This recording with Andrew Trask is from the Foresight Institute Secure AI seminar series, hosted in April 2026. Andrew Trask is the founder of OpenMined and creator of PySyft, one of the most widely used frameworks for privacy-preserving machine learning. He has spent the last decade building technical infrastructure that allows AI systems to train on sensitive data without exposing it.
In this talk, Andrew makes the case that the field has developed a powerful set of privacy and security tools, including federated learning, homomorphic encryption, and differential privacy, and that the moment has arrived to move from research to real-world deployment. To see the slides that go along with this presentation, see the recording on YouTube.
If you want to join future seminars live, the schedule is at foresight.org and in our Luma calendar.
","author_name":"Foresight Institute"}