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PODCAST

The Road to Accountable AI

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

technology

All Episodes

33:54

Blake Hall: Safeguarding Identity in the AI Era

The Road to Accountable AI ·

2025/12/11

In this episode, Blake Hall, CEO of ID.me, discusses the massive escalation in online fraud driven by generative AI, noting that attacks have evolved from "Nigerian prince" scams to sophisticated, scalable social engineering campaigns that threaten even the most digital-savvy users. He explains that traditional knowledge-based verification methods are now obsolete due to data breaches, shifting the security battleground to biometric and possession-based verification. Hall details how his company

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32:04

Mitch Kapor: AI Gap-Closing

The Road to Accountable AI ·

2025/12/04

Legendary entrepreneur and investor Mitch Kapor draws on his decades of experience to argue that while AI represents a massive wave of disruptive innovation, it also represents an opportunity to avoid mistakes made with social media and the early internet. In this episode, he contends that technologists tend toward over-optimism about technology solving human problems while underestimating downsides. Self-regulation by large AI companies like OpenAI and Anthropic is likely to fail, he suggests,

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34:56

Brad Carson: Sharing AI's Bounty

The Road to Accountable AI ·

2025/11/20

Former Congressman and Pentagon official Brad Carson discusses his organization, Americans for Responsible Innovation (ARI), which seeks to bridge the gap between immediate AI harms like and catastrophic safety risks, while bringing deep Capitol Hill expertise to the AI conversation . He argues that unlike previous innovations such as electricity or the automobile, AI has been deeply unpopular with the public from the start, creating a rare bipartisan alignment among those skeptical of its

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36:03

Oliver Patel: Sharing Frameworks for AI Governance

The Road to Accountable AI ·

2025/11/13

Oliver Patel has built a sizeable online following for his social media posts and Substack about enterprise AI governance, using clever acronyms and visual frameworks to distill down insights based on his experience at AstraZeneca, a major global pharmaceutical company. In this episode, he details his career journey from academic theory to government policy and now practical application, and offers insights for those new to the field. He argues that effective enterprise AI governance requires being

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33:55

Ravit Dotan: Rethinking AI Ethics

The Road to Accountable AI ·

2025/11/06

Ravit Dotan argues that the primary barrier to accountable AI is not a lack of ethical clarity, but organizational roadblocks. While companies often understand what they should do, the real challenge is organizational dynamics that prevent execution—AI ethics has been shunted into separate teams lacking power and resources, with incentive structures that discourage engineers from raising concerns. Drawing on work with organizational psychologists, she emphasizes that frameworks prescribe what

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33:55

Trey Causey: Is Responsble AI Failing?

The Road to Accountable AI ·

2025/10/30

Kevin Werbach speaks with Trey Causey about the precarious state of the responsible AI (RAI) field. Causey argues that while the mission is critical, the current organizational structures for many RAI teams are struggling. He highlights a fundamental conflict between business objectives and governance intentions, compounded by the fact that RAI teams' successes (preventing harm) are often invisible, while their failures are highly visible. Causey makes the case that for RAI teams to be effective,

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33:13

Caroline Louveaux: Trust is Mission Critical

The Road to Accountable AI ·

2025/10/23

Kevin Werbach speaks with Caroline Louveaux, Chief Privacy, AI, and Data Responsibility Officer at Mastercard, about what it means to make trust mission critical in the age of artificial intelligence. Caroline shares how Mastercard built its AI governance program long before the current AI boom, grounding it in the company’s Data and Technology Responsibility Principles”. She explains how privacy-by-design practices evolved into a single global AI governance framework aligned with the EU AI Act,

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33:28

Cameron Kerry: From Gridlock to Governance?

The Road to Accountable AI ·

2025/10/16

Cameron Kerry, Distinguished Visiting Fellow at the Brookings Institution and former Acting US Secretary of Commerce, joins Kevin Werbach to explore the evolving landscape of AI governance, privacy, and global coordination. Kerry emphasizes the need for agile and networked approaches to AI regulation that reflect the technology’s decentralized nature. He argues that effective oversight must be flexible enough to adapt to rapid innovation while grounded in clear baselines that can help organizations

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35:00

Derek Leben: All of Us are Going to Become Ethicists

The Road to Accountable AI ·

2025/10/09

Carnegie Mellon business ethics professor Derek Leben joins Kevin Werbach to trace how AI ethics evolved from an early focus on embodied systems—industrial robots, drones, self-driving cars—to today’s post-ChatGPT landscape that demands concrete, defensible recommendations for companies. Leben explains why fairness is now central: firms must decide which features are relevant to a task (e.g., lending or hiring) and reject those that are irrelevant—even if they’re predictive. Drawing on philosophers

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34:38

Heather Domin: From Principles to Practice

The Road to Accountable AI ·

2025/10/02

Kevin Werbach interviews Heather Domin, Global Head of the Office of Responsible AI and Governance at HCLTech. Domin reflects on her path into AI governance, including her pioneering work at IBM to establish foundational AI ethics practices. She discusses how the field has grown from a niche concern to a recognized profession, and the importance of building cross-functional teams that bring together technologists, lawyers, and compliance experts. Domin emphasizes the advances in governance tools,

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37:57

Dean Ball: The World is Going to Be Totally Different...

