The Road to Accountable AI

Holistic AI was one of the first companies built specifically to govern, audit, and red team AI systems. As co-founder and co-CEO Emre Kazim explains, its original thesis was that AI governance would mirror data governance: a compliance-driven regime. He now believes the better analogy is cybersecurity: a more technical, incident-driven discipline where best practices emerge from real-world events and propagate across industry, rather than descending from abstract regulatory frameworks. Kazim argues this shift has significant implications for who owns AI governance inside enterprises, what skills they need, and why documentation-and-reporting vendors are unlikely to capture the core of the market. Kazim also makes the case that human-in-the-loop oversight, long treated as the default answer to AI risk, has become untenable as systems grow more dynamic and agentic. He distinguishes between two enterprise adoption patterns: a democratic model in which every employee has a copilot, and a vanguard model in which a small number of mission-critical agentic systems drive most of the value and demand most of the governance attention. Finally, he argues that meaningful research capacity will be the price of entry for AI governance firms going forward. Dr. Emre Kazim is the co-founder and co-CEO of Holistic AI, an AI governance platform company spun out of University College London in 2020. He previously served as a Research Fellow in UCL's Department of Computer Science. Kazim has published more than 50 peer-reviewed articles on AI ethics and governance, serves as a member of the OECD's Network of Experts on AI, and is involved with the NIST AI Safety Institute. Transcript Towards Algorithm Auditing (Royal Society Open Science, 2024) What is AI Governance? (Holistic Blog, February 2026)

Kevin Werbach speaks with long-time responsible AI leader Rumman Chowdhury the current environment, in which substantive standards and oversight efforts for AI are taking shape amid a larger anti-regulation wave. Chowdhury distinguishes sharply between frontier labs, where the posture is largely "AI at all costs," and the non-tech enterprises she works with, who are wrestling with how to scale governance bodies that originally reviewed single AI implementations to hundreds of systems, third-party procurement questions, and agentic workloads. She describes the current evaluations market as immature on nearly every dimension, and explains why generic benchmarks rarely translate to enterprise contexts like insurance or auto manufacturing. The conversation then turns to AI's impact on work and education. Her concern is that companies pursuing short-term efficiency by cutting entry-level hiring will face what MIT researchers Caosun and Aral call the "augmentation trap," in which workers' cognitive skills atrophy while new workers never develop them. She offers "discernment" as her 2026 word of the year, discribing the skill -- more than just critical thinking -- we must cultivate and defend. Her new podcast and forthcoming book, Thinking About Thinking, argues that our notion of intelligence was built for an Industrial Revolution workforce we are now automating away. Dr. Rumman Chowdhury is the founder of Humane Intelligence PBC, building modular, tool-agnostic AI evaluation infrastructure for enterprise and real-world contexts. She co-founded the nonprofit Humane Intelligence in 2022 and served as its CEO until 2025. She previously was Director of the Machine Learning Ethics, Transparency, and Accountability team at Twitter, founder of the algorithmic audit platform Parity, and Global Lead of Responsible AI at Accenture, where she built one of the first enterprise-level bias detection tools. She has served as U.S. Science Envoy for AI and as a Responsible AI Fellow at Harvard's Berkman Klein Center, and holds a doctorate in political science from the University of California, San Diego. Transcript Virginia SB 384 / HB 797 — Independent Verification Organization legislation (Fathom) The Augmentation Trap: AI Productivity and the Cost of Cognitive Offloading Open to Debate: Will AI Make Work Obsolete? Why AI evals need to reflect the real world (Transformer)

