Rediet Abebe was born and grew up in Addis Ababa, Ethiopia, before moving to the United States to continue her education. She pursued graduate study in computer science at Cornell University, where she became the first Black woman to earn a Ph.D. in the department's history, focused on the theoretical and applied intersections of algorithms with questions of poverty and inequality.
Abebe's research centres on what she and collaborators term 'algorithmic fairness' and 'mechanism design for social good' — using the tools of computer science not merely to optimise commercial systems, but to explicitly model and address problems like access to housing, healthcare, and economic opportunity. Her work challenges the assumption that algorithms are neutral, examining instead how systems can be deliberately designed to reduce, rather than reinforce, existing inequality.
She co-founded Mechanism Design for Social Good (MD4SG), a research initiative and community connecting economists, computer scientists, and social scientists working on algorithmic approaches to social problems, and Black in AI, an organisation supporting Black researchers and practitioners in artificial intelligence, addressing significant underrepresentation in the field.
Abebe is now an assistant professor of computer science at the University of California, Berkeley, where she continues her research on the societal applications and consequences of algorithmic systems, and remains an active voice on the responsible design of AI and machine learning technologies.
- First Black woman to earn a computer science Ph.D. at Cornell University
- Co-founded Mechanism Design for Social Good (MD4SG)
- Co-founded Black in AI, supporting Black researchers in artificial intelligence
- Assistant Professor of Computer Science, UC Berkeley
- Tools are not neutral — design them deliberately. Abebe's research insists that algorithms reflect the values built into them, and argues for building in equity rather than assuming it.
- Build the community you were missing. Both MD4SG and Black in AI exist because she and her collaborators identified real gaps in who gets to shape algorithmic research.