The Road to Accountable AI ·

2025/09/25

Kevin Werbach interviews Dean Ball, Senior Fellow at the Foundation for American Innovation and one of the key shapers of the Trump Administration's approach to AI policy. Ball reflects on his career path from writing and blogging to shaping federal policy, including his role as Senior Policy Advisor for AI and Emerging Technology at the White House Office of Science and Technology Policy, where he was the primary drafter of the Trump Administration's recent AI Action Plan. He explains how he has

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36:35

David Hardoon: You Can't Outsource Accountability

The Road to Accountable AI ·

2025/09/18

Kevin Werbach interviews David Hardoon, Global Head of AI Enablement at Standard Chartered Bank and former Chief Data Officer of the Monetary Authority of Singapore (MAS), about the evolving practice of responsible AI. Hardoon reflects on his perspective straddling both government and private-sector leadership roles, from designing the landmark FEAT principles at MAS to embedding AI enablement inside global financial institutions. Hardoon explains the importance of justifiability, a concept he sees

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30:08

Karine Perset: Building Bridges for Global AI Governance

The Road to Accountable AI ·

2025/09/11

Kevin Werbach interviews Karine Perset, Acting Head of the OECD’s AI and Emerging Technology Division, about the global effort to shape responsible AI. Perset explains how the OECD—an intergovernmental organization with 38 member countries—has become a central forum for governments to cooperate on complex, interdependent challenges like AI. Since launching its AI foresight forum in 2016, the OECD has spearheaded two cornerstone initiatives: the OECD Recommendation on AI, the first intergovernmental

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42:50

DJ Patil: AI's Steering Wheel Challenge

The Road to Accountable AI ·

2025/09/04

Kevin Werbach interviews DJ Patil, the first U.S. Chief Data Scientist under the Obama Administration, about the evolving role of AI in government, healthcare, and business. Patil reflects on how the mission of government data leadership has grown more critical today: ensuring good data, using it responsibly, and unleashing its power for public benefit. He describes both the promise and the paralysis of today’s “big data” era, where dashboards abound, but decision-making often stalls. He highlights

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29:32

Kay Firth-Butterfield: Using AI Wisely

The Road to Accountable AI ·

2025/06/26

Kevin Werbach interviews Kay Firth-Butterfield about how responsible AI has evolved from a niche concern to a global movement. As the world’s first Chief AI Ethics Officer and former Head of AI at the World Economic Forum, Firth-Butterfield brings deep experience aligning AI with human values. She reflects on the early days of responsible AI—when the field was dominated by philosophical debates—to today, when regulation such as the European Union's AI Act is defining the rules of the road.

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39:33

Dale Cendali: How Courts (and Maybe Congress!) Will...

The Road to Accountable AI ·

2025/06/19

Kevin Werbach interviews Dale Cendali, one of the country’s leading intellectual property (IP) attorneys, to discuss how courts are grappling with copyright questions in the age of generative AI. Over 30 lP awsuits already filed against major generative AI firms, and the outcomes may shape the future of AI as well as creative industries. While we couldn't discuss specifics of one of the most talked-about cases, Thomson Reuters v. ROSS -- because Cendali is litigating it on behalf of Thomson Reuters

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36:52

Brenda Leong: Building AI Law Amid Legal Uncertainty

The Road to Accountable AI ·

2025/06/12

Kevin Werbach interviews Brenda Leong, Director of the AI division at boutique technology law firm ZwillGen, to explore how legal practitioners are adapting to the rapidly evolving landscape of artificial intelligence. Leong explains why meaningful AI audits require deep collaboration between lawyers and data scientists, arguing that legal systems have not kept pace with the speed and complexity of technological change. Drawing on her experience at Luminos.Law—one of the first AI-specialist

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37:00

Shameek Kundu: AI Testing and the Quest for Boring...

The Road to Accountable AI ·

2025/06/05

Kevin Werbach interviews Shameek Kundu, Executive Director of AI Verify Foundation, to explore how organizations can ensure AI systems work reliably in real-world contexts. AI Verify, a government-backed nonprofit in Singapore, aims to build scalable, practical testing frameworks to support trustworthy AI adoption. Kundu emphasizes that testing should go beyond models to include entire applications, accounting for their specific environments, risks, and data quality. He draws on lessons from AI

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32:44

Uthman Ali: Responsible AI in a Safety Culture

The Road to Accountable AI ·

2025/05/29

Host Kevin Werbach interviews Uthman Ali, Global Responsible AI Officer at BP, to delve into the complexities of implementing responsible AI practices within a global energy company. Ali emphasizes how the culture of safety in the industry influences BP's willingness to engage in AI governance. He discusses the necessity of embedding ethical AI principles across all levels of the organization, emphasizing tailored training programs for various employee roles—from casual AI users to data

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35:26

Karen Hao: Is Imperial AI Inevitable?

The Road to Accountable AI ·

2025/05/22

Kevin Werbach interviews journalist and author Karen Hao about her new book Empire of AI, which chronicles the rise of OpenAI and the broader implications of generative artificial intelligence. Hao reflects on how the ethical challenges of AI have evolved, noting the shift from concerns like data privacy and algorithmic bias to more complex issues such as intellectual property violations, environmental impact, misleading user experiences, and concentration of power. She emphasizes that while some

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