The Race + Data Science Lecture Series aims to celebrate and advance research in the areas of race and data, engineering, and computational science. With this series of events, our goal is to improve how we as data scientists and data-adjacent researchers speak about race.
Guest Speaker
Deborah Raji, Fellow, Mozilla
Details & Recording
Wednesday, October 13 (2:00 PM – 3:00 PM ET) – Virtual’
Chair & Moderator
Desmond Upton Patton, Associate Director of Diversity, Equity and Inclusion, The Data Science Institute, Columbia University. Patton is also Associate Professor of Social Work; Associate Dean of Curriculum Innovation and Academic Affairs; and Courtesy Appointment in Department of Sociology, Columbia University School of Social Work.
Abstract & Biography
The Challenges of Audits, Accountability & Algorithmic Justice
As its popularity and proliferation increase, AI tools are slowly and surely making their way into our everyday lives. However, as its use becomes widespread, we continue to encounter failures that are becoming harder to explain – and hold decision makers accountable for. In this talk, rather than discussing the solutions to these harms, I hope to shed some light on the nature of the problems we face with algorithmic deployments, and the challenges of ensuring accountability and algorithmic justice.
Bio: Deborah is a Mozilla fellow, interested in algorithmic auditing. She also works closely with the Algorithmic Justice League initiative to highlight bias in deployed AI products. She has also worked with Google’s Ethical AI team and been a research fellow at the Partnership on AI and AI Now Institute at New York University working on various projects to operationalize ethical considerations in ML engineering practice. Recently, she was named to Forbes 30 Under 30 and MIT Tech Review 35 Under 35 Innovators.
The Race + Data Science Lecture Series is supported by funding from the MacArthur Foundation and New America.