Var Shankar makes the case that most AI governance guidance is built for large, sophisticated, multifunctional global enterprises — and that this leaves out the roughly half of American workers employed at organizations with fewer than 500 people. Through the Council on AI Governance, the nonprofit he leads with Alexis Cook, he is trying to fill that gap with open, current, and pragmatic resources, including an AI Governance Playbook organized around four focus areas: strategy, risk and compliance, workforce literacy, and operational management. He tells Kevin that the case for AI governance no longer needs to be made; what smaller organizations now need is help asking vendors the right questions and clarifying who owns what internally when a few people are doing many jobs. The conversation then turns to the parts of the field Var thinks are most undercooked. Workforce literacy, he argues, is the focus area most often neglected because it functions as a vitamin rather than a painkiller — long-term, hard to resource, and easy to reduce to a training module when what is actually needed is hands-on involvement in pilots and documentation. He explains why healthcare offers an unusually strong foundation for AI assurance, with its existing regulatory architecture, comfort with use-case variability, and tradition of post-deployment monitoring, and he describes assurance itself as the connective tissue between an organization and the outside world — distinct from regulation and from internal governance, not a substitute for either. Drawing on a pilot he co-authored on with the Standards Council of Canada testing system-level certification at a Canadian bank, he highlights two surprising lessons: that even simplified certification criteria get interpreted differently by different actors, and that even one of the world's most forward-thinking public standards bodies lacked the technical capacity to play standard-setter for something as dynamic as an AI system. He closes with practical advice for risk and compliance professionals: start with the positive vision of what the organization is trying to do with AI, observe how existing IT, data, and security governance already work, and identify which standards ecosystems the organization is already plugged into. Var Shankar is Executive Director of the Council on AI Governance, an independent nonprofit developing open AI governance resources for organizations of all sizes. He previously served as Executive Director of the Responsible AI Institute and as Chief AI and Privacy Officer at Enzai, a regtech AI compliance startup. An attorney by training and a graduate of Harvard Law School, he practiced law at Cravath, Swaine & Moore and earlier worked on the Clinton Global Initiative and with the government of British Columbia on digital government and COVID response. He teaches AI governance at Purdue, where he has helped develop a master's-level AI auditing program, and serves on the OECD Network of Experts on AI, the World Economic Forum's AI Governance Alliance, and the Brookings Forum for Cooperation on AI. He co-developed Kaggle's Intro to AI Ethics course with Alexis Cook. Transcript   Council on AI Governance: AI Governance Playbook Context-specific certification of AI systems: a pilot in the financial industry (AI and Ethics, 2025) Standards Council of Canada AI accreditation pilot

Good data about how companies are implementing AI governance programs is essential both for organizations to benchmark their efforts, and for observers to understand the state of development. In this episode, Katie Fowler, Director of Responsible Business at the Thomson Reuters Foundation, joins Kevin Werbach to discuss the findings of Responsible AI in Practice, a new report drawing on a global dataset of roughly 3,000 companies across 13 sectors. Fowler unpacks the report's central finding: an enormous gap between corporate AI ambition and operational governance, with 44 percent of companies reporting an AI strategy but only 13 percent publicly committing to a formal governance framework. She argues that the gap is structural rather than just a disclosure failure, noting that AI expertise often sits deep within technical teams rather than at the leadership levels responsible for organization-wide rollout. She points to striking regional variation in workforce protections, the EU AI Act's emergence as a de facto global reference framework even outside Europe, and pushes back on the narrative that regulation stifles innovation. Looking forward, she discusses how investors are using transparency as a proxy for risk management in the absence of mature responsible AI metrics, and outlines the long-term vision of building a dataset robust enough to support a responsible AI index tied to financial materiality. Katie Fowler is Director of Responsible Business at the Thomson Reuters Foundation, the independent charity affiliated with Thomson Reuters. She leads initiatives including the Workforce Disclosure Initiative (a global platform collecting survey data on how companies treat workers across their direct operations and supply chains) and the AI Company Data Initiative, launched in partnership with UNESCO. Before joining the Foundation, Fowler held leadership roles at The Social Innovation Partnership and Chance for Childhood.  Transcript Responsible AI in Practice: 2025 Global Insights from the AI Company Data Initiative Why a Companywide Effort Is Key to Responsible and Trustworthy AI Adoption (Katie Fowler, techUK guest blog, 2025)  

