Title: Virtual Democracy and Food Rescue
Speaker: Anson Kahng
Virtual democracy is an approach to automating decisions, by learning models of the preferences of individual people, and, at runtime, aggregating the predicted preferences of those people on the dilemma at hand. One of the key questions is which aggregation method — or voting rule — to use; we offer a novel statistical viewpoint that provides guidance. Specifically, we seek voting rules that are robust to prediction errors, in that their output on people’s true preferences is likely to coincide with their output on noisy estimates thereof. We prove that the classic Borda count rule is robust in this sense, whereas any voting rule belonging to the wide family of pairwise-majority consistent rules is not. Our empirical results further support, and more precisely measure, the robustness of Borda count. Lastly, we consider the application of virtual democracy to the domain of food rescue, or matching food donations to needy recipients.
Anson is a third-year PhD student in the Computer Science Department at Carnegie Mellon University, where he is advised by Ariel Procaccia. He works on theoretical problems at the intersection of computer science and economics, particularly in computational social choice. Recently, he has worked on voting aggregation for noisy votes, impartial voting mechanisms, virtual democracy, and liquid democracy.