Francisca García-Cobián Richter, PhD, research associate professor at the Jack, Joseph and Morton Mandel School of Applied Social Sciences, will present the monthly Mary Ann Swetland Center for Environmental Health webinar. Richter argues that without an explicit framework to identify and address discrimination bias, data science will not realize its potential to advance social justice.
Building upon the FAIR (Findable, Accessible, Interoperable and Reusable) principles of (meta) data and drawing from research in the social, health and data sciences, Richter proposes a framework—FAIR2 (Frame, Articulate, Identify, Report)—for identifying and addressing discrimination bias in social data science.
Richter says FAIR2 enriches data science with experiential knowledge, clarifies assumptions about discrimination with causal graphs and systematically analyzes sources of bias in the data, leading to a more ethical use of data and analytics for the public interest—and eventual use in classrooms to prepare a new and diverse generation of data scientists.
The free webinar is on Sept 26 at 9 a.m.