AI-generated deepfakes are exploding in volume and quality, posing frightening challenges for public discourse, security, safety, and more. My guest, Henry Ajder, has been mapping the deepfake landscape since before most people had heard the term. In this conversation, he describes the dramatic changes in realism, efficiency, accessibility, and functionality of synthetic media tools since he published the first comprehensive census of deepfakes in 2019. Ajder describes the current moment as one of "epistemic nihilism," where people cannot reliably distinguish real from synthetic content and the available technological responses are not yet at a level of categorical trust. He introduces a framework of "deception, doubt, and degradation" for understanding deepfake harms, and draws a distinction between the clearly malicious, the clearly beneficial, and a vast unsettling middle ground of uses that society has not yet figured out how to evaluate. On the response side, Ajder warns that media literacy advice is not just outdated but actively harmful, because it gives people false confidence in their ability to spot fakes. Detection tools, watermarking, and content provenance standards like C2PA, while valuable, each have real limitations. Ajder's practical advice for organizations centers on red-teaming, understanding what your tool is actually for and who it serves, and recognizing that authenticity is a strategic asset in a synthetic age. Henry Ajder is the founder of Latent Space Advisory and one of the world's foremost experts on deepfakes and generative AI. He authored the landmark 2019 State of Deepfakes report, and has since advised organizations including Meta, Adobe, the UK Government, the EU Commission, the US FTC, and the World Economic Forum. He co-leads the University of Cambridge's Generative AI in Business programme, and sits on Meta's Reality Labs Advisory Council. Transcript Latent Space Advisory The State of Deepfakes: Landscape, Threats, and Impact (2019) The Future Will Be Synthesised (BBC Radio 4 Documentary Series, 2022)  

Could a private insurance market play a significant role in compensating for AI-related harms and incentivizing companies to engage in more effective AI governance? Phil Dawson of Armillla AI explains why AI insurance is emerging as a distinct product category, why traditional policies aren't effective at addressing AI risks, and what AI insurance actually covers. Dawson details Armilla's journey from AI testing platform assurance provider to, managing general agent for AI insurance policies, arguing that the company's AI audit experience gave it the risk data and evaluation capabilities needed to underwrite AI systems. A key turning point, he says, was realizing that as companies received reports showing how their models performed or underperformed, they became more concerned about risk, and insurance emerged as the next logical step to build trust. Dawson identifies the absence of claims data as the central challenge for AI underwriting, which forces insurers to rely on proxy signals. He argues that policymakers can help by incentivizing transparency, disclosure, and third-party assessment. Drawing on lessons from cyber insurance, Dawson contends that risk-based pricing must be grounded in system-level governance evaluation. He also describes Armilla's partnership program, which connects insured companies with AI governance platforms, auditing firms, and certification bodies, ultimately driving improved AI governance maturity across the sector. Philip Dawson is Head of AI Policy and Partnerships at Armilla AI, an MGA and Lloyd's cover holder that provides dedicated AI insurance products. A lawyer and public policy adviser, he has spent nearly a decade working on AI governance, including early involvement in the drafting of the OECD AI Principles and roles at Element AI, the United Nations, and the Harvard Kennedy School's Carr Center for Human Rights Policy. Transcript Ready or Not: The Impact of Artifician Intelligence on Insurance Risks (Armilla AI and Lockton, February 2026) Armilla AI Raises Lloyd's-Backed Coverage to $25M as Traditional Insurers Retreat from AI Risk (Fintech Finance News, January 22, 2026)  Gen AI Risks for Businesses: Exploring the Role for Insurance (Geneva Association, October 2, 2025)

Walter Haydock draws a direct line from military risk management to the enterprise AI challenge. His argues that organizations need to stop doing "math with colors," and move toward quantitative assessment that assigns dollar values to potential AI failures. Much of the conversation in this episode focuses on ISO 42001, the global standard for AI management systems, which Haydock has championed and which his own firm has gone through. He draws a three-part taxonomy of AI governance frameworks: legislation you either comply with or don't, voluntary self-attestable frameworks like the NIST AI RMF, and externally certifiable standards like ISO 42001 that bring independent verification. Haydock outlines a forward-looking vision in which certification, insurance, and legal safe harbors reinforce one another. Machine-readable audit data will eventually allow insurers to make informed underwriting decisions about AI risk, reducing uncertainty for both enterprises and their customers.  Though, as he acknowledges, we are still far from that environment, with AI audits today still roughly 90% manual. Walter Haydock is the founder of StackAware, which helps AI-powered companies manage security, compliance, and privacy risk. Before entering the private sector, he served as a reconnaissance and intelligence officer in the U.S. Marine Corps, as a professional staff member for the Homeland Security Committee of the U.S. House of Representatives, and as an analyst at the National Counterterrorism Center. He is a graduate of the United States Naval Academy, Georgetown University's School of Foreign Service, and Harvard Business School. Transcript Deploy Securely (Haydock's Substack)

