The Road to Accountable AI

Latest Episodes:

David Weinberger: How AI Challenges Our Fundamental Ideas May 01, 2025

Show notes

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)

Ashley Casovan: From Privacy Practice to AI Governance Apr 24, 2025

Show notes

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

Lauren Wagner: The Potential of Private AI Governance Apr 17, 2025

Show notes

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

Medha Bankhwal and Michael Chui: Implementing AI Trust Apr 10, 2025

Show notes

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

Eric Bradlow: AI Goes to Business School Apr 03, 2025

Show notes

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.

Wendy Gonzalez: Managing the Humans in the AI Loop Dec 12, 2024

Show notes

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

Jessica Lennard: AI Regulation as Part of a Growth Agenda Dec 05, 2024

Show notes

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)

Tim O'Reilly: The Values of AI Disclosure Nov 21, 2024

Show notes

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

Alice Xiang: Connecting Research and Practice for Responsible AI Nov 14, 2024

Show notes

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

Krishna Gade: Observing AI Explainability...and Explaining AI Observability Nov 07, 2024

Show notes

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

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