UNESCO
UNESCO’s Hands-On AI Supervision
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 wi...
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Episodes
Dialogue with Market Actors: Cooperation for Better AI Oversight 10.03.2026 27:19
Supervision cannot succeed without structured engagement with developers, deployers, and industry partners. In this episode, Huub Jannsen discusses best practices for market dialogue, transparency expectations, and collaborative mechanisms that support compliance while fostering innovation. The episode highlights how oversight bodies can build trust and shared responsibility across the AI ecosyste...
Cybersecurity for AI Supervision: Protecting Systems, Data, and Institutions 03.03.2026 33:41
As AI systems introduce new attack surfaces, cybersecurity becomes a foundational element of oversight. Carlos Antunes outlines key threat vectors, resilience strategies, and practical measures supervisory authorities can implement. This episode gives listeners a clear roadmap for integrating cybersecurity considerations into AI supervision workflows. Speaker: Carlos Antunes (Portugal National Cyb...
Red Teaming as a Supervisory Tool: Stress-Testing AI Systems 24.02.2026 27:04
Red teaming is rapidly becoming a critical component of AI oversight. In this episode, Rumman Chowdhury explains how structured adversarial testing can uncover system vulnerabilities, model failures, and misuse pathways. The discussion focuses on practical red-teaming approaches that supervisory authorities can adopt, even with limited resources. Speaker: Rumman Chowdhury (Human Intelligence) Inte...
Evaluating AI Systems: Metrics, Methods, and Measurement Gaps 17.02.2026 33:08
A deep dive into the metrics and methodologies essential for robust AI evaluations. Agnès Delaborde examines measurement challenges, standards alignment, and the tools supervisory authorities need to assess AI system performance. The conversation highlights gaps between emerging benchmarks and real-world regulatory needs. Speaker: Agnès Delaborde (Laboratoire national de métrologie et d'essais – L...
Mapping AI Risks: From Principles to Practice 10.02.2026 36:20
This episode explores how supervisory authorities can translate high-level AI risk principles into practical, operational risk-mapping processes. Nathalie Cohen discusses evaluation frameworks, data considerations, and real-world challenges identified during the roundtable exercise, providing regulators with concrete steps for structuring risk identification and prioritisation. Speaker: Nathalie C...
AI Safety & Benchmarking: Building Trustworthy Evaluation Ecosystems 01.02.2026 34:32
Effective AI supervision requires reliable benchmarking ecosystems. Nicholas Miailhe discusses why benchmarks matter, how they should be constructed, and what regulators need to know about safety evaluations. The conversation highlights emerging international efforts to standardise safety testing and ensure comparability across models. Speaker: Nicholas Miailhe (PRISM Eval) Interviewer: Doaa Abu E...
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