Richa Kaul breaks down the AI risk landscape for enterprises, and argues that the key to managing all of them is resisting the urge to sensationalize. Kaul offers a candid assessment of where enterprise AI governance committees are falling short, noting that many  lack the technical fluency to ask vendors the right questions, such as where customer data goes, whether it trains other clients' models, and what specific steps reduce hallucination. She suggests that market-driven security standards like SOC-2 and ISO 27001 often matter more in practice than government regulation, creating a "beautiful ecosystem" where risk management runs ahead of the law. Looking forward, she addresses the growing challenge of agentic AI systems that make decisions autonomously, offering a deceptively simple prescription: Map every action an agent can take, know where your highest risk sits, identify the critical decision points, and demand human sign-off at each one/ Richa Kaul is the founder and CEO of Complyance, an AI-native enterprise governance, risk, and compliance (GRC) platform. Before founding Complyance, she was Chief Strategy Officer at ContractPodAi, a legal technology company, and previously served as Managing Director at the Virginia Economic Development Partnership and as a management consultant at McKinsey. Transcript Complyance Raises $20M to Help Companies Manage Risk and Compliance (TechCrunch, February 11, 2026)

How AI is, could, and shouldn't be used in military and other national security contexts is a topic of growing importance. Recent conflicts on the battlefield, and between the U.S. military and a major AI lab, are forcing conversations about legal, ethical, and appropriate business limitations for increasingly powerful AI tools. Michael Horowitz, a Political Science professor and Director of Perry World House at the University of Pennsylvania, is one of the world's leading experts on military AI and autonomous weapons. In this episode, drawing on his two stints in the U.S. Department of Defense, Horowitz walks through the major buckets of military AI use. He explains why militaries are, in some ways, more incentivized than any other institution to get AI governance right, but genuine tensions among speed, effectiveness, and meaningful human control can make responsible military AI difficult in practice. We cover Anthropic's recent dispute with the Pentagon as a case study in the fragile and increasingly consequential relationship between Silicon Valley and the defense establishment.  Michael C. Horowitz is the Richard Perry Professor of Political Science and Director of Perry World House at the University of Pennsylvania, and a Senior Fellow for Technology and Innovation at the Council on Foreign Relations. From 2022 to 2024, he served as U.S. Deputy Assistant Secretary of Defense for Force Development and Emerging Capabilities, where he was the principal author of the U.S. Political Declaration on Responsible Military Use of AI and Autonomy. He is the author of The Diffusion of Military Power: Causes and Consequences for International Politics and co-author of Why Leaders Fight. Transcript Battles of Precise Mass: Technology Is Remaking War — and America Must Adapt (Foreign Affairs, 2024) The Ethics & Morality of Robotic Warfare: Assessing the Debate over Autonomous Weapons (Daedalus, 2016) Rules of Engagement (Penn Gazette, 2025)  

Tanvi Singh draws on over two decades of building and governing AI systems inside global banks to make a provocative case: you cannot be accountable for decisions you do not control. Enterprises are consuming intelligence through models they don't own, can't explain, and didn't train. Singh reframes sovereignty beyond data center locations and infrastructure, to control across the entire stack, so that an organization's AI reflects its own values, laws, and culture. Whlile frontier LLMs will continue to dominate the consumer and retail market, she argues that domain-specific models will be important for enterprise and regulated use cases, offering better accuracy at dramatically lower cost. The conversation also touches on Singh's engagement with the Vatican's Pontifical Academy of Sciences around AI ethics, which has worked on benchmarks that reflect institutional values rather than defaulting to the cultural norms baked into large internet-trained models. Tanvi Singh is the Co-Founder and CEO of Ekta Inc., a sovereign AI platform company building domain-specific foundation models for governments and regulated industries. She previously served as Group Head of AI, Data & Analytics at UBS and held senior technology leadership roles at Credit Suisse, GE, and Monsanto. She is the founder and managing partner of Nirmata-ai Ventures, a Zurich-based deep-tech venture fund, and serves as a board member of the Global Blockchain Business Council and GirlsCanCode.  Transcript Sovereign AI: Why States and Institutions Have to Take Back Their Digital Intelligence (HSToday, co-authored with Thomas Cellucci) Ekta AI  

