Katie Fowler (Thompson Reuters Foundation): How 3,000 Companies Approach AI Governance
The Road to Accountable AI
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...
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Henry Ajder, Latent Space Advisory: Deepfakes and the Crisis of Digital Trust
The Road to Accountable AI
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...
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Phil Dawson, Armilla AI: Insurance for AI Risks
The Road to Accountable AI
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...
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Walter Haydock, StackAware: In Search Of AI Governance Certification
The Road to Accountable AI
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...
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Richa Kaul, Complyance: Asking the Right Questions
The Road to Accountable AI
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...
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Michael Horowitz, UPenn: Governing AI That's Designed to Kill
The Road to Accountable AI
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...
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Tanvi Singh, Ekta AI: The Case for Sovereign AI
The Road to Accountable AI
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...
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Ray Eitel-Porter, Co-Author of Governing the Machine: The Confidence to Use AI
The Road to Accountable 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...
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Alexandru Voica: Responsible AI Video
The Road to Accountable AI
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...
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Blake Hall: Safeguarding Identity in the AI Era
The Road to Accountable AI
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...
info_outlineRavit 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.
My New Path in AI Ethics (October 2025)
The Values Encoded in Machine Learning Research (FAccT 2022 Distinguished Paper Award) -
Responsible AI Maturity Framework