does. The whole field of AI is built around the assumption that we can solve B without solving A. They may be right. Evolution often builds very complicated solutions. Compare a human 'computer' to a calculator doing arithmetic. Clearly we don't need to understand how the brain does this in order to build something better than a human. Maybe the same can be done for general intelligence. Maybe not. I advocate pursuing both avenues.