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 AI systems in the real world, today.
info_outline
Brad Carson: Sharing AI's Bounty
11/20/2025
Brad Carson: Sharing AI's Bounty
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 .
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/39081410
info_outline
Oliver Patel: Sharing Frameworks for AI Governance
11/13/2025
Oliver Patel: Sharing Frameworks for AI Governance
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.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38905455
info_outline
Ravit Dotan: Rethinking AI Ethics
11/06/2025
Ravit Dotan: Rethinking AI Ethics
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. (October 2025) (FAccT 2022 Distinguished Paper Award) -
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38815600
info_outline
Trey Causey: Is Responsble AI Failing?
10/30/2025
Trey Causey: Is Responsble AI Failing?
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.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38773935
info_outline
Caroline Louveaux: Trust is Mission Critical
10/23/2025
Caroline Louveaux: Trust is Mission Critical
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. (Forbes 2024) (IMD, 2023) (Business Insider, July 2025)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38577525
info_outline
Cameron Kerry: From Gridlock to Governance?
10/16/2025
Cameron Kerry: From Gridlock to Governance?
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. (Brookings, July 31, 2025) (Brookings, February 10, 2025) (Brookings, July 7, 2023)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38395850
info_outline
Derek Leben: All of Us are Going to Become Ethicists
10/09/2025
Derek Leben: All of Us are Going to Become Ethicists
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 (MIT Press 2025) (Routledge 2019) (Blog post, 2025)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38391755
info_outline
Heather Domin: From Principles to Practice
10/02/2025
Heather Domin: From Principles to Practice
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.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38409805
info_outline
Dean Ball: The World is Going to Be Totally Different in 10 Years
09/25/2025
Dean Ball: The World is Going to Be Totally Different in 10 Years
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 developed influence through a differentiated viewpoint: rejecting the notion that AI progress will plateau and emphasizing that transformative adoption is what will shape global competition. He critiques both the Biden administration’s “AI Bill of Rights” approach, which he views as symbolic and wasteful, and the European Union’s AI Act, which he argues imposes impossible compliance burdens on legacy software while failing to anticipate the generative AI revolution. By contrast, he describes the Trump administration’s AI Action Plan as focused on pragmatic measures under three pillars: innovation, infrastructure, and international security. Looking forward, he stresses that U.S. competitiveness depends less on being first to frontier models than on enabling widespread deployment of AI across the economy and government. Finally, Ball frames tort liability as an inevitable and underappreciated force in AI governance, one that will challenge companies as AI systems move from providing information to taking actions on users’ behalf. Dean Ball is a Senior Fellow at the Foundation for American Innovation, author of Hyperdimensional, and former Senior Policy Advisor at the White House OSTP. He has also held roles at the National Science Foundation, the Mercatus Center, and Fathom. His writing spans artificial intelligence, emerging technologies, bioengineering, infrastructure, public finance, and governance, with publications at institutions including Hoover, Carnegie, FAS, and American Compass. https://drive.google.com/file/d/1zLLOkndlN2UYuQe-9ZvZNLhiD3e2TPZS/view
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38344095
info_outline
David Hardoon: You Can't Outsource Accountability
09/18/2025
David Hardoon: You Can't Outsource Accountability
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 as distinct from ethics or accountability. Organizations must not only justify their AI use to themselves, but also to regulators and, ultimately, the public. At Standard Chartered, he focuses on integrating AI safety and AI talent into one discipline, arguing that governance is not a compliance burden but a driver of innovation and resilience. In the era of generative AI and black-box models, he stresses the need to train people in inquiry--interrogating outputs, cross-referencing, and, above all, exercising judgment. Hardoon concludes by reframing governance as a strategic advantage: not a cost center, but a revenue enabler. By embedding trust and transparency, organizations can create sustainable value while navigating the uncertainties of rapidly evolving AI risks. David Hardoon is the Global Head of AI Enbablement at Standard Chartered Bank with over 23 years of experience in Data and AI across government, finance, academia, and industry. He was previously the first Chief Data Officer at the Monetary Authority of Singapore, and CEO of Aboitiz Data Innovation. (2018) (Business Times, 2024) (Business Times, 2021)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/37929395
