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 uses advanced techniques—like analyzing light refraction on skin versus screens—to detect deepfakes, while emphasizing a "best of breed" approach that relies on government-tested vendors.

Beyond the threats, Hall outlines a positive vision for a digital wallet that functions as a user-controlled "digital twin," allowing individuals to share only necessary data (tokenized identity) rather than overexposing personal information. He argues that government agencies must play a stronger role in validating core identity attributes to stop synthetic fraud and suggests that future AI "agents" will rely on cryptographically signed credentials to act on our behalf securely. Ultimately, he advocates for a model where companies "sell trust, not data," empowering users to control their own digital identity across finance, healthcare, and government services.

Blake Hall is the Co-Founder and CEO of ID.me, a digital identity network with over 150 million members that simplifies how individuals prove and share their identity online. A former U.S. Army Ranger, Hall led a reconnaissance platoon in Iraq and was awarded two Bronze Stars, including one for valor, before earning his MBA from Harvard Business School. He has been recognized as CEO of the Year by One World Identity and an Entrepreneur of the Year by Ernst & Young for his work in pioneering secure, user-centric digital identity solutions.

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He Once Hunted Terrorists in Iraq. Now He Runs a $2 Billion Identity Verification Company (Inc., November 11, 2025)

"No Identity Left Behind": How Identity Verification Can Improve Digital Equity (ID.me)

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, because incentives to aggregate power and wealth are too strong, requiring external pressure and oversight. Kapor explains that his responsible investing approach at his venture capital firm, Kapor Capital, focuses on gap-closing rather than diversity for its own sake, funding startups that address structural inequalities in access, opportunity, or outcomes, regardless of founder demographics. He discusses the Humanity AI initiative and argues that philanthropy needs to develop AI literacy and technical capacity, with some foundations hiring chief technology officers to effectively engage with these issues. He believes targeted interventions can create meaningful change without matching the massive investments of the major AI labs. Kapor expresses hope that a younger generation of leaders in tech and philanthropy can step up to make positive differences, emphasizing that his generation should empower them rather than occupying seats at the table.

Mitch Kapor is a pioneering technology entrepreneur, investor, and philanthropist who founded Lotus Development Corporation and created Lotus 1-2-3, the breakthrough spreadsheet software that helped establish the PC software industry in the 1980s. He co-founded the Electronic Frontier Foundation to advocate for digital rights and civil liberties, and later established Kapor Capital with his wife Freada Kapor Klein to invest in startups that close gaps of access, opportunity, and outcome for underrepresented communities. Kapor recently completed a masters degree at the MIT Sloan School focused on gap-closing investing, returning to finish what he started 45 years earlier when he left MIT to pursue his career in Silicon Valley. He serves on the steering committee of Humanity AI, a $500 million initiative to ensure AI benefits society broadly.

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 power and impacts. This creates openings for productive discussions about AI policy. Drawing on his military experience, Carson suggests that while AI will shorten the kill chain, it won't fundamentally change the human nature of warfare, and he warns against the US military's tendency to seek technical solutions to human problems . The conversation covers current policy debates, highlighting the necessity of regulating the design of models rather than just their deployment, and the importance of export controls to maintain the West's advantage in compute . Ultimately, Carson emphasizes that for AI to succeed politically, the "bounty" of this technology must be shared broadly to avoid tearing apart the social fabric

Brad Carson is the founder and president of Americans for Responsible Innovation (ARI), an organization dedicated to lobbying for policy that ensures artificial intelligence benefits the public interest. A former Rhodes Scholar, Carson has had a diverse career in public service, having served as a U.S. Congressman from Oklahoma, the Undersecretary of the Army, and the acting Undersecretary of Defense for Personnel and Readiness . He also served as a university president and deployed to Iraq in 2008 .

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Former TU President Brad Carson Pushes for Strong AI Guardrails

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 pragmatic and picking your battles, since the role isn't to stop AI adoption but to enable organizations to adopt it safely and responsibly at speed and scale. He notes that core pillars of modern AI governance, such as AI literacy, risk classification, and maintaining an AI inventory, are incorporated into the EU AI Act and thus essential for compliance. Looking forward, Patel identifies AI democratization—how to govern AI when everyone in the workforce can use and build it—as the biggest hurdle, and offers thougths about how enteprises can respond.

Oliver Patel is the Head of Enterprise AI Governance at AstraZeneca. Before moving into the corporate sector, he worked for the UK government as Head of Inbound Data Flows, where he focused on data policy and international data transfers, and was a researcher at University College London. He serves as an IAPP Faculty Member and a member of the OECD's Expert Group on AI Risk. His forthcoming book, Fundamentals of AI Governance, will be released in early 2026.

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Enterprise AI Governance Substack

Top 10 Challenges for AI Governance Leaders in 2025 (Part 1)

Fundamentals of AI Governance book page

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 systems companies should have but ignore how to navigate organizational realities. The key insight: responsible AI can't be a separate compliance exercise but must be embedded organically into how people work. Ravit discusses a recent shift in her orientation from focusing solely on governance frameworks to teaching people how to use AI thoughtfully. She critiques "take-out mode" where users passively order finished outputs, which undermines skills and critical review. The solution isn't just better governance, but teaching workers how to incorporate responsible AI practices into their actual workflows.

Dr. Ravit Dotan is the founder and CEO of TechBetter, an AI ethics consulting firm, and Director of the Collaborative AI Responsibility (CAIR) Lab at the University of Pittsburgh. She holds a Ph.D. in Philosophy from UC Berkeley and has been named one of the "100 Brilliant Women in AI Ethics" (2023), and was a finalist for "Responsible AI Leader of the Year" (2025). Since 2021, she has consulted with tech companies, investors, and local governments on responsible AI. Her recent work emphasizes teaching people to use AI thoughtfully while maintaining their agency and skills. Her work has been featured in The New York Times, CNBC, Financial Times, and TechCrunch.

