Stuart E. Dreyfus is professor emeritus of industrial engineering and operations research at the University of California, Berkeley.[1] At the RAND Corporation he programmed the JOHNNIAC computer and co-authored Applied Dynamic Programming with Richard Bellman; dynamic programming, his central field, is one of the mathematical foundations of the reinforcement learning behind modern AI.[1]
With his older brother Hubert, a philosopher, he built the Dreyfus model of skill acquisition, first set out in their 1980 report for the Air Force.[2] He later argued, in his account of “System 0,” that expert intuition is the brain’s procedural memory learning by trial, feedback, and reward, the same reinforcement-learning mechanism his own mathematics helped give the machines.[3] His own summary of the position is blunt: “Expertise is pattern discrimination and association based on experience. It is intuitive. There is no evidence you can reduce it to rules and theory. Hence, Artificial Intelligence probably can’t be produced using rules and principles. That’s not what intelligence is.”[4]