Privacy-Preserving Decentralized Data Science with Andrew Trask

Today we're joined by Andrew Trask, PhD student at the University of Oxford and Leader of the OpenMined Project. OpenMined is an open-source community focused on researching, developing, and promoting tools for secure, privacy-preserving, value-aligned artificial intelligence. Andrew and I caught up back at NeurIPS to dig into why OpenMined is important and explore some of the basic research and technologies supporting Private, Decentralized Data Science. We touch on ideas such as Differential Privacy, and Secure Multi-Party Computation, and how these ideas come into play in, for example, federated learning.