Judea Pearl
Professor of Computer Science and Director of the Cognitive Systems Lab at UCLA, recipient of the A.M. Turing Award, 2020 World Leader in AI World Society Award

Judea Pearl, (born 1936, Tel Aviv), is an Israeli-American computer scientist and winner of the 2011 A.M. Turing Award, the highest honour in computer science, for his “fundamental contributions to artificial intelligence.”

Pearl received a bachelor’s degree in electrical engineering from Technion–Israel Institute of Technology in Haifa in 1960 and a master’s degree in electrical engineering from Newark College of Engineering (now part of the New Jersey Institute of Technology) in 1961. He then received a master’s in physics from Rutgers University in New Brunswick, New Jersey, and a doctorate in electrical engineering from the Polytechnic Institute of Brooklyn in New York (now the Polytechnic Institute of New York University) in 1965. He worked at the David Sarnoff Laboratories of the RCA Corporation (now the Sarnoff Corporation) in Princeton, New Jersey, and on computer memory at the manufacturer Electronic Memories, Inc. (later Electronics Memories and Magnetics Corp.), in Hawthorne, California. He became a professor of computer science at the University of California, Los Angeles, in 1970.

Pearl introduced the messiness of real life to artificial intelligence. Previous work in the field had a foundation in Boolean algebra, where statements were either true or false. Pearl created the Bayesian network, which used graph theory (and often, but not always, Bayesian statistics) to allow machines to make plausible hypotheses when given uncertain or fragmentary information. He described this work in his book Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (1988).
Pearl’s work after the 1990s concentrated on the role of morality in artificial intelligence, specifically the role of counterfactual statements—that is, a statement where the premise is not true (e.g., “If the car had worked, I would have driven to the store”). He has posited that counterfactual statements are “the building blocks of scientific and moral behaviour” and thus that machines that could understand such statements would be able to take responsibility for their actions.