Young children’s learning may be an important model for artificial intelligence (AI). In this program, Alison Gopnik, professor of psychology and member of the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley, says that comparing children and artificial agents in the same tasks and environments can help us understand the abilities of existing systems and create new ones. In particular, many current large data-supervised systems, such as large language models (LLMs), provide new ways to access information collected by past agents. However, they lack the kinds of exploration and innovation that are characteristic of children. New techniques may help to instantiate childlike curiosity, exploration and play in AI systems.

This program is co-hosted with the UC Berkeley College of Computing, Data Science, and Society and the UC Berkeley Artificial Intelligence Research (BAIR) Lab.

About the Series:
CITRIS Research Exchange delivers fresh perspectives on information technology and society from distinguished academic, industry and civic leaders. Free and open to the public, these seminars feature leading voices on societal-scale research issues. Series: "Data Science Channel" [Science] [Show ID: 39351]

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