Abstract: This talk explores the design of ecosystems for education, work, and communities to help individuals and communities navigate change. Dr. Lee will share lessons learned around two major themes. We first consider how we might integrate education, work, and community engagement more tightly to provide real-world experiential learning at scale while also supporting community projects. We then discuss the design of human-AI interactions that are more human-centered, where AI is used to augment learning, collaboration, relationships, and individual journeys. We discuss these topics not only through the theoretical lens of research, but also through our practical experience growing the tech4good lab, which currently involves 120+ undergraduate students each quarter in learning user research, ui/ux design, web development, and AI while advancing projects that have served hundreds of other students and community members.
Guest bio: David T. Lee is an Assistant Professor of Computational Media at UC Santa Cruz, where he directs the Tech4Good Lab. He received his Ph.D. from Stanford University and his B.S. from the California Institute of Technology. His research centers on designing human-AI ecosystems for education, work, and community engagement, and on supporting experiential, community-engaged passion-driven learning. He founded and directed several student programs including the Tech4Good Collaboratory, a Course-Based Community Consultancy, and the Exploratory Reading Group program, each of which provide rich learning experiences to hundreds of students as early as their first year. His work has received awards at AAAI HCOMP and ACM CHI, been published in the Proceedings of the National Academy of Sciences (PNAS), and been deployed to serve students, communities, and governments. He has received a Baskin Engineering Teaching Excellence Award, NSF Graduate Research Fellowship, Accel Leadership Fellowship, Santa Cruz Titans of Tech Award, Brown Institute for Media Innovation Magic Grant (x2), Google Scholars Research Award, Public Interest Technology University Network (PIT-UN) Network Challenge, and NSF Improving Undergraduate STEM Education Grant (x2).
