Data for Good: Sarita Schoenebeck, University of Michigan

Data for Good: Sarita Schoenebeck, University of Michigan
Friday, October 30, 2020
11:00 AM - 12:00 PM
Online Event
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Presented by: The Computational Social Science Working Group, Columbia University

Guest Speaker: Sarita Schoenebeck, Associate Professor, School of Information; Director of the Living Online Lab (LOL); and Co-Director the Social Media Research Lab, University of Michigan

Building Just Technologies in an Unjust World

Abstract: Computing has embraced principles of neutrality, objectivity, and fairness. However, societies are neither neutral, objective, nor fair. Prescribing these values in computing can inadvertently mirror, or amplify, widespread societal injustices. This talk will explore how justice theories, including restorative justice, racial justice, and social justice, can expose alternative approaches for the design and analysis of computational systems. The talk will identify synergies between human-computer interaction and machine learning, using the context of online harassment as a case study. In doing so, it will explore what aspects of online harassment, such as experiences of harm, can or should be formalized in algorithms or not. It will conclude with reflections on how to embed justice in research, teaching, and service activities and in institutional priorities.

Bio: Sarita Schoenebeck is an Associate Professor in the School of Information at the University of Michigan. She directs the Living Online Lab and co-directs the Social Media Research Lab. Her research focuses on promoting more equitable and inclusive experiences online. She received her Ph.D. in Human-Centered Computing from Georgia Tech. She is the recipient of the NSF CAREER award, the UMSI Diversity, Equity, and Inclusion award, and Best Paper and Honorable Mention awards at CHI and CSCW. Her research has been covered multiple times in The New York Times, the Washington Post, NPR, and elsewhere.
Event Contact Information:
Data Science Institute
212-854-5660
[email protected]
LOCATION:
  • Online
TYPE:
  • Lecture
  • Seminar
  • Webcast
CATEGORY:
  • Computer Science
  • Engineering
EVENTS OPEN TO:
  • Alumni
  • Faculty
  • Family-friendly
  • Graduate Students
  • Postdocs
  • Prospective Students
  • Public
  • Staff
  • Students
  • Trainees
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