creators

Melanie Mitchell: AI, analogy and complexity

Melanie Mitchell is the James B. Alley, Jr. Professor at the Santa Fe Institute and author of Artificial Intelligence: A Guide for Thinking Humans.

Melanie Mitchell is an American computer scientist known for her work on conceptual abstraction, analogy-making and complex systems. She studied mathematics at Brown University, where she also did research in astronomy, and took a PhD in computer science at the University of Michigan in 1990; her dissertation, advised by Douglas Hofstadter, produced the Copycat model of analogy-making. She was a research professor and director of the Adaptive Computation Program at the Santa Fe Institute through the 1990s, then a technical staff member at Los Alamos National Laboratory, a professor at the OGI School of Science and Engineering, and a professor at Portland State University from 2004 to 2020. She has been at SFI since 2020 as the James B. Alley, Jr. Professor, and sits on its Science Steering Committee. She created SFI's Complexity Explorer platform, whose "Introduction to Complexity" course has enrolled more than 25,000 students. Her books include "An Introduction to Genetic Algorithms" (1996), "Complexity: A Guided Tour" (2009), winner of the 2010 Phi Beta Kappa Science Book Award, and "Artificial Intelligence: A Guide for Thinking Humans" (2019). Her recent research and writing, including her Substack newsletter, focus on the reasoning limits of large language models and what machine understanding would require. In 2025 she received a National Academies Eric and Wendy Schmidt Award for Excellence in Science Communications.

Specialization

analogy-making, conceptual abstraction, complex systems, evaluation of AI reasoning

Country

United States