Decisions and Algorithms

This class is intended for graduate students interested in getting an advanced understanding of judgments and decisions made with predictive algorithms. We will first survey the vast literature on the psychology of how people arrive at judgments and make decisions with the help of statistical information, focused mostly on experimental lab evidence from cognitive and social psychology. Then we will study the burgeoning evidence on how people use statistical algorithms in practice, exploring field evidence from a range of settings from criminal justice and healthcare to housing and labor markets. We will pay special attention to psychological principles that impact the effectiveness and fairness of algorithms deployed at scale. The primary aim is to help students understand systematic human errors and explore potential algorithmic solutions.