HMI DAIS 10 - Rediet Abebe (Harvard Society of Fellows/University of California, Berkeley incoming)
HMI DAIS 10 - Rediet Abebe (Harvard Society of Fellows/University of California, Berkeley incoming)
Public online seminar, 9am 29 October 2020 AEST
Rediet Abebe gave the tenth HMI Data, AI and Society public seminar.
Rediet Abebe is a Junior Fellow at the Harvard Society of Fellows and an incoming Assistant Professor of Computer Science at the University of California, Berkeley. Abebe holds a Ph.D. in computer science from Cornell University and graduate degrees in mathematics from Harvard University and the University of Cambridge. Her research is in artificial intelligence and algorithms, with a focus on equity and justice concerns. Abebe is a co-founder and co-organizer of the multi-institutional, interdisciplinary research initiative Mechanism Design for Social Good (MD4SG). Her dissertation received the 2020 ACM SIGKDD Dissertation Award for offering the foundations of this emerging research area. Abebe's work has informed policy and practice at the National Institute of Health (NIH) and the Ethiopian Ministry of Education. She has been honored in the MIT Technology Reviews' 35 Innovators Under 35 and the Bloomberg 50 list as a one to watch. Abebe also co-founded Black in AI, a non-profit organization tackling representation issues in AI. Her research is influenced by her upbringing in her hometown of Addis Ababa, Ethiopia.
Seminar Title: Roles for Computing in Social Justice
Abstract: Recent scholarship in AI ethics warns that computing work has treated problematic features of the status quo as fixed, failing to address and even exacerbate deep patterns of injustice and inequality. Acknowledging these critiques, we ask: what roles, if any, can computing play to support and advance fundamental social change? We articulate four such roles -- computing as a diagnostic, formalizer, rebuttal, and synecdoche -- through an analysis that considers the opportunities as well as the significant risks inherent in such work. We then discuss how these insights may be used to support advocacy work aimed at fostering more equitable and just systems.
HMI Dais recordings can be viewed here.