Transmission vs. Truth, Imitation vs. Innovation: What 4-year-olds can teach AI

EECS Colloquium

Wednesday, November 8, 2023

306 Soda Hall (HP Auditorium)
4:00 – 5:00 pm

 Youtube Webinar

Abstract

Much discussion about large language models and language-and-vision as well as other AI models has focused on whether these models are intelligent agents. I present an alternative perspective. First, I argue that LLM’s are cultural technologies that enhance cultural transmission and are efficient and powerful imitation engines. Second, I explore what AI models can tell us about imitation and innovation by testing whether they can be used to discover new tools and novel causal structures, and contrasting their responses with those of human children. Third, I report examples of exploration techniques that are used by children and show how they can lead to advances in reinforcement learning.

Biography

Alison Gopnik is a professor of psychology and affiliate professor of philosophy at the University of California at Berkeley, and a member of the Berkeley AI Research Group. She received her BA from McGill University and her Ph.D. from Oxford University. She is a leader in the study of cognitive science and of children’s learning and development and was one of the founders of the field of “theory of mind”, an originator of the “theory theory” of cognitive development, and the first to apply Bayesian probabilistic models to children’s learning. She has received both the APS Lifetime Achievement Cattell and William James Awards, the Bradford Washburn Award for Science Communication, the SRCD Lifetime Achievement Award for Basic Science in Child Development and the Rumelhart Prize for Theoretical Foundations of Cognitive Science. She is an elected member of the Society of Experimental Psychologists and the American Academy of Arts and Sciences and a Cognitive Science Society, American Association for the Advancement of Science, and Guggenheim Fellow. She was 2022-23 President of the Association for Psychological Science.