info_outline
Karine Perset: Building Bridges for Global AI Governance
09/11/2025
Karine Perset: Building Bridges for Global AI Governance
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 standard adopted in 2019, and OECD.AI, a policy observatory that tracks global trends, policies, and metrics. Perset highlights the organization’s unique role in convening evidence-based dialogue across governments, experts, and stakeholders worldwide. She describes the challenge of reconciling diverse national approaches while developing common tools, like a global incident-reporting framework and over 250 indicators that measure AI maturity across investment, research, infrastructure, and workforce skills. She underscores both the urgency and the opportunity: AI systems are diffusing rapidly across all sectors, powered by common algorithms that create shared risks. Without aligned safeguards and interoperable standards, countries risk repeating one another’s mistakes. Yet if governments can coordinate, share data responsibly, and support one another’s policy development, AI can strengthen economic resilience, innovation, and public trust. Karine Perset is the Acting Head of the OECD AI and Emerging Digital Technologies Division, where she oversees the OECD.AI Policy Observatory, the Global Partnership on AI (GPAI) & integrated network of experts as well as the OECD Global Forum on Emerging Technologies. She oversees the development of analysis, policies and tools inline with the OECD AI Principles. She also helps governments manage the opportunities and challenges that AI and emerging technologies raise for governments. Previously she was Advisor to ICANN’s Governmental Advisory Committee and Counsellor of the OECD’s Science, Technology and Industry Director.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/38056775
info_outline
DJ Patil: AI's Steering Wheel Challenge
09/04/2025
DJ Patil: AI's Steering Wheel Challenge
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 the untapped potential of federal datasets, such as the VA’s Million Veterans Project, which could accelerate cures for major diseases if unlocked. Yet funding gaps, bureaucratic resistance, and misalignment with Congress continue to stand in the way. Turning to AI, Patil describes a landscape of extraordinary progress: tools that help patients ask the right questions of their physicians, innovations that enhance customer service, and a wave of entrepreneurial energy transforming industries. At the same time, he raises alarms about inequitable access, job disruption, complacency in relying on imperfect systems, and the lack of guardrails to prevent harmful misuse. Rather than relentlessly stepping on the gas in the AI "race," he emphasizes, we need a steering wheel, in the form of public policy, to ensure that AI development serves the public good. DJ Patil is an entrepreneur, investor, scientist, and public policy leader who served as the first U.S. Chief Data Scientist under the Obama Administration. He has held senior leadership roles at PayPal, eBay, LinkedIn, and Skype, and is currently a General Partner at Greylock Ventures. Patil is recognized as a pioneer in advancing the use of data science to drive innovation, inform policy, and create public benefit.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/37929375
info_outline
Kay Firth-Butterfield: Using AI Wisely
06/26/2025
Kay Firth-Butterfield: Using AI Wisely
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.. Firth-Butterfield highlights the growing trust gap in AI, warning that rapid deployment without safeguards is eroding public confidence. Drawing on her work with Fortune 500 firms and her own cancer journey, she argues for human-centered AI, especially in high-stakes areas like healthcare and law. She also underscores the equity issues tied to biased training data and lack of access in the Global South, noting that AI is now generating data based on historical biases. Despite these challenges, she remains optimistic and calls for greater focus on sustainability, access, and AI literacy across sectors. Kay Firth-Butterfield is the founder and CEO of Good Tech Advisory LLC. She was the world’s first C-suite appointee in AI ethics and was the inaugural Head of AI and Machine Learning at the World Economic Forum from 2017 to 2023. A former judge and barrister, she advises governments and Fortune 500 companies on AI governance and remains affiliated with Doughty Street Chambers in the UK. (Time100 Impact Awards)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/37134515
info_outline
Dale Cendali: How Courts (and Maybe Congress!) Will Determine AI's Copyright Fate
06/19/2025
Dale Cendali: How Courts (and Maybe Congress!) Will Determine AI's Copyright Fate
