Lukas Althoff

This intensive two-week workshop helps PhD students advance their own social science research with AI. Lectures, demos, and pair programming sessions alongside peers introduce students to new methods. Lectures include guest talks from researchers at Stanford, frontier AI labs, and think tanks. Students spend the days on their own projects. Throughout, we consider how to design workflows for effective human-AI collaboration, what to delegate, where human judgment matters, and how to design robust verification practices.

Progress and inequality are intertwined throughout human history. This course traces both from the Neolithic Revolution to the AI era, asking: What causes progress? Who benefits? And what can we learn for the future? Topics range from the engines of progress—resources, cities, knowledge, institutions—to the barriers that determine who is left behind, including race, gender, and intergenerational mobility.

This graduate course emphasizes theoretical and empirical methods for studying long-run economic change, with a focus on the forces that drive progress and the barriers that prevent it from being broadly shared. Drawing on historical evidence and economic analysis, we investigate how societies have generated — and distributed — economic opportunity, and what lessons the past provides for the future. While the evidence will span various periods of American history, the course will not cover those periods chronologically but rather focus on critical analysis of specific questions and mechanisms of change.