Gary McGraw, cofounder of the Berryville Institute of Machine Learning, pointed to a core gap: Today’s benchmarks tend to measure how well AI systems can perform security tasks—not how secure the systems themselves are. Companies need to keep that distinction in mind when evaluating their tools and defenses.

McGraw warned as far back as 2019 that securing machine learning systems would be “one of the defining cybersecurity struggles of the next decade.” That moment has now arrived.

“These meetings are a way to remind ourselves of the fundamentals,” he said, “as we try to define what machine learning security actually is.”