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 -- she drew on her decades of experience in IP law to provide an engaging look at the legal battlefield and the prospects for resolution. Cendali breaks down the legal challenges around training AI on copyrighted materials—from books to images to music—and explains why these cases are unusually complex for copyright law. She discusses the recent US Copyright Office report on Generative AI training, what counts as infringement in AU outputs, and what is sufficient human authorship for copyirght protection of AI works. While precedent offers some guidance, Cendali notes that outcomes will depend heavily on the specific facts of each case. The conversation also touches on how well courts can adapt existing copyright law to these novel technologies, and the prospects for a legislative solution. Dale Cendali is a partner at Kirkland & Ellis, where she leads the firm’s nationwide copyright, trademark, and internet law practice. She has been named one of the 25 Icons of IP Law and one of the 100 Most Influential Lawyers in America. She also serves as an advisor to the American Law Institute’s Copyright Restatement project and sits on the Board of the International Trademark Association.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/37039165
info_outline
Brenda Leong: Building AI Law Amid Legal Uncertainty
06/12/2025
Brenda Leong: Building AI Law Amid Legal Uncertainty
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36937440
info_outline
Shameek Kundu: AI Testing and the Quest for Boring Predictability
06/05/2025
Shameek Kundu: AI Testing and the Quest for Boring Predictability
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 Verify’s Global AI Assurance pilot, which matched real-world AI deployers—such as hospitals and banks—with specialized testing firms to develop context-aware testing practices. Kundu explains that the rise of generative AI and widespread model use has expanded risk and complexity, making traditional testing insufficient. Instead, companies must assess whether an AI system performs well in context, using tools like simulation, red teaming, and synthetic data generation, while still relying heavily on human oversight. As AI governance evolves from principles to implementation, Kundu makes a compelling case for technical testing as a backbone of trustworthy AI. Shameek Kundu is Executive Director of the AI Verify Foundation. He previously held senior roles at Standard Chartered Bank, including Group Chief Data Officer and Chief Innovation Officer, and co-founded a startup focused on testing AI systems. Kundu has served on the Bank of England’s AI Forum, Singapore’s FEAT Committee, the Advisory Council on Data and AI Ethics, and the Global Partnership on AI.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36831760
info_outline
Uthman Ali: Responsible AI in a Safety Culture
05/29/2025
Uthman Ali: Responsible AI in a Safety Culture
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 scientists—to ensure a comprehensive understanding of AI’s ethical implications. He also highlights the importance of proactive governance, advocating for the development of ethical policies and procedures that address emerging technologies such as robotics and wearables. Ali’s approach underscores the balance between innovation and ethical responsibility, aiming to foster an environment where AI advancements align with societal values and regulatory standards. Uthman Ali is BP’s first Global Responsible AI Officer, and has been instrumental in establishing the company’s Digital Ethics Center of Excellence. He advises prominent organizations such as the World Economic Forum and the British Standards Institute on AI governance and ethics. Additionally, Ali contributes to research and policy discussions as an advisor to Oxford University's Oxethica spinout and various AI safety institutes. (IEEE Standards Association) (2024 podcast interview)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36739365
info_outline
Karen Hao: Is Imperial AI Inevitable?
05/22/2025
Karen Hao: Is Imperial AI Inevitable?
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 technical solutions exist, they are rarely implemented by developers, and foundational harms often occur before tools reach end users. Hao argues that OpenAI’s trajectory was not inevitable but instead the result of specific ideological beliefs, aggressive scaling decisions, and CEO Sam Altman’s singular fundraising prowess. She critiques the “pseudo-religious” ideologies underpinning Silicon Valley’s AI push, where utopian and doomer narratives coexist to justify rapid development. Hao outlines a more democratic alternative focused on smaller, task-specific models and stronger regulation to redirect AI’s future trajectory. Karen Hao has written about AI for publications such as The Atlantic, The Wall Street Journal, and MIT Tchnology Review. She was the first journalist to ever profile OpenAI, and leads The AI Spotlight Series, a program with the Pulitzer Center that trains thousands of journalists around the world on how to cover AI. She has also been a fellow with the Harvard Technology and Public Purpose program, the MIT Knight Science Journalism program, and the Pulitzer Center’s AI Accountability Network. She won an American Humanist Media Award in 2024, and an American National Magazine Award in 2022. (The Atlantic, 2023) (Wall St. Journal, 2023) (The Atlantic, 2023) (MIT Technology Review, 2020)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36539235
info_outline
Jaime Banks: How Users Perceive AI Companions
05/15/2025
