In this talk I present recent work on combining game theory, statistics, and control theory. This combination provides new techniques for predicting / controlling any system comprising humans, human groups (e.g., firms, tribes), and / or adaptive automated systems (e.g., reinforcement learning robots). As illustrations, I will focus on three projects: 1) Suppressing flutter in an airplane wing by controlling a set of autonomous micro-flaps at its trailing edge. 2) First raising taxes in a human economy, and then lowering them back to the starting values, to steer the economy to a Pareto superior equilibrium. 3) Designing a dynamic auction of arrival slots at a weather-impacted airport, to maximize social welfare.