Algorithmic Justice: Race, Bias, and Big Data

Data Science Initiative and the Center for the Study of Race and Ethnicity in America
Institute at Brown for Environment and Society (IBES)
, Carmichael Auditorium, Room 130

Data are not objective; algorithms have biases; machine learning doesn’t produce truth. These realities have uneven effects on people’s lives, often serving to reinforce existing systemic biases and social inequalities. At the same time, data can be used in the service of social justice, and taking control of the data produced about people and its use is more and more important in our data-centric world. Brown’s Center for the Study of Race and Ethnicity in America (CSREA) and Data Science Initiative (DSI) invite you to a panel discussion about algorithms, race, and justice—the problems and the possibilities.

Speakers
  • Meredith Broussard, Assistant Professor of Journalism, Arthur L. Carter Journalism Institute, New York University
  • Max Clermont ’11, MPH ’12, Co-founder, Head of Policy, Data for Black Lives
  • Virginia Eubanks, Associate Professor of Political Science, University of Albany, SUNY
  • Yeshimabeit Milner ’12, Founder and Executive Director, Data for Black Lives
  • Samuel Sinyangwe, Co-Founder, Mapping Police Violence and Campaign Zero

Presented by the Data Science Initiative and the Center for the Study of Race and Ethnicity in America at Brown University.

Lectures, Discussions + Conferences, Video Available