AI incidents, audits, and the limits of benchmarks

AI is moving fast from research to real-world deployment, and when things go wrong, the consequences are no longer hypothetical. In this episode, Sean McGregor, co-founder of the AI Verification & Evaluation Research Institute and also the founder of the AI Incident Database, joins Chris and Dan to discuss AI safety, verification, evaluation, and auditing. They explore why benchmarks often fall short, what red-teaming at DEFCON reveals about machine learning risks, and how organizations can better assess and manage AI systems in practice. Featuring: Sean McGregor– LinkedIn Chris Benson – Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack – Website , GitHub , X Links: AI Verification & Evaluation Research Institute AI Incident Database 38th convening of IAAI BenchRisk State of Global AI Incident Reporting Upcoming Events: Register for upcoming webinars here !

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AI incidents, audits, and the limits of benchmarks is an episode from Practical AI by Changelog Media.

This episode is 42:52 long.

This episode was published on Feb 13, 2026.

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