Ray Eitel-Porter, former Global Lead for Responsible AI at Accenture and co-author of the new book, Governing the Machine, discusses how enterprises can move from abstract AI principles to practical governance. He emphasizes that organizations can only realize AI's benefits if responsibility is embedded into everyday business processes rather than treated as a standalone compliance exercise. Drawing on his experience leading global data and AI programs, Eitel-Porter explains how the release of ChatGPT transformed enterprise attitudes toward AI, accelerating adoption while exposing risks such as hallucinations, reliability failures, and reputational harm. Effective governance has evolved from static principles to operational controls, including workflow checkpoints, red teaming, and technical guardrails, particularly for generative AI systems with inherently probabilistic outputs. On risk, he stresses that not all AI use cases require the same level of scrutiny; governance should scale with potential impact and harm, focusing on what an AI system is intended to do so that non-technical teams can surface high-risk use cases without incentives to downplay risk. On regulation, Eitel-Porter notes that despite uncertainty around the EU AI Act, many multinational companies are treating it as a global baseline, similar to GDPR, while contrasting this with more deregulatory signals from the United States and questioning the global influence of the UK's middle-ground approach. He also shares insights from Governing the Machine, co-authored with Miriam Bogle and Paul Donkhan, emphasizing that AI governance is not a barrier to innovation but the foundation that allows organizations to deploy AI at scale with confidence and control. Ray Eitel-Porter is a Senior Advisor at Accenture and the former Global Lead for Responsible AI, where he designed and scaled AI governance programs for multinational organizations. He previously led Accenture's data and AI practice in the UK and has over a decade of experience advising companies on responsible AI, data governance, and emerging technology risk. Eitel-Porter is the co-author of Governing the Machine: How to Navigate the Risks of AI and Unlock Its True Potential (Bloomsbury, 2025) and has led multi-year programs across public and private sectors, including global banks, retailers, and health brands. Transcript Governing the Machine (Bloomsbury 2025) Lessons from the Frontline – Designing and Implementing AI Governance (AI Journal)    

Alexandru Voica, Head of Corporate Affairs and Policy at Synthesia, discusses how the world's largest enterprise AI video platform has approached trust and safety from day one. He explains Synthesia's "three C's" framework—consent, control, and collaboration: never creating digital replicas without explicit permission, moderating every video before rendering, and engaging with policymakers to shape practical regulation. Voica acknowledges these safeguards have cost some business, but argues that for enterprise sales, trust is competitively essential. The company's content moderation has evolved from simple keyword detection to sophisticated LLM-based analysis, recently withstanding a rigorous public red team test organized by NIST and Humane Intelligence. Voica criticizes the EU AI Act's approach of regulating how AI systems are built rather than focusing on harmful outcomes, noting that smaller models can now match frontier capabilities while evading compute-threshold regulations. He points to the UK's outcome-focused approach—like criminalizing non-consensual deepfake pornography—as more effective. On adoption, Voica argues that AI companies should submit to rigorous third-party audits using ISO standards rather than publishing philosophical position papers—the thesis of his essay "Audits, Not Essays." The conversation closes personally: growing up in 1990s Romania with rare access to English tutoring, Voica sees AI-powered personalized education as a transformative opportunity to democratize learning. Alexandru Voica is the Head of Corporate Affairs and Policy at Synthesia, the UK's largest generative AI company and the world's leading AI video platform. He has worked in the technology industry for over 15 years, holding public affairs and engineering roles at Meta, NetEase, Ocado, and Arm. Voica holds an MSc in Computer Science from the Sant'Anna School of Advanced Studies and serves as an advisor to MBZUAI, the world's first AI university. Transcript Audits, Not Essays: How to Win Trust for Enterprise AI (Transformer) Synthesia's Content Moderation Systems Withstand Rigorous NIST, Humane Intelligence Red Team Test (Synthesia) Computerspeak Newsletter

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. Transcript 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 . Transcript 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. Transcript 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. Transcript 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. Transcript 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. Transcript 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. Transcript 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 Transcript 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. Transcript  AI Governance in the Agentic Era Implementing Responsible AI in the Generative Age - Study Between HCL Tech and MIT

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. Transcript https://drive.google.com/file/d/1zLLOkndlN2UYuQe-9ZvZNLhiD3e2TPZS/view America's AI Action Plan Dean Ball's Hyperdimensional blog  

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.  MAS Feat Principles on Repsonsible AI (2018) Veritas Initative – MAS-backed consortium applying FEAT principles in practice Can AI Save Us From the Losing War With Scammers? Perhaps (Business Times, 2024) Can Artificial Intelligence Be Moral?  (Business Times, 2021)

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. OECD.ai   

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. Transcript Ethics of Data Science, Co-Authored by DJ Patil

