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Mechanism Design for Social Good Working Groups

Bias, Discrimination, and Fairness

The MD4SG Bias, Discrimination, and Fairness working group examines the various social ramifications of technological systems that are deployed in real-world settings. We are especially concerned with the perpetuation and normalization of socially unjust practices that occur when seemingly objective tools embed and operate from biased understandings of the world. Drawing on a variety of academic disciplines, we turn our focus inward to assess how various technical approaches can and cannot be more thoughtfully designed and implemented so to prevent the further marginalization of our most vulnerable communities.


Working Group Organizer

Lily Hu Ph.D. Student in Applied Mathematics Harvard University

Working Group Members

Augustin Chaintreau Associate Professor of Computer Science Columbia University
Shuchi Chawla Professor of Computer Science University of Wisconsin - Madison
Jessica Finocchiaro Ph.D. Student in Computer Science University of Colorado - Boulder
Paul Gölz Ph.D. Student in Computer Science Carnegie Mellon University
Jon Kleinberg Professor of Computer Science and Information Science Cornell University
Faidra Monachou Ph.D. Student in Management Science & Engineering Stanford University
Yasmeen Mussard-Afcari Graduate Research Assistant in Computer Science Howard University
Bikalpa Neupane Ph.D. Student in Informatics & Human Computer Interaction State College, Pennsylvania
Benjamin Otieno PH.D. Student in Information Technology Kibabii University
Eric Sodomka Research Scientist in Economics & Computation Facebook Research
Daniel Stone Associate Professor of Economics Bowdoin University
Briana Vecchione Ph.D. Student in Information Science Cornell University