Machine Learning Paragons Square Off

August 22, 2012

It is an AI kerfuffle, we learn from’s “Norvig vs. Chomsky and the Fight for the Future of AI.” The two prominent machine linguists, one old-school and one new, are at philosophical odds over the future of machine learning. Simply put, the esteemed Noam Chomsky seems to have started it when he criticized today’s researchers for using statistical methods to mimic behavior without attempting to understand the meaning of that behavior. Google’s director of research Peter Norvig shot back, insisting that such understanding is overrated. Instead, he advocates a statistical reasoning approach underpinned by huge amounts of data populating huge lookup tables.

Tor’s Kevan Gold describes the conflict well. This issue embodies the conflict between getting the answer and understanding the answer; Gold’s math homework analogy captures it well. In his conclusion he extrapolates:

“What seems to be a debate about linguistics and AI is actually a debate about the future of knowledge and science. Is human understanding necessary for making successful predictions? If the answer is ‘no,’ and the best way to make predictions is by churning mountains of data through powerful algorithms, the role of the scientist may fundamentally change forever. But I suspect that the faith of Kepler and Einstein in the elegance of the universe will be vindicated in language and intelligence as well; and if not, we at least have to try.”

Christopher Berry also contributes to the discussion in his Eyes on Analytics blog post, “Norvig, Chomsky, Science, Models.” Check out his umbrella analogy. I like his succinct conclusion:

“Machine learning is as a power tool in the belt. It isn’t a substitute for the objective itself.”

Though both of these writers seem to bolster Chomsky, I suspect this issue will not be resolved quickly, if at all. Stay tuned.

Cynthia Murrell, August 22, 2012

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