The most useful work in behavioral economics documents costly mistakes that people make in important settings and identifies ways to help them make better decisions. This dissertation presents four articles with those two goals in mind. In chapter one, co-authored with Yuji Winet, I examine perverse motivations people have in jury decisions and group decisions in general. In chapter two, I examine the efficiency of venture capital investing. In chapter three, co-authored with Amanda Agan, Jens Ludwig, and Sendhil Mullainathan, I examine how human biases interact with algorithmic biases in recommendation systems. In chapter four, I explore how police officers use algorithms for informative and performative purposes.