The Dob in No I, but It's So Simple

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i remember whena simon dedeo was a previous guest on the podcast. He mentioned in conversation that he wanted to do an implementation of judea pearls due operator. And i had never heard of this concept before, but instantly iwas i i had the impression this was something very, very, very important. So i ran out and learned about it. Ad it's clear thatis is going to be crucial to have we're thinking about artificial intelligence and complicated science questions going forward. I'm very happy with the do pos e, but it's so simple.

To say that event A causes event B is to not only make a claim about our actual world, but about other possible worlds — in worlds where A didn’t happen but everything else was the same, B would not have happened. This leads to an obvious difficulty if we want to infer causes from sets of data — we generally only have data about the actual world. Happily, there are ways around this difficulty, and the study of causal relations is of central importance in modern social science and artificial intelligence research. Judea Pearl has been the leader of the “causal revolution,” and we talk about what that means and what questions remain unanswered.

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Judea Pearl received a Ph.D. in electrical engineering from the Polytechnic Institute of Brooklyn. He is currently a professor of computer science and statistics and director of the Cognitive Systems Laboratory at UCLA. He is a founding editor of the Journal of Causal Inference. Among his awards are the Lakatos Award in the philosophy of science, The Allen Newell Award from the Association for Computing Machinery, the Benjamin Franklin Medal, the Rumelhart Prize from the Cognitive Science Society, the ACM Turing Award, and the Grenander Prize from the American Mathematical Society. He is the co-author (with Dana MacKenzie) of The Book of Why: The New Science of Cause and Effect.

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