Career: Information, Algorithms, and Learning

The career development plan proposed here is based on three lines of research at the intersection of economic theory and computer science. The first project, “Information Design for Algorithms: Accuracy and Fairness” proposes a theoretical study of how to balance accuracy and fairness when consequential decisions (such as who should receive a loan or bail) are automated. The second project, “The Restrictiveness and Transferability of Economic Models” proposes new measures for evaluating economic models. The proposed measure of restrictiveness tells us whether a model fits available data because it precisely identifies regularities in that data, or because it is so flexible it can fit any data at all. The proposed measure of transferability tells us how a model estimated on data from one domain would perform on data drawn from a new (but related) domain. The final project, “Self-Censorship and Social Media,” proposes a model of information flow on social media platforms when the social norms that govern acceptable expression are in flux. This project focuses on characterizing when and how expressed views systematically differ from the true distribution of opinions.