Herbert A. Simon (1916-2001) was an American scholar whose work spanned economics, political science, psychology, and computer science. He spent most of his career at Carnegie Mellon University and is one of the rare figures to win top honors in two different fields: the ACM Turing Award in computing and the Nobel Memorial Prize in Economic Sciences.
Simon is one of the founders of artificial intelligence. With Allen Newell and Cliff Shaw he built the Logic Theorist in 1956 and the General Problem Solver, and with Newell he developed the physical symbol system hypothesis, the foundational claim of symbolic AI. The two shared the 1975 Turing Award. In economics and decision theory, Simon is best known for “bounded rationality” and “satisficing,” the idea that real people and organizations do not optimize perfectly but settle for good-enough decisions given limited information and time. For this he won the 1978 Nobel Prize in Economic Sciences, awarded, in the words of the official citation, “for his pioneering research into the decision-making process within economic organizations.”
Simon’s career was unusually unified by a single question: how do people and machines actually make decisions and solve problems? His answer, that thinking is information processing that can be modeled and reproduced, links his economics, his psychology, and his AI work into one body of thought.
Why business readers should care: Simon’s idea of bounded rationality is now standard in how we think about real-world decision making, and his AI work helped establish that human expertise and judgment can be modeled by machines. Both themes sit at the center of how organizations use AI to support decisions today.