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.  Transcript Kay Firth-Butterfield Is Shaping Responsible AI Governance (Time100 Impact Awards) Our Future with AI Hinges on Global Cooperation Building an Organizational Approach to Responsible AI Co-Existing with AI - Firth-Butterfield's Forthcoming Book

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. Transcript Thompson Reuters Wins Key Fair Use Fight With AI Startup Dale Cendali - 2024 Law360 MVP Copyright Office Report on Generative AI Training

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 law firms—she outlines how companies can leverage existing regulations, industry-specific expectations, and contextual risk assessments to build practical, responsible AI governance frameworks. Leong emphasizes that many organizations now treat AI oversight not just as a legal compliance issue, but as a critical business function. As AI tools become more deeply embedded in legal workflows and core operations, she highlights the growing need for cautious interpretation, technical fluency, and continuous adaptation within the legal field. Brenda Leong is Director of ZwillGen's AI Division, where she leads legal-technical collaboration on AI governance, risk management, and model audits. Formerly Managing Partner at Luminos.Law, she pioneered many of the audit practices now used at ZwillGen. She serves on the Advisory Board of the IAPP AI Center, teaches AI law at IE University, and previously led AI and ethics work at the Future of Privacy Forum.  Transcript   AI Audits: Who, When, How...Or Even If?   Why Red Teaming Matters Even More When AI Starts Setting Its Own Agenda      

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.   Transcript AI Verify Foundation Findings from the Global AI Assurance Pilot Starter Kit for Safety Testing of LLM-Based Applications  

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.   Transcript Prioritizing People and Planet as the Metrics for Responsible AI (IEEE Standards Association) Robocops and Superhumans: Dilemmas of Frontier Technology (2024 podcast interview)

  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. Transcript Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI Inside the Chaos at OpenAI (The Atlantic, 2023) Cleaning Up ChatGPT Takes Heavy Toll on Human Workers (Wall St. Journal, 2023) The New AI Panic (The Atlantic, 2023) The Messy, Secretive Reality Behind OpenAI's Bid to Save the World (MIT Technology Review, 2020)

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. Transcript ‘She Helps Cheer Me Up': The People Forming Relationships With AI Chatbots (The Guardian, April 2025) Can AI Be Blamed for a Teen's Suicide? (NY Times, October 2024) Beyond ChatGPT: AI Companions and the Human Side of AI (Syracuse iSchool video)

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.  Transcript Responsible AI: Empowering Innovation with Integrity   Putting Responsible AI into Action (video masterclass)  

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.  Transcript Everyday Chaos Our Machines Now Have Knowledge We'll Never Understand (Wired)  How Machine Learning Pushes Us to Define Fairness (Harvard Business Review)

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. Transcript Ashley Casovan IAPP IAPP AI Governance Profession Report 2025 Global AI Law and Policy Tracker Mapping and Understanding the AI Governance Ecosystem

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.  Transcript AI Governance Through Markets (February 2025) How Tech Created the Online Fact-Checking Industry (March 2025) Responsible Innovation Labs Data & Trust Alliance  

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. Episode Transcript The State of AI: How Organizations are Rewiring to Capture Value (March 12, 2025)  Superagency in the workplace: Empowering people to unlock AI's full potential (January 28, 2025) Building AI Trust: The Key Role of Explainability (November 26, 2024) McKinsey Responsible AI Principles

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.  Episode Transcript Wharton AI & Analytics Initiative Eric Bradlow - Knowledge at Wharton   Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.  

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.  https://www.sama.com/ Forbes Business Council - Wendy Gonzalez

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.  Competition and Markets Authority CMA AI Strategic Update (April 2024)

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, AI Disclosures Project Asimov's Addendum Substack The First Step to Proper AI Regulation Is to Make Companies Fully Disclose the Risks

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.  Sony AI Flagship Project Augmented Datasheets for Speech Datasets and Ethical Decision-Making by Alice Xiang and Others  

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.   Fiddler.Ai How Explainable AI Keeps Decision-Making Algorithms Understandable, Efficient, and Trustworthy - Krishna Gade x Intelligent Automation Radio    

