Contextual Privacy in the Agentic Era (Virtual Talk)

We examine how privacy must evolve as AI systems become increasingly agentic and operate across diverse tasks, tools, and information flows. I will highlight two research directions: using reinforcement learning to instill contextual integrity in agents, and using agentic systems to synthesize new privacy-preserving algorithms on the fly. Together, these point toward a scalable view of privacy that is both context-sensitive at deployment time and adaptive at the level of mechanism design.