Feb 12, 4 pm – 6 pm
This panel explores the mathematical and algorithmic work of developing accountability mechanisms in political processes.
We will be joined by two distinguished scholars who work at the intersection of mathematics, law, algorithms, ethics, and policy. Mathematician Moon Duchin (Tufts University) will share her exciting recent work on the uses of randomized algorithms to study the signatures of human intent in the case study of electoral redistricting. Computer scientist Kobbi Nissim (Georgetown University) will discuss the rigorous analysis needed for interpreting privacy law. The discussion will be moderated by professor of economics, Ali Khan (JHU).
4:00 pm Moon Duchin “Decisionmaking Forensics”
4:30 pm Kobbi Nissim “The Mathematics of Privacy Regulation”
5:00 pm Discussion, moderated by Ali Khan (JHU)
Moon Duchin is an Associate Professor of mathematics at Tufts University and serves as director of Tufts’ interdisciplinary Science, Technology, and Society program. Her mathematical research is in geometric group theory, low-dimensional topology, and dynamics. She is the PI of the MGGG Redistricting Lab (mggg.org), a multidisciplinary team that works on the geometry and geography of electoral redistricting.
Kobbi Nissim is a Professor of Computer Science at Georgetown University. He works towards establishing rigorous practices for privacy in computation: identifying problems that result from the collection, sharing, and processing of information, formalizing these problems and studying them towards creating solid practices and technological solutions. He is particularly interested in intersection points between privacy and various disciplines within and outside computer science including cryptography, machine learning, game theory, complexity theory, algorithmics, statistics, databases, and more recently privacy law and policy.
M. Ali Khan is a Professor of Economics at Johns Hopkins University. He pursues interests in economic interaction, as formalized in general equilibrium theory. His wide interests in theory and epistemology are complemented by those in mathematics, especially methods of nonstandard analysis, nonsmooth analysis and optimization, and stochastic processes.