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AI incidents, audits, and the limits of benchmarks
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Daniel Whitenack and Chris Benson

· 43 Minutes

PodcastPractical AI

AI incidents, audits, and the limits of benchmarks

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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

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Original source

This story was published by Practical AI and written by Daniel Whitenack and Chris Benson. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on share.transistor.fm

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