World Model · podcast knowledge graph

AI incidents, audits, and the limits of benchmarks

2026-02-13 · 43 min · episode 346 · 6 entities

episode page audio

Asserted relationships

  • → hosted by Daniel Whitenack and Chris Benson person
    0.55
    evidence rules-v5
    Feed author/publisher: Daniel Whitenack and Chris Benson
  • → discusses Technology company
    0.40
    evidence rules-v5
    Feed category: Technology
  • → hosted by Practical AI LLC company
    0.40
    evidence rules-v5
    Feed author/publisher: Practical AI LLC

Entities found in this episode

companys 4

  • mentioned Practical AI LLC company
    0.70
    evidence rules-v5
    Feed author/publisher: Practical AI LLC
  • mentioned Technology company
    0.50
    evidence rules-v5
    Feed category: Technology
  • discusses Technology company
    0.40
    evidence rules-v5
    Feed category: Technology
  • hosted by Practical AI LLC company
    0.40
    evidence rules-v5
    Feed author/publisher: Practical AI LLC

persons 2

Episode description as stored
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 !