The
governance brief

Weekly conversations with AI governance practitioners, regulators, and industry leaders.

Ep. 1238 min

Why the EU AI Act changes everything

Guest: Dr. Marta Lindqvist, former EU AI Board advisor

An inside look at how the EU AI Act moved from policy paper to enforceable law. Dr. Lindqvist breaks down the political dynamics, the compromises that shaped Annex III, and what enforcement will actually look like when auditors start knocking on doors.

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Ep. 1142 min

Shadow AI in the enterprise

Guest: Raj Patel, CISO at a Fortune 500 insurer

Raj shares how his security team discovered hundreds of unsanctioned AI tools across the organization, the triage framework they built to assess risk, and why blocking access entirely backfired. Practical lessons for any enterprise security leader.

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Ep. 1035 min

Governing autonomous agents

Guest: Dr. Aisha Okonkwo, AI safety researcher

As AI agents gain the ability to take actions without human approval, governance frameworks need to evolve. Dr. Okonkwo explains progressive autonomy controls, kill switch design, and why traditional model cards fall short for agentic systems.

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Ep. 930 min

Bias audits that actually work

Guest: Camille Fournier, ML fairness lead at a major bank

Most bias audits are compliance theater. Camille walks through the methodology her team uses to detect proxy discrimination in credit models, how they handle intersectional fairness, and the tooling gaps that still need solving.

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Ep. 844 min

The compliance officer's AI playbook

Guest: Michael Torres, Chief Compliance Officer

Michael spent two decades in financial services compliance before AI arrived. He shares how compliance teams can upskill, which frameworks actually map to AI risk, and why the biggest governance failures come from organizational silos rather than technical gaps.

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Ep. 737 min

Red-teaming AI before regulators do

Guest: Lena Richter, adversarial ML engineer

Lena runs red-team exercises against production AI systems for a living. She explains how prompt injection, data poisoning, and model extraction attacks work in practice, and why organizations that test themselves proactively fare better when regulators investigate.

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