This week, Professor Werbach is joined by USC Law School professor Angela Zhang, an expert on China's approach to the technology sector. China is both one of the world's largest markets and home to some of the world's leading tech firms, as well as an active ecosystem of AI developers. Yet its relationship to the United States has become increasingly tense. Many in the West see a battle between the US and China to dominate AI, with significant geopolitical implications. In the episodoe, Zhang discusses China's rapidly evolving tech and AI landscape, and the impact of government policies on its development. She dives into what the Chinese government does and doesn't do in terms of AI regulation, and compares Chinese practices to those in the West. Kevin and Angela consider the implications of US export controls on AI-related technologies, along with the potential for cooperation between the US and China in AI governance. Finally, they look toward the future of Chinese AI including its progress and potential challenges.  Angela Huyue Zhang is a Professor of Law at the Gould School of Law  of the University of Southern California. She is the author of Chinese Antitrust Exceptionalism: How the Rise of China Challenges Global Regulation which was named one of the Best Political Economy Books of the Year by ProMarket in 2021. Her second book, High Wire: How China Regulates Big Tech and Governs Its Economy, released in March 2024, has been covered in The New York Times, Bloomberg, Wire China, MIT Tech Review and many other international news outlets.    High Wire: How China Regulates Big Tech and Governs Its Economy  The Promise and Perils of China's Regulation of Artificial Intelligence Angela Zhang's Website   Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.  

Professor Werbach speaks with Shea Brown, founder of AI auditing firm BABL AI. Brown discusses how his work as an astrophysicist led him to and machine learning, and then to the challenge of evaluating AI systems. He explains the skills needed for effective AI auditing and what makes a robust AI audit. Kevin and Shae talk about the growing landscape of AI auditing services and the strategic role of specialized firms like BABL AI. They examine the evolving standards and regulations surrounding AI auditing from local laws to US government initiatives to the European Union's AI Act. Finally, Kevin and Shae discuss the future of AI auditing, emphasizing the importance of independence.  Shea Brown, the founder and CEO of BABL AI, is a researcher, speaker, consultant in AI ethics, and former associate professor of instruction in Astrophysics at the University of Iowa. Founded in 2018, BABL AI has audited and certified AI systems, consulted on responsible AI best practices, and offered online education on related topics. BABL AI's overall mission is to ensure that all algorithms are developed, deployed, and governed in ways that prioritize human flourishing. Shea is a founding member of the International Association of Algorithmic Auditors (IAAA). BABL.ai International Association of Algorithmic Auditors NYC Local Law 144: Automated Employment Decision Tools (AEDT) Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.  

This week, Professor Werbach is joined by Kevin Bankston, Senior Advisor on AI Governance for the Center for Democracy & Technology, to discuss the benefits and risks of open weight frontier AI models. They discuss the meaning of open foundation models, how they relate to open source software, how such models could accelerate technological advancement, and the debate over their risks and need for restrictions. Bankston discusses the National Telecommunications and Information Administration's recent recommendations on open weight models, and CDT's response to the request for comments. Bankston also shares insights based on his prior work as AI Policy Director at Meta, and discusses national security concerns around China's ability to exploit open AI models.  Kevin Bankston is Senior Advisor on AI Governance for the Center for Democracy & Technology, supporting CDT's AI Governance Lab. In addition to a prior term as Director of CDT's Free Expression Project, he has worked on internet privacy and related policy issues at the American Civil Liberties Union, Electronic Frontier Foundation, the Open Technology Institute, and Meta Platfrms. He was named by Washingtonian magazine as one of DC's 100 top tech leaders of 2017. Kevin serves as an adjunct professor at the Georgetown University Law Center, where he teaches on the emerging law and policy around generative AI.  CDT Comments to NTIA on Open Foundation Models by Kevin Bankston  CDT Submits Comment on AISI's Draft Guidance, "Managing Misuse Risk for Dual-Use Foundation Models" Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.  

In this episode, Professor Kevin Werbach sits with Lara Abrash, Chair of Deloitte US. Lara and Kevin discuss the complexities of integrating generative AI systems into companies and aligning stakeholders in making AI trustworthy. They discuss how to address bias, and the ways Deloitte promotes trust throughout its organization. Lara explains the role and technological expertise of boards, company risk management, and the global regulatory environment. Finally, Lara discusses the ways in which Deloitte handles both its people and the services they provide.  Lara Abrash is the Chair of Deloitte US, leading the Board of Directors in governing all aspects of the US Firm. Overseeing over 170,000 employees, Lara is a member of Deloitte's Global Board of Directors and Chair of the Deloitte Foundation. Lara stepped into this role after serving as the chief executive officer of the Deloitte US Audit & Assurance business. Lara frequently speaks on topics focused on advancing the profession including modern leadership traits, diversity, equity, and inclusion, the future of work, and tech disruption. She is a member of the American Institute of Certified Public Accountants and received her MBA from Baruch College.  Deloitte's Trustworthy AI Framework Deloitte's 2024 Ethical Technology Report Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.

