This month sees MIT’s Brains, Minds, and Machines symposium. The opening panel discussion was moderated by Steven Pinker and called for a reboot in artificial intelligence. The panel consisted of Noam Chomsky, Marvin Minsky, Patrick Winston, Susan Carey, Emilio Bizzi, and Sidney Brenner. Most panelists called for a reboot of old style research methods in AI as opposed to the more narrow applications of AI seen today. An article on Technology review summarizes Chomsky’s contribution:
Chomsky derided researchers in machine learning who use purely statistical methods to produce behavior that mimics something in the world, but who don’t try to understand the meaning of that behavior. Chomsky compared such researchers to scientists who might study the dance made by a bee returning to the hive, and who could produce a statistically based simulation of such a dance without attempting to understand why the bee behaved that way. “That’s a notion of [scientific] success that’s very novel. I don’t know of anything like it in the history of science,” said Chomsky.
I wondered what people thought of this argument and how it relates to the computational and statistical models used to demonstrate language that are becoming so fashionable these days.