Jaime Banks: How Users Perceive AI Companions
AI companion applications, which create interactive personas for one-on-one conversations, are incredibly popular. However, they raise a number of challenging ethical, legal, and psychological questions. In this episode, Kevin Werbach speaks with researcher Jaime Banks about how users view their conversations with AI companions, and the implications for governance. Banks shares insights from her research on mind-perception, and how AI companion users engage in a willing suspension of disbelief similar to watching a movie. She highlights both potential benefits and dangers, as well as novel issues such as the real feelings of loss users may experience when a companion app shuts down. Banks advocates for data-driven policy approaches rather than moral panic, suggesting responses such as an "AI user's Bill of Rights" for these services. Jaime Banks is Katchmar-Wilhelm Endowed Professor at the School of Information Studies at Syracuse University. Her research examines human-technological interaction, including social AI, social robots, and videogame avatars. She focuses on relational construals of mind and morality, communication processes, and how media shape our understanding of complex technologies. Her current funded work focuses on social cognition in human-AI companionship and on the effects of humanizing language on moral judgments about AI. (The Guardian, April 2025) (NY Times, October 2024) (Syracuse iSchool video)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36531135
info_outline
Kelly Trindel: AI Governance Across the Enterprise? All in a Day’s Work
05/08/2025
Kelly Trindel: AI Governance Across the Enterprise? All in a Day’s Work
In this episode, Kevin Werbach interviews Kelly Trindel, Head of Responsible AI at Workday. Although Trindel's team is housed within Workday’s legal department, it operates as a multidisciplinary group, bringing together legal, policy, data science, and product expertise. This structure helps ensure that responsible AI practices are integrated not just at the compliance level but throughout product development and deployment. She describes formal mechanisms—such as model review boards and cross-functional risk assessments—that embed AI governance into product workflows across the company. The conversation covers how Workday evaluates model risks based on context and potential human impact, especially in sensitive areas like hiring and performance evaluation. Trindel outlines how the company conducts bias testing, maintains documentation, and uses third-party audits to support transparency and trustworthiness. She also discusses how Workday is preparing for emerging regulatory frameworks, including the EU AI Act, and how internal governance systems are designed to be flexible in the face of evolving policy and technological change. Other topics include communicating AI risks to customers, sustaining post-deployment oversight, and building trust through accountability infrastructure. Dr. Kelly Trindel directs Workday’s AI governance program. As a pioneer in the responsible AI movement, Kelly has significantly contributed to the field, including testifying before the U.S. Equal Employment Opportunity Commission (EEOC) and later leading an EEOC task force on ethical AI—one of the government’s first. With more than 15 years of experience in quantitative science, civil rights, public policy, and AI ethics, Kelly’s influence and commitment to responsible AI are instrumental in driving the industry forward and fostering AI solutions that have a positive societal impact. (video masterclass)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36456255
info_outline
David Weinberger: How AI Challenges Our Fundamental Ideas
05/01/2025
David Weinberger: How AI Challenges Our Fundamental Ideas
Professor Werbach interviews David Weinberger, author of several books and a long-time deep thinker on internet trends, about the broader implications of AI on how we understand and interact with the world. They examine the idea that throughout history, dominant technologies—like the printing press, the clock, or the computer—have subtly but profoundly shaped our concepts of knowledge, intelligence, and identity. Weinberger argues that AI, and especially machine learning, represents a new kind of paradigm shift: unlike traditional computing, which requires humans to explicitly encode knowledge in rules and categories, AI systems extract meaning and make predictions from vast numbers of data points without needing to understand or generalize in human terms. He describes how these systems uncover patterns beyond human comprehension—such as identifying heart disease risk from retinal scans—by finding correlations invisible to human experts. Their discussion also grapples with the disquieting implications of this shift, including the erosion of explainability, the difficulty of ensuring fairness when outcomes emerge from opaque models, and the way AI systems reflect and reinforce cultural biases embedded in the data they ingest. The episode closes with a reflection on the tension between decentralization—a value long championed in the internet age—and the current consolidation of AI power in the hands of a few large firms, as well