His research explores ethical and policy issues in AI, particularly fairness in machine learning, methods for bringing accountability to automated decision-making, and the privacy implications of inference. In 2014, Barocas co-founded Fairness, Accountability, and Transparency in Machine Learning (FAT/ML), an annual event that brings together an emerging community of researchers working on these issues. He was previously a postdoctoral researcher in the New York City lab of Microsoft Research, where he was a member of the fairness, accountability, transparency, and ethics in AI group, as well as a postdoctoral research associate at the Center for Information Technology Policy at Princeton University. He completed his doctorate in the Department of Media, Culture, and Communication at New York University, where he remains an affiliate of the Information Law Institute.