Abstract
For a few years, we have been developing algorithms to predict individual attributes like personality traits, political preferences, and demographics. More recently, we have shown that AI combined with social data can predict future behavior - before the users know what their actions will be.
This talk will discuss the cutting edge of user attribute inference, discuss the applications of this work, and address the myriad of privacy concerns that these algorithms provoke.
Agenda
4:00 - 5:00 pm: Talk
5:00 - 5:30 Breakout Rooms
About Dr. Jennifer Golbeck
Dr. Jennifer Golbeck is Director of the Social Intelligence Lab and an Associate Professor in the College of Information Studies at the University of Maryland, College Park.
Her research focuses on analyzing and computing with social media, focused on predicting user attributes, and using the results to design and build systems that improve the way people interact with information online. She also studies how people perceive privacy on the web and how to build better privacy-respecting systems.
She received an AB in Economics and an SB and SM in Computer Science at the University of Chicago, and a Ph.D. in Computer Science from the University of Maryland, College Park. Golbeck is a member of the ACM and SIGCHI and an ACM Distinguished Speaker.
Location
Zoom Meeting - Details will be provided upon registration
Fees
All: Free
(Membership: $30 Annually)