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My New Path in AI Ethics (October 2025)

The Values Encoded in Machine Learning Research (FAccT 2022 Distinguished Paper Award) -

Responsible AI Maturity Framework

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, they must possess deep technical competence to build solutions and gain credibility with engineering teams. He also explores the idea of "epistemic overreach," where RAI groups have been tasked with an impossibly broad mandate they lack the product-market fit to fulfill. Drawing on his experience in the highly regulated employment sector at Indeed, he details the rigorous, science-based approach his team took to defining and measuring bias, emphasizing the need to move beyond simple heuristics and partner with legal and product teams before analysis even begins.

Trey Causey is a data scientist who most recently served as the Head of Responsible AI for Indeed. His background is in computational sociology, where he used natural language processing to answer social questions.

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Responsible Ai Is Dying. Long Live Responsible AI

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, NIST AI Risk Management, and standards.

The conversation explores how Mastercard balances innovation speed with risk management, automates low-risk assessments, and maintains executive oversight through its AI Governance Council. Caroline also discusses the company's work on agentic commerce, where autonomous AI agents can initiate payments, and why trust, certification, and transparency are essential for such systems to succeed. Caroline unpacks what it takes for a global organization to innovate responsibly — from cross-functional governance and "tone from the top," to partnerships like the Data & Trust Alliance and efforts to harmonize global standards. Caroline emphasizes that responsible AI is a shared responsibility and that companies that can "innovate fast, at scale, but also do so responsibly" will be the ones that thrive.

Caroline Louveaux leads Mastercard's global privacy and data responsibility strategy. She has been instrumental in building Mastercard's AI governance framework and shaping global policy discussions on data and technology. She serves on the board of the International Association of Privacy Professionals (IAPP), the WEF Task Force on Data Intermediaries, the ENISA Working Group on AI Cybersecurity, and the IEEE AI Systems Risk and Impact Executive Committee, among other activities.

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How Mastercard Uses AI Strategically: A Case Study (Forbes 2024)

Lessons From a Pioneer: Mastercard's Experience of AI Governance (IMD, 2023)

As AI Agents Gain Autonomy, Trust Becomes the New Currency. Mastercard Wants to Power Both. (Business Insider, July 2025)

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 and governments learn together. Kerry revisits his long-standing push for comprehensive U.S. privacy legislation, lamenting the near-passage of the 2022 federal privacy bill that was derailed by partisan roadblocks. Despite setbacks, he remains hopeful that bottom-up experimentation and shared best practices can guide responsible AI use, even without sweeping laws.

Cameron F. Kerry is the Ann R. and Andrew H. Tisch Distinguished Visiting Fellow in Governance Studies at the Brookings Institution and a global thought leader on privacy, technology, and AI governance. He served as General Counsel and Acting Secretary of the U.S. Department of Commerce, where he led work on privacy frameworks and digital policy. A senior advisor to the Aspen Institute and board member of several policy initiatives, Kerry focuses on building transatlantic and global approaches to digital governance that balance innovation with accountability.

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What to Make of the Trump Administration's AI Action Plan (Brookings, July 31, 2025)

Network Architecture for Global AI Policy (Brookings, February 10, 2025)

How Privacy Legislation Can Help Address AI (Brookings, July 7, 2023)

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 such as John Rawls and Michael Sandel, he argues for objective judgments about a system's purpose and qualifications. Getting practical about testing for AI fairness, he distinguishes blunt outcome checks from better metrics, and highlights counterfactual tools that reveal whether a feature actually drives decisions. With regulations uncertain, he urges companies to treat ethics as navigation, not mere compliance: Make and explain principled choices (including how you mitigate models), accept that everything you do is controversial, and communicate trade-offs honestly to customers, investors, and regulators. In the end, Leben argues, we all must become ethicists to address the issues AI raises...whether we want to or not.

Derek Leben is Associate Teaching Professor of Ethics at the Tepper School of Business, Carnegie Mellon University, where he teaches courses such as "Ethics of Emerging Technologies," "Fairness in Business," and "Ethics & AI." Leben is the author of Ethics for Robots (Routledge, 2018) and AI Fairness (MIT Press, 2025). He founded the consulting group Ethical Algorithms, through which he advises governments and corporations on how to build fair, socially responsible frameworks for AI and autonomous

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AI Fairness: Designing Equal Opportunity Algorithms (MIT Press 2025)

Ethics for Robots: How to Design a Moral Algorithm (Routledge 2019)

The Ethical Challenges of AI Agents (Blog post, 2025)

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, bias testing, and automation that are helping developers and organizations keep pace with rapidly evolving AI systems. She describes her role at HCLTech, where client-facing projects across multiple industries and jurisdictions create unique governance challenges that require balancing company standards with client-specific risk frameworks. Domin notes that while most executives acknowledge the importance of responsible AI, few feel prepared to operationalize it. She emphasizes the growing demand for proof and accountability from regulators and courts, and finds the work exciting for its urgency and global impact. She also talks about the new chalenges of agentic AI, and the potential for "oversight agents" that use AI to govern AI.

Heather Domin is Global Head of the Office of Responsible AI and Governance at HCLTech and co-chair of the IAPP AI Governance Professional Certification. A former leader of IBM's AI ethics initiatives, she has helped shape global standards and practices in responsible AI. Named one of the Top 100 Brilliant Women in AI Ethics™ 2025, her work has been featured in Stanford executive education and outlets including CNBC, AI Today, Management Today, Computer Weekly, AI Journal, and the California Management Review.

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AI Governance in the Agentic Era

Implementing Responsible AI in the Generative Age - Study Between HCL Tech and MIT