Urban Science for Public Good: Gender and Racial Equity in Artificial

Gender and racial equity are often central goals of urban planning. But what are gender and race? What happens when we start to measure and model these dimensions of identity? Conversely, what happens when we ignore gender and race in urban computation? This course introduces students to some of the leading scientists, theorists and practitioners who are working to challenge bias in AI and to use data and computation to work towards gender and racial equity in cities. Along the way, we will reflect on our own identities and learn critical concepts to navigate gender and race from fields such as urban planning, women's and gender studies, critical race studies, and computer science. Licensed for academic year 2019-2020 by the Committee on Curricula. Subject can count toward the 9-unit discovery-focused credit limit for first year-students.