UC Berkeley

Machine learning (ML) systems are rapidly increasing in size, are acquiring new capabilities, and are increasingly deployed in high-stakes settings. To address the growing need for safe ML systems, I first discuss works towards making systems perform reliably. Thereafter I discuss works towards making systems act in accordance with human values. In closing I discuss open problems in making ML systems safer.