as Weinberger’s controversial take on copyright and data access in training large models. David Weinberger is a pioneering thought-leader about technology's effect on our lives, our businesses, and ideas. He has written several best-selling, award-winning books explaining how AI and the Internet impact how we think the world works, and the implications for business and society. In addition to writing for many leading publications, he has been a writer-in-residence, twice, at Google AI groups, Editor of the Strong Ideas book series for MIT Press, a Fellow at the Harvarrd Berkman-Klein Center for Internet and Society, contributor of dozens of commentaries on NPR's All Things Considered, a strategic marketing VP and consultant, and for six years a Philosophy professor. (Wired) (Harvard Business Review)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36359685
info_outline
Ashley Casovan: From Privacy Practice to AI Governance
04/24/2025
Ashley Casovan: From Privacy Practice to AI Governance
Professor Werbach talks with Ashley Casavan, Managing Director of the AI Governance Center at the IAPP, the global association for privacy professional and related roles. Ashley shares how privacy, data protection, and AI governance are converging, and why professionals must combine technical, policy, and risk expertise. They discuss efforts to build a skills competency framework for AI roles and examine the evolving global regulatory landscape—from the EU’s AI Act to U.S. state-level initiatives. Drawing on Ashley’s experience in the Canadian government, the episode also explores broader societal challenges, including the need for public dialogue and the hidden impacts of automated decision-making. Ashley Casovan serves as the primary thought leader and public voice for the IAPP on AI governance. She has developed expertise in responsible AI, standards, policy, open government and data governance in the public sector at the municipal and federal levels. As the director of data and digital for the government of Canada, Casovan previously led the development of the world’s first national government policy for responsible AI. Casovan served as the Executive Director of the Responsible AI Institute, a member of OECD’s AI Policy Observatory Network of Experts, a member of the World Economic Forum's AI Governance Alliance, an Executive Board Member of the International Centre of Expertise in Montréal on Artificial Intelligence and as a member of the IFIP/IP3 Global Industry Council within the UN.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36209255
info_outline
Lauren Wagner: The Potential of Private AI Governance
04/17/2025
Lauren Wagner: The Potential of Private AI Governance
Kevin Werbach interviews Lauren Wagner, a builder and advocate for market-driven approaches to AI governance. Lauren shares insights from her experiences at Google and Meta, emphasizing the critical intersection of technology, policy, and trust-building. She describes the private AI governance model, and the incentives for private-sector incentives and transparency measures, such as enhanced model cards, to guide responsible AI development without heavy-handed regulation. Lauren also explores ongoing challenges around liability, insurance, and government involvement, highlighting the potential of public procurement policies to set influential standards. Reflecting on California's SB 1047 AI bill, she discusses its drawbacks and praises the inclusive debate it sparked. Lauren concludes by promoting productive collaborations between private enterprises and governments, stressing the importance of transparent, accountable, and pragmatic AI governance approaches. Lauren Wagner is a researcher, operator and investor creating new markets for trustworthy technology. She is currently a Term Member at the Council on Foreign Relations, a Technical & AI Policy Advisor to the Data & Trust Alliance, and an angel investor in startups with a trust & safety edge, particularly AI-driven solutions for regulated markets. She has been a Senior Advisor to Responsible Innovation Labs, an early-stage investor at Link Ventures, and held senior product and marketing roles at Meta and Google. (February 2025) (March 2025)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/36088880
info_outline
Medha Bankhwal and Michael Chui: Implementing AI Trust
04/10/2025
Medha Bankhwal and Michael Chui: Implementing AI Trust
Kevin Werbach speaks with Medha Bankhwal and Michael Chui from QuantumBlack, the AI division of the global consulting firm McKinsey. They discuss how McKinsey's AI work has evolved from strategy consulting to hands-on implementation, with AI trust now embedded throughout their client engagements. Chui highlights what makes the current AI moment transformative, while Bankwhal shares insights from McKinsey's recent AI survey of over 760 organizations across 38 countries. As they explain, trust remains a major barrier to AI adoption, although there are geographic differences in AI governance maturity. Medha Bankhwal, a graduate of Wharton's MBA program, is an Associate Partner, as well as Co-founder of McKinsey’s AI Trust / Responsible AI practice. Prior to McKinsey, Medha was at Google and subsequently co-founded a digital learning not-for-profit startup. She co-leads forums for AI safety discussions for policy + tech practitioners, titled “Trustworthy AI Futures” as well as a community of ex-Googlers dedicated to the topic of AI Safety. Michael Chui is a senior fellow at QuantumBlack, AI by McKinsey. He leads research on the impact of disruptive technologies and innovation on business, the economy, and society. Michael has led McKinsey research in such areas as artificial intelligence, robotics and automation, the future of work, data & analytics, collaboration technologies, the Internet of Things, and biological technologies. (March 12, 2025) (January 28, 2025) (November 26, 2024)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/35910115
