UNESCO’s Hands-On AI Supervision

by UNESCO

UNESCO’s Hands-On AI Supervision: Lessons from Practice is a six-episode mini podcast series showcasing concrete lessons from the 2nd Expert Roundtable on AI Supervision, convened by UNESCO. Each episode distils insights from hands-on exercises with leading experts on AI risk mapping, evaluations, red teaming, benchmarking, cybersecurity, and engagement with market actors. Designed for regulators, policymakers, and practitioners, the series explores practical methodologies, emerging challenges, and the institutional capacities needed for effective AI oversight. Through focused conversations with specialists, the series provides accessible, actionable knowledge to strengthen technical readiness and foster ongoing dialogue across the global AI supervision community. Hosted on Ausha. See ausha.co/privacy-policy for more information.

Latest episodes

Showing 6 · updated from the feed

Dialogue with Market Actors: Cooperation for Better AI Oversight

Supervision cannot succeed without structured engagement with developers, deployers, and industry partners. In this episode, Huub Jannsen discusses best practices for mar

Mar 10
27 min

Cybersecurity for AI Supervision: Protecting Systems, Data, and Institutions

As AI systems introduce new attack surfaces, cybersecurity becomes a foundational element of oversight. Carlos Antunes outlines key threat vectors, resilience strategies,

Mar 3
33 min

Red Teaming as a Supervisory Tool: Stress-Testing AI Systems

Red teaming is rapidly becoming a critical component of AI oversight. In this episode, Rumman Chowdhury explains how structured adversarial testing can uncover system vul

Feb 24
27 min

Evaluating AI Systems: Metrics, Methods, and Measurement Gaps

A deep dive into the metrics and methodologies essential for robust AI evaluations. Agnès Delaborde examines measurement challenges, standards alignment, and the tools su

Feb 17
33 min

Mapping AI Risks: From Principles to Practice

This episode explores how supervisory authorities can translate high-level AI risk principles into practical, operational risk-mapping processes. Nathalie Cohen discusses

Feb 10
36 min

AI Safety & Benchmarking: Building Trustworthy Evaluation Ecosystems

Effective AI supervision requires reliable benchmarking ecosystems. Nicholas Miailhe discusses why benchmarks matter, how they should be constructed, and what regulators

Feb 1
34 min

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#128 NEW Social Sciences US

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