ITS
Information Technology Services
ITS
Information Technology Services
Our weekly SRI Seminar Series welcomes Michael Bernstein, an associate professor of computer science at Stanford University, where he is a member of the Human-Computer Interaction Group. Bernstein’s research on the design of social computing systems has won best paper awards at top conferences in human-computer interaction, and has been reported in venues such as The New York Times, New Scientist, Wired, and The Guardian.
In this talk, Bernstein will explore how AI systems respond to and mitigate forms of societal disagreement, demonstrating a “Jury Learning” AI architecture that is designed to resolve such forms disagreement, and organizational initiatives established to aid researchers in navigating these issues.
Whose voices—whose labels—should artificial intelligence (AI) systems learn to emulate? For AI tasks ranging from online comment toxicity to misinformation detection to medical diagnosis, different groups in society may have irreconcilable disagreements about what constitutes ground truth. I will present empirical results demonstrating that current AI metrics overestimate performance in the face of this societal disagreement. In response, I will describe Jury Learning, an AI architecture that resolves these disagreements explicitly through the metaphor of a jury: defining which people or groups, in what proportion, determine the classifier’s prediction. Because no technical architecture is singularly enough to solve these problems, I will also describe an organizational architecture, Ethics and Society Review (ESR), which we created at Stanford University to aid researchers in navigating these issues.
Michael Bernstein is an associate professor of computer science and STMicroelectronics Faculty Scholar at Stanford University, where he is a member of the Human-Computer Interaction Group. Bernstein’s research focuses on the design of social computing systems. This research has won best paper awards at top conferences in human-computer interaction, including CHI, CSCW, and UIST, and has been reported in venues such as The New York Times, New Scientist, Wired, and The Guardian. Michael has been recognized with an Alfred P. Sloan Fellowship, UIST Lasting Impact Award, and the Patrick J. McGovern Tech for Humanity Prize. He holds a bachelor’s degree in Symbolic Systems from Stanford University, as well as a master’s degree and a PhD in computer science from MIT.
To register for the event, visit the official registration page.
The SRI Seminar Series brings together the Schwartz Reisman community and beyond for a robust exchange of ideas that advance scholarship at the intersection of technology and society. Seminars are led by a leading or emerging scholar and feature extensive discussion.
Each week, a featured speaker will present for 45 minutes, followed by an open discussion. Registered attendees will be emailed a Zoom link before the event begins. The event will be recorded and posted online.
