There are few technology areas more important than the intersection of AI and cybersecurity in 2025.  For AI to deliver on its promised value of autonomously solving manual tasks, we must ensure it behaves securely.  And for AI to improve our cybersecurity, we’ll need to identify where AI-driven forms of automation add value even as AI capabilities growth makes answering this a moving target.

How do we succeed?  In this talk, I’ll lay out what I see as the core open questions in the field and give opinionated answers:

• How do we render non-deterministic, uninterpretable deep neural networks trustworthy enough that we can rely on them as virtual colleagues and assistants?
• Where are the most lucrative areas in security to which we should apply large language models, inference scaling laws, and reinforcement learning?
• Which artifacts are most important for frontier AI companies to defend as we pursue the AI race, and what’s the role for the open source and open science culture that’s led to the foundational ideas driving progress in our field today?

After giving a perspective on these questions based in my experience leading AI security work at Meta, I’ll discuss the role of the cybersecurity community in answering them.