This talk is part of the CAM Colloquium and Cornell’s Center for Data Science for Enterprise and Society’s Data Science Distinguished Lecture Series

ABSTRACT: The mathematical attention to voting systems has come in waves: the first wave was bound up with the development of probability, the second wave was axiomatic, and the third wave is computational. There are many beautiful results giving guarantees and obstructions when it comes to the provable properties of systems of election. But the axioms and objectives from this body of work are not a great match for the practical challenges of 21st century democracy. I will discuss ideas for bringing the tools of modeling and computation into closer conversation with the concerns of policymakers and reformers in the voting rights sphere. In particular, I’ll take a close look at ranked choice voting (or, as Politico recently called it, “the hottest political reform of the moment”).

BIO
Moon’s pure math research is in geometric group theory and geometric topology, with tools from dynamics. She looks at the metric geometry of groups and surfaces, often by zooming out to the large scale picture and  thinks about ways to do coarse geometry more “finely” by paying attention to properties that are destroyed by usual notions of large-scale equivalence. Since 2016 she has been deeply involved in studying the mathematics of redistricting—ever since teaching Math of Social Choice, the entry-level voting theory course at Tufts, for the first time.

Over the next few years, She founded the MGGG Redistricting Lab (mggg.org), which grew out of an informal collective called the Metric Geometry and Gerrymandering Group. They are based at the Tisch College of Civic Life, where their team includes expertise in geometry, modeling and computation, graph algorithms, geography, policy, law, and civics. They bring techniques like Markov chains to the study of fair redistricting, but always in conversation with the real-world applications.

At Tufts, Moon was a founding faculty of the interdisciplinary Science, Technology, and Society program, and a large portion of her work crosses over in an STS direction. She likes to think about the social foundations of authority, about technology and law, and about mathematical interventions for racial justice.