AI researcher Melanie Mitchell argues true intelligence rests on concepts and analogy-making, and warns we're vastly underestimating how hard human-level AI is.

Melanie Mitchell — Professor of computer science at Portland State University and external professor at the Santa Fe Institute. A former student of Douglas Hofstadter and John Holland, she created the copycat analogy-making architecture and wrote 'Artificial Intelligence: A Guide for Thinking Humans.'
Melanie Mitchell joins Lex Fridman to question what intelligence really is and whether today's AI is anywhere close to it. She argues that concepts and analogy-making are the core of cognition, drawing on her copycat project built with Douglas Hofstadter. Mitchell is skeptical that brute-force deep learning can reach human-level intelligence, pointing to missing common sense, embodiment, and innate structure. She discusses autonomous driving as a case where the open-ended 'long tail' demands common sense, and critiques the orthogonality view of superintelligence held by Bostrom and Russell. She closes on complexity science, the Santa Fe Institute, and her pride in copycat.
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Melanie Mitchell
“she has contributed a lot of important ideas to the field of AI including her recent book simply called artificial intelligence a guide for thinking humans” — Lex Fridman 00:00:30Find it on Amazon
Melanie Mitchell
“I have a book called analogy making as perception which is a version of my PhD thesis on it” — guest 01:51:08Find it on Amazon