info_outline
Eric Bradlow: AI Goes to Business School
04/03/2025
Eric Bradlow: AI Goes to Business School
Kevin Werbach speaks with Eric Bradlow, Vice Dean of AI & Analytics at Wharton. Bradlow highlights the transformative impacts of AI from his perspective as an applied statistician and quantitative marketing expert. He describes the distinctive approach of Wharton's analytics program, and its recent evolution with the rise of AI. The conversation highlights the significance of legal and ethical responsibility within the AI field, and the genesis of the new Wharton Accountable AI Lab. Werbach and Bradlow then examine the role of academic institutions in shaping the future of AI, and how institutions like Wharton can lead the way in promoting accountability, learning and responsible AI deployment. Eric Bradlow is the Vice Dean of AI & Analytics at Wharton, Chair of the Marketing Department, and also a professor of Economics, Education, Statistics, and Data Science. His research interests include Bayesian modeling, statistical computing, and developing new methodology for unique data structures with application to business problems. In addition to publishing in a variety of top journals, he has won numerous teaching awards at Wharton, including the MBA Core Curriculum teaching award, the Miller-Sherrerd MBA Core Teaching Award and the Excellence in Teaching Award. Want to learn more? Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI’s power while addressing its risks.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/35910100
info_outline
Wendy Gonzalez: Managing the Humans in the AI Loop
12/12/2024
Wendy Gonzalez: Managing the Humans in the AI Loop
This week, Kevin Werbach is joined by Wendy Gonzalez of Sama, to discuss the intersection of human judgment and artificial intelligence. Sama provides data annotation, testing, model fine-tuning, and related services for computer vision and generative AI. Kevin and Wendy review Sama's history and evolution, and then consider the challenges of maintaining reliability in AI models through validation and human-centric feedback. Wendy addresses concerns about the ethics of employing workers from the developing world for these tass. She then shares insights on Sama's commitment to transparency in wages, ethical sourcing, and providing opportunities for those facing the greatest employment barriers. Wendy Gonzalez is the CEO Sama. Since taking over 2020, she has led a variety of successes at the company, including launching Machine Learning Assisted Annotation which has improved annotation efficiency by over 300%. Wendy has over two decades of managerial and technology leadership experience for companies including EY, Capgemini Consulting and Cycle30 (acquired by Arrow Electronics), and is an active Board Member of the Leila Janah Foundation.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/34194215
info_outline
Jessica Lennard: AI Regulation as Part of a Growth Agenda
12/05/2024
Jessica Lennard: AI Regulation as Part of a Growth Agenda
The UK is in a unique position in the global AI landscape. It is home to important AI development labs and corporate AI adopters, but its regulatory regime is distinct from both the US and the European Union. In this episode, Kevin Werbach sits down with Jessica Leonard, the Chief Strategy and External Affairs Officer at the UK's Competition and Markets Authority (CMA). Jessica discusses the CMA's role in shaping AI policy against the backdrop of a shifting political and economic landscape, and how it balances promoting innovation with competition and consumer protection. She highlights the guiding principles that the CMA has established to ensure a fair and competitive AI ecosystem, and how they are designed to establish trust and fair practices across the industry. Jessica Lennard took up the role of Chief Strategy & External Affairs Officer at the CMA in August 2023. Jessica is a member of the Senior Executive Team, an advisor to the Board, and has overall responsibility for Strategy, Communications and External Engagement at the CMA. Previously, she was a Senior Director for Global Data and AI Initiatives at VISA. She also served as an Advisory Board Member for the UK Government Centre for Data Ethics and Innovation. (April 2024)
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/33954477
info_outline
Tim O'Reilly: The Values of AI Disclosure
11/21/2024
Tim O'Reilly: The Values of AI Disclosure
