Our current machine learning (ML) models achieve impressive performance on many benchmark tasks. Yet, these models remain remarkably brittle, susceptible to manipulation and, more broadly, often behave in ways that are unpredictable to users. Why is this the case? In this talk by Aleksander Madry, Professor of Computer Science, Massachusetts Institute of Technology, we identify human-ML misalignment as a chief cause of this behavior.