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Rediet Abebe

Junior Fellow, Harvard Society of Fellows
Assistant Professor, UC Berkeley
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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.

Technical Vision Talk: Roles for Computing in Social Justice
​Recent scholarship warns that computing work has treated problematic features of the status quo as fixed, failing to address and often even exacerbating deep patterns of injustice and inequality. This begs the question: what roles, if any, can computing play to support and advance fundamental social change? Through an analysis informed by critical scholarship, we articulate four such roles -- computing as a diagnostic, formalizer, rebuttal, and synecdoche. We discuss examples of research in algorithms, machine learning, and mechanism design that cut a path between solutionist and critical perspectives. We use these to highlight potential ways in which computational techniques can support, rather than supplant, other modes of understanding and tackling social inequities. Examining Mechanism Design for Social Good (MD4SG) -- a multi-disciplinary research network -- as a case study, we discuss how these insights may be used to assist advocacy work aimed at fostering more equitable and just systems.

Meet-the-Speaker:
Rediet will also participate in a Meet the Speaker session, where you will be able to have a deeper dive conversation about topics covered on the main stage. Accessible to WiDS Worldwide registrants.

Join us at WiDS Worldwide! 
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  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Research
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conferences
    • WiDS Stanford 2023 Agenda
    • WiDS Stanford 2023 Speakers
    • WiDS Regional Events 2023
    • Ambassadors 2023 >
      • Ambassador Advisory Council
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2022
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Datathon Details
    • Datathon Resources >
      • Datathon Press Release
    • WiDS Datathon Workshops 2023
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Next Gen >
      • Next Gen Resources
      • Next Gen Committee