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7 episodes

The Road to Accountable AI

by Kevin Werbach · English

BusinessTechnology

Artificial intelligence is changing business, and the world. How can you navigate through the hype to understand AI's true potential, and the ways it can be implemented effectively, responsibly, and safely? Wharton Professor and Chair of Legal Studies and Business Ethics Kevin Werbach has analyzed emerging technologies for thirty years, and created one of the first business school course on legal and ethical considerations of AI in 2016. He interviews the experts and executives building accountable AI systems in the real world, today.

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Hamilton Mann: Separating the Powers of AI

Accountable AI through “separating the powers” framework (legislative, executive, judicial) applied to algorithmic systems; argues AI needs integrity beyond alignment, plus governance that prevents…

12 Nov 2026 · 37m · 10 chapters

Dave Trier (ModelOp): Turning AI Policies into Workflows

Accountable enterprise AI governance—how Model Op turns lengthy corporate AI policies into automated, auditable workflows, including risk tiering, testing, and controls down to cloud accounts and the…

5 Nov 2026 · 34m · 15 chapters

Lawrence Snapp (TrustScale): Fighting AI Hallucination

Accountable AI assurance to fight LLM hallucinations by verifying AI outputs against evidence, creating rubrics/evals across the AI value chain, and adding “hallucination firewall” controls analogous…

29 Oct 2026 · 33m · 17 chapters

Joshua Tan (Current AI): The Honda Civic Model of AI

Accountable AI via “public AI” and governance lessons from DAOs/collective intelligence, arguing AI should be treated like public infrastructure rather than only a corporate product.

22 Oct 2026 · 37m · 15 chapters

Brett Levenson (Moonbounce): The Best AI Security System is the One People Will Use

Accountable AI security—Moonbounce’s “semantic firewall” that enforces a company’s policies in real time by decomposing rules into atomic yes/no questions (“info-first”) and maintaining adaptive,…

15 Oct 2026 · 39m · 11 chapters

Sharon Goldman (Ground Level AI): AI as It Meets the Real World

AI as it reaches the real world—accountability, trust, cybersecurity, AI infrastructure (especially data centers), and how to explain these issues to non-technical audiences.

8 Oct 2026 · 33m · 15 chapters

Robert Levitan (Ethical Tech Project): Unlimited Intelligence, But Where's the Wisdom?

Accountable AI governance—why companies should start now, using guardrails and AI governance plans to prevent harms, maintain trust, and reduce legal/regulatory and litigation risk.

1 Oct 2026 · 37m · 16 chapters

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