Casey Mulligan, professor of economics at the University of Chicago, reviews how technology can assist not only with pure data analysis but the theoretical reasoning useful for guiding such analysis. He describes processes for automated reasoning emerging from real algebraic geometry that are helpful in economics, sociology, and political science. His talk centers on the size and complexity of problems that can be processed in this way, and how to assess machine-made errors.
Insight·Feb 16, 2017