{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Practical AI","title":"AI incidents, audits, and the limits of benchmarks","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/1b8e65f4\"></iframe>","width":"100%","height":180,"duration":2572,"description":"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.\nFeaturing:\nSean McGregor– LinkedIn\nChris Benson – Website, LinkedIn, Bluesky, GitHub, X\nDaniel Whitenack – Website, GitHub, X\nLinks:\nAI Verification & Evaluation Research Institute\nAI Incident Database\n38th convening of IAAI\nBenchRisk\nState of Global AI Incident Reporting\nUpcoming Events: \nRegister for upcoming webinars here!","thumbnail_url":"https://img.transistorcdn.com/Ox7ZlyiQOhdDa4Qy1MnJH5WFoksAetrzb40Jo1pePFs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8wMTZi/ZWJmNWIwNDdmYTcw/NGJjMTExZjNjZmYy/M2ZjNS5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}