Psychology has traditionally been a laboratory discipline, focused on small-scale experiments conducted in person. However, recent technological innovations have made it possible to collect far more data from far more people than ever before. In this talk, I will explore some of the consequences of being able to conduct psychological research at a larger scale, highlighting some of the tools that we have developed for doing so. In particular, I will focus on three recent projects exploring aspects of human decision-making. The first uses a platform for large-scale interactive behavioral simulations to study how social transmission affects motivated reasoning. The second uses machine learning in conjunction with cognitive models to develop better predictive models of human choice. The third explores how we can use machine learning as a tool for developing better explanatory models for large scale datasets.