Melanie Mitchell: "Can Analogy Unlock AI’s Barrier of Meaning?"

UCSB College of Engineering

Speaker Bio: Melanie Mitchell is the Davis Professor of Complexity at the Santa Fe Institute and Professor of Computer Science (currently on leave) at Portland State University. Her current research focuses on conceptual abstraction, analogy-making, and visual recognition in artificial intelligence systems. She is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her latest book is Artificial Intelligence: A Guide for Thinking Humans.

Abstract: In 1986, the mathematician and philosopher Gian-Carlo Rota wrote, “I wonder whether or when artificial intelligence will ever crash the barrier of meaning.” Here, the phrase “barrier of meaning” refers to a belief about humans versus machines: humans are able to “actually understand” the situations they encounter, whereas it can be argued that AI systems (at least current ones) do not possess such understanding.

Some cognitive scientists have proposed that analogy-making is a central mechanism for concept formation and concept understanding in humans. Douglas Hofstadter called analogy-making “the core of cognition”, and Hofstadter and co-author Emmanuel Sander noted, “Without concepts there can be no thought, and without analogies there can be no concepts.” In this talk I will reflect on the role played by analogy-making at all levels of intelligence, and on how analogy-making abilities will be central in developing AI systems with humanlike intelligence.

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