In the perfect world of economic models, investors make perfectly rational decisions using perfect information and earn the best possible returns. They never get distracted or confused. Of course, in real life it doesn’t always work that way. Investors can get bamboozled by management drivel, or besotted with charismatic founders. What if we could use AI to make better investment decisions? In this episode of the Chicago Booth Review podcast, we explore how researchers are using machine-learning models to improve how investors allocate their funds.