Loeb Lecture: Finding Fairness: What Does an Algorithm See?

Moon Duchin, professor of mathematics at Tufts University, will discuss how mathematical modeling and algorithmic decision-making can be used to track fairness in democratic systems.

Mathematical modeling and algorithmic decision-making is explosively expanding its reach in governance, policy, and across the spectrum of human activity.  The law isn't necessarily catching up very quickly! 

Duchin will give a tour of how mathematicians are using randomness to track fairness in representative democracy, and how courts and commissions are trying to make sense of the story mathematicians are telling. From party-blind redistricting in Missouri to race-blind redistricting in Mississippi, case studies can help us understand how to think with algorithms.

Hosts: Aliakbar Daemi and Ari Stern

Moon Duchin is a professor of mathematics, a senior fellow in the Jonathan M. Tisch College of Civic Life, and recently finished a term as director of the Program in Science, Technology, and Society at Tufts University.  Her pure math work is in geometry, topology, groups, and dynamics. Her work in applied pure math includes collaborations with civil rights organizations, data and computational scientists, political scientists, lawyers, and geographers on a large-scale project to detect and address gerrymandering. Duchin is a Fellow of the American Mathematical Society and has recently provided expert reports and testimony in redistricting litigation in Wisconsin, North Carolina, Alabama, South Carolina, and Pennsylvania.

Duchin concentrated in mathematics and women’s studies at Harvard College and received her PhD in mathematics from the University of Chicago. She has been awarded an NSF CAREER grant, a Guggenheim Fellowship, and a Radcliffe Institute Fellowship, and she has been selected to give the prestigious AMS Einstein Public Lecture in mathematics in 2023.

A tea will be served at 3:30 in Bowles Plaza. In case of inclement weather, the tea reception will take place in McMillan Cafe.

Access Lecture Via Zoom (Passcode: 192564)