I am Gordon McKay Professor of Computer Science at Harvard University; I am also affiliated with the Center for Research on Computation and Society. Before joining Harvard in 2020, I had been a faculty member in the Computer Science Department at Carnegie Mellon University.
I work on a broad and dynamic set of problems related to AI, algorithms, economics, and society. I am especially excited about projects that involve both interesting theory and direct applications; examples include the websites Spliddit and RoboVote, and ongoing collaborations with nonprofit organizations such as Refugees.AI, 412 Food Rescue, and the Sortition Foundation.
Not-for-profit service that provides solutions to everyday fair division problemsGo there
Not-for-profit service that aggregates preferences or opinions into optimal decisionsGo there
MD4SG Workshop, June 2019
I will present the 'virtual democracy' framework for the design of ethical AI. In a nutshell, the framework consists of three steps: first, collect preferences from voters on example dilemmas; second, learn models of their preferences, which generalize to any (previously unseen) dilemma; and third, at runtime, predict the voters' preferences on the current dilemma, and aggregate these virtual 'votes' using a voting rule to reach a decision. I will focus on two instantiations of this approach: a proof-of concept system that decides ethical dilemmas potentially faced by autonomous vehicles, and a decision support tool designed to help a Pittsburgh-based nonprofit allocate food donations to recipient organizations. These projects bridge AI, social choice theory, statistics, and human-computer interaction; I will discuss challenges in all of these areas.
University of Washington CS Colloquium, November 2017
Computational social choice deals with algorithms for aggregating individual preferences or opinions towards collective decisions. AI researchers (including myself) have long argued that such algorithms could play a crucial role in the design and implementation of multiagent systems. However, in the last few years I have come to realize that the "killer app" of computational social choice is helping people — not software agents — make joint decisions. I will illustrate this theme through two recent endeavors: Spliddit.org, a website that offers provably fair solutions to everyday problems; and Robovote.org, which provides optimization-driven voting methods. Throughout the talk, I will devote special attention to the theoretical foundations and results that make these services possible.
University of Washington CS Colloquium, March 2018
Technological advances have changed every aspect of our lives in recent decades, yet, for the most part, the same systems of democratic decision making have been in place for centuries. I will argue that computer scientists can help rethink the practice of democracy, as well as its potential applications. I will focus on three emerging paradigms that go far beyond your run-of-the-mill election: (i) liquid democracy, an approach that allows voters to transitively delegate their votes; (ii) participatory budgeting, whereby residents collectively decide how to spend their local government's budget; and (iii) virtual democracy, which employs instant elections among machine learning models of real voters to address the grand AI challenge of ethical decision making.