Date: Monday, September 9, 2019
Time: 12:15 PM - 2:00 PM
Location:Pierce Hall 100F, 29 Oxford St., Cambridge, MA
Contact Name:Shana Ashar
Sponsor:Mossavar-Rahmani Center for Business and Government
Centers & Initiatives:
STS Circle with Moon Duchin (Tufts, Mathematics)
?Abstract We‘ve all heard that algorithmic assistance is increasingly used for high-stakes decisionmaking, from policing and sentencing to medical diagnosis to resource allocation, sometimes with manifestly unjust results. Often, these critical conversations treat algorithms as consummate black boxes, either because the algorithms are proprietary or because they are built on such complicated neural networks (say) that their interpretability is severely limited. But what if we wrote the algorithms? Electoral redistricting is an excellent problem domain for this inquiry it seems perfectly clear that something is wrong and unfair about the way gerrymandered maps divide people for the purposes of voting, but it's quite hard to locate the precise harm and even harder to reason about remedies. I'll use the case of redistricting to tell overlapping stories model design; Constitutional logic; and metrics of fairness. Bio Moon Duchin is an associate professor of Mathematics and Senior Fellow in the Tisch College of Civic Life at Tufts University. She serves as director of the interdisciplinary program in Science, Technology, and Society and as collaborating faculty in the Department of Race, Colonialism, and Diaspora Studies. Her mathematical subfields are geometry, topology, group theory, and dynamical systems. Her current research focus is in the study of electoral redistricting in the U.S., using Markov chain Monte Carlo and other randomized algorithms to understand relationships between community, partisanship, race, and representation.