Artificial intelligence is now part of homes, classrooms, and care settings—through apps, toys, and learning platforms—yet babies and toddlers remain largely absent from AI policy conversations, despite this being the most critical window for brain development.
On September 9, the Center for Universal Education at Brookings and ZERO TO THREE will host a symposium on the opportunities and risks of AI for children from birth to age 8, bringing together researchers, technology leaders, media experts, policy makers and other stakeholders to explore how these technologies can support healthy early development.
The event is part of the Generation AI starts early initiative.
Online viewers can submit questions in advance via email.
Register to watch online
Agenda:
9:00-9:15am – Welcome
Matthew Melmed, Executive Director, ZERO TO THREE
Sweta Shah, Fellow, Center for Universal Education, Brookings
Kathy Kirsh-Pasek, Senior Fellow, Center for Universal Education, Brookings
9:15-9:35am – Keynote
Dr. Dana Suskind, Founder and Co-Director, TMW Center for Early Learning + Public Health; Founding Director, Pediatric Cochlear Implant Program; Professor of Surgery and Pediatrics, University of Chicago Medicine
9:35-10:35am – Expert panel: The developing child in an AI world
Kathy Hirsh-Pasek, Senior Fellow, Center for Universal Education, Brookings
Dr. Jenny Radesky, David G. Dickinson Legacy Professor Pediatrics, Associate Professor of Pediatrics, and Division Director of Developmental and Behavioral Pediatrics, University of Michigan Medical School
Ying Xu, Assistant Professor of Education, Harvard Graduate School of Education
Moderator: Caitlin Gibson, Feature Writer, The Washington Post
10:45-11:45am – Expert panel: Practice and innovation panel: Building an AI world fit for young children
Michael Levin, Director of Strategy and Partnerships, Or Initiative, Chapman University
Allison Mishkin, Youth Safety Lead, OpenAI
Andreana Castellanos, Chief Executive Officer and Founder, Afinidata
Moderator: Laurie Segall, Chief Executive Officer, Mostly Human
