JUDEA PEARL, professor of computer science at UCLA, has been at the center of not one but two scientific revolutions. First, in the 1980s, he introduced a new approach to artificial intelligence called Bayesian networks. This probability-based model of machine reasoning enabled machines to function in a complex, ambiguous, and uncertain world. Within a few years, Bayesian networks completely overshadowed the previous rule-based approaches to artificial intelligence.
Leveraging the computational benefits of Bayesian networks, Pearl realized that the combination of simple graphical models and probability (as in Bayesian networks) could also be used to represent cause-effect relationships. The significance of this discovery far transcends its roots in artificial intelligence. His principled, mathematical approach to causality has already benefited virtually every field of science and social science, and promises to do more when popularized.
Pearl has written three highly influential scholarly books: Heuristics (Addison-Wesley, 1984), Probabilistic Reasoning in Intelligent Systems (Morgan-Kauffmann, 1988), and Causality: Models, Reasoning, and Inference (Cambridge University Press, 2009). He is a winner of the Alan Turing Award, often considered the equivalent of the Nobel Prize for computer science. He is a member of the U.S. National Academy of Sciences, and was one of the first ten inductees into the IEEE Intelligent Systems Hall of Fame. He has received numerous awards and honorary doctorates, including the Rumelhart Prize (Cognitive Science Society), the Benjamin Franklin Medal (Franklin Institute) and the Lakatos Award (London School of Economics). He is the founder and president of the Daniel Pearl Foundation.