In this episode, Kevin speaks with with the influential tech thinker Tim O’Reilly, founder and CEO of O’Reilly Media and popularizer of terms such as open source and Web 2.0. O'Reilly, who co-leads the AI Disclosures Project at the Social Science Research Council, offers an insightful and historically-informed take on AI governance. Tim and Kevin first explore the evolution of AI, tracing its roots from early computing innovations like ENIAC to its current transformative role Tim notes the centralization of AI development, the critical role of data access, and the costs of creating advanced models. The conversation then delves into AI ethics and safety, covering issues like fairness, transparency, bias, and the need for robust regulatory frameworks. They also examine the potential for distributed AI systems, cooperative models, and industry-specific applications that leverage specialized datasets. Finally, Tim and Kevin highlight the opportunities and risks inherent in AI's rapid growth, urging collaboration, accountability, and innovative thinking to shape a sustainable and equitable future for the technology. Tim O’Reilly is the founder, CEO, and Chairman of O’Reilly Media, which delivers online learning, publishes books, and runs conferences about cutting-edge technology, and has a history of convening conversations that reshape the computer industry. Tim is also a partner at early stage venture firm O’Reilly AlphaTech Ventures (OATV), and on the boards of Code for America, PeerJ, Civis Analytics, and PopVox. He is the author of many technical books published by O’Reilly Media, and most recently WTF? What’s the Future and Why It’s Up to Us (Harper Business, 2017). SSRC,
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/33954467
info_outline
Alice Xiang: Connecting Research and Practice for Responsible AI
11/14/2024
Alice Xiang: Connecting Research and Practice for Responsible AI
Join Professor Werbach in his conversation with Alice Xiang, Global Head of AI Ethics at Sony and Lead Research Scientist at Sony AI. With both a research and corporate background, Alice provides an inside look at how her team integrates AI ethics across Sony's diverse business units. She explains how the evolving landscape of AI ethics is both a challenge and an opportunity for organizations to reposition themselves as the world embraces AI. Alice discusses fairness, bias, and incorporating these ethical ideas in practical business environments. She emphasizes the importance of collaboration, transparency, and diveristy in embedding a culture of accountable AI at Sony, showing other organizations how they can do the same. Alice Xiang manages the team responsible for conducting AI ethics assessments across Sony's business units and implementing Sony's AI Ethics Guidelines. She also recently served as a General Chair for the ACM Conference on Fairness, Accountability, and Transparency (FAccT), the premier multidisciplinary research conference on these topics. Alice previously served on the leadership team of the Partnership on AI. She was a Visiting Scholar at Tsinghua University’s Yau Mathematical Sciences Center, where she taught a course on Algorithmic Fairness, Causal Inference, and the Law. Her work has been quoted in a variety of high profile journals and published in top machine learning conferences, journals, and law reviews.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/33349962
info_outline
Krishna Gade: Observing AI Explainability...and Explaining AI Observability
11/07/2024
Krishna Gade: Observing AI Explainability...and Explaining AI Observability
Kevin Werbach speaks with Krishna Gade, founder and CEO of Fiddler AI, on the the state of explainability for AI models. One of the big challenges of contemporary AI is understanding just why a system generated a certain output. Fiddler is one of the startups offering tools that help developers and deployers of AI understand what exactly is going on. In the conversation, Kevin and Krishna explore the importance of explainability in building trust with consumers, companies, and developers, and then dive into the mechanics of Fiddler's approach to the problem. The conversation covers current and potential regulations that mandate or incentivize explainability, and the prospects for AI explainability standards as AI models grow in complexity. Krishna distinguishes explainability from the broader process of observability, including the necessity of maintaining model accuracy through different times and contexts. Finally, Kevin and Krishna discuss the need for proactive AI model monitoring to mitigate business risks and engage stakeholders. Krishna Gade is the founder and CEO of Fiddler AI, an AI Observability startup, which focuses on monitoring, explainability, fairness, and governance for predictive and generative models. An entrepreneur and engineering leader with strong technical experience in creating scalable platforms and delightful products,Krishna previously held senior engineering leadership roles at Facebook, Pinterest, Twitter, and Microsoft. At Facebook, Krishna led the News Feed Ranking Platform that created the infrastructure for ranking content in News Feed and powered use-cases like Facebook Stories and user recommendations.
/episode/index/show/524f620b-2515-4e33-b87b-b9eef246c60d/id/33395487