Dawn Song

In this engaging conversation, Dr. Dawn Song, a computer science professor and MacArthur Fellow, dives into the world of agentic AI and its implications for security and privacy. She discusses her transition from physics to security, the impact of prestigious awards on her research freedom, and the mission of the Berkeley Center for Responsible Decentralized Intelligence. Dawn emphasizes the challenges of securing AI agents, the risks of complex systems, and her personal journey building custom agents for increased productivity.

Dawn Song, a UC Berkeley professor specializing in security and machine learning, discusses crucial topics like the vulnerabilities in software and the risks posed by human error. She delves into adversarial machine learning, revealing its implications for autonomous vehicles and the need for enhanced defenses. Privacy concerns and data ownership dynamics are highlighted, alongside emerging strategies like differential privacy. The conversation also touches on program synthesis and the journey from physics to computer science, emphasizing the beauty of both fields.

Award-winning professor and tech entrepreneur Dawn Song joins Jon Krohn to discuss Responsible Decentralized Intelligence. Topics include homomorphic encryption, differential privacy, multi-party computation, PrivateSQL, deep learning, federated learning, and the concept of a responsible data economy.