Professor Werbach speaks with Adam Thierer, senior fellow for Technology and Innovation at R Street Institute. Adam and Kevin highligh developments in AI regulation on the state, federal, and international scale, and discuss both the benefits and dangers of regulatory engagement in the area. They consider the notion of AI as a “field-of-fields,” and the value of a sectoral approach to regulation, looking back to the development of regulatory approaches for the internet. Adam discusses what types of AI regulations can best balance accountability with innovation, protecting smaller AI developers and startups.  Adam Thierer specializes in entrepreneurialism, Internet, and free-speech issues, with a focus on emerging technologies. He is a senior fellow for the Technology & Innovation team at R Street Institute, a leading public policy think tank, and previously spent 12 years as a senior fellow at the Mercatus Center at George Mason University. Adam has also worked for the Progress and Freedom Foundation, the Adam Smith Institute, the Heritage Foundation and the Cato Institute. Adam has published 10 books on a wide range of topics, including online child safety, internet governance, intellectual property, telecommunications policy, media regulation and federalism. Flexible, Pro-Innovation Governance Strategies for Artificial Intelligence Permissionless Innovation: The Continuing Case for Comprehensive Technological Freedom Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.

In this episode, Kevin Werbach is joined by Reggie Townsend, VP of Data Ethics at SAS, an analytics software for business platform. Together they discuss SAS's nearly 50-year long history of supporting business's technology and the recent implementation of responsible AI initiatives. Reggie introduces model cards and the importance of variety in AI systems across diverse stakeholders and sectors. Reggie and Kevin explore the increase in both consumer trust and purchases when they feel a brand is ethical in its use of AI and the importance of trustworthy AI in employee retention and recruitment. Their discussion approaches the idea of bias in an untraditional way, highlighting the positive humanistic nature of bias and learning to manage the negative implications. Finally, Reggie shares his insights on fostering ethical AI practices through literacy and open dialogue, stressing the importance of authentic commitment and collaboration among developers, deployers, and regulators. SAS adds to its trustworthy AI offerings with model cards and AI governance services Article by Reggie Townsend: Talking AI in Washington, DC Reggie Townsend oversees the Data Ethics Practice (DEP) at SAS Institute. He leads the global effort for consistency and coordination of strategies that empower employees and customers to deploy data driven systems that promote human well-being, agency and equity. He has over 20 years of experience in strategic planning, management, and consulting focusing on topics such as advanced analytics, cloud computing and artificial intelligence. With visibility across multiple industries and sectors where the use of AI is growing, he combines this extensive business and technology expertise with a passion for equity and human empowerment.   Want to learn more? ​​Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks.  

Join Professor Kevin Werbach in his discussion with Helen Toner, Director of Strategy and Foundational Research Grants at Georgetown's Center for Security and Emerging Technology. In this episode, Werbach and Toner discuss how the public views AI safety and ethics and both the positive and negative outcomes of advancements in AI. We discuss Toner's lessons from the unsuccessful removal of Sam Altman as the CEO of OpenAI, oversight structures to audit and approve the AI companies deploy, and the role of the government in AI accountability. Finally, Toner explains how businesses can take charge of their responsible AI deployment.   Helen Toner is the Director of Strategy and Foundational Research Grants at Georgetown's Center for Security and Emerging Technology (CSET). She previously worked as a Senior Research Analyst at Open Philanthropy, where she advised policymakers and grantmakers on AI policy and strategy. Between working at Open Philanthropy and joining CSET, Helen lived in Beijing, studying the Chinese AI ecosystem as a Research Affiliate of Oxford University's Center for the Governance of AI. From 2021-2023, she served on the board of OpenAI, the creator of ChatGPT.  Helen Toner's TED Talk: How to Govern AI, Even if it's Hard to Predict Helen Toner on the OpenAI Coup “It was about trust and accountability” (Financial Times)   Want to learn more? Engage live with Professor Werbach and other Wharton faculty experts in Wharton's new  Strategies for Accountable AI online executive education program. It's perfect for managers, entrepreneurs, and advisors looking to harness AI's power while addressing its risks