Me, Myself, and AI

Disintegrating the Org Chart: ServiceNow’s Jacqui Canney

In this episode, Sam is joined by Jacqui Canney, chief people and AI enablement officer at ServiceNow. Jacqui outlines how the software company has embedded AI agents into processes like employee onboarding to automate tasks, personalize experiences, and free up people’s time to focus on higher-value work. She emphasizes that successful adoption of artificial intelligence requires strong change management, workforce training, and a focus on talent — not just technology — including companywide AI skill assessments and personalized learning paths. Tune in to learn why Jacqui sees AI as a human capital opportunity. Read the episode transcript here. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Guest bio: Jacqui Canney is the chief people and AI enablement officer at ServiceNow, where she leads the enterprise software company’s talent strategies for improving employees experience and preparing them for the future workforce through the use of technology and generative AI. Before joining ServiceNow in 2021, Canney served as chief people officer at WPP and Walmart. She previously worked at Accenture for 25 years. Canney currently sits on the board of directors for food delivery platform Wonder and nonprofit Project Healthy Minds. She’s also on the Institute for Corporate Productivity’s Chief HR Officer Board and Boston College’s board of trustees, and she cochairs the Boston College Wall Street Business Leadership Council. Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

Shifting AI From Fear to Optimism: U.S. Department of Labor’s Taylor Stockton

In this episode, Sam speaks with Taylor Stockton, chief innovation officer at the U.S. Department of Labor, about how artificial intelligence is reshaping the workforce. Taylor emphasizes that AI is having an economywide impact, transforming tasks within nearly every job rather than affecting only certain industries or specific roles. He stresses the importance of helping workers and businesses adapt. He also argues that AI literacy is becoming a foundational skill and should be prioritized alongside soft skills like relationship building, which will remain essential for differentiation in an AI-driven economy. Taylor calls for shifting the public narrative from fear to optimism, toward highlighting the ways that AI expands opportunity, mobility, and meaningful work, instead of deepening uncertainty. Read the episode transcript here. Guest bio: As the chief innovation officer of the U.S. Department of Labor, Taylor Stockton leads an exploration into how artificial intelligence and emerging technologies impact the labor market and American workers, as well as what new innovations can support workers in achieving the American dream. Stockton cofounded venture capital firm Pathway Ventures, which focuses on the future of work, and was the chief operating officer of an AI-powered workforce development company. He received his bachelor’s in management at Boston College and Master of Business Administration from Harvard Business School. *Please take our listener survey: ⁠⁠⁠mitsmr.com/podcastsurvey⁠⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.  

An Industry Benchmark for Data Fairness: Sony’s Alice Xiang

On today’s episode, Sam talks with Alice Xiang, global head of AI governance at Sony and lead research scientist for AI ethics at Sony AI, about what it actually takes to put responsible artificial intelligence into practice at scale. Alice shares how Sony moved early on AI ethics and why governance, not just principles, is now the real challenge as AI spreads across products and workflows. The conversation dives into FHIBE, Sony’s publicly available and ethically sourced benchmark for evaluating bias in computer vision, and why measuring fairness is often harder than fixing it. Along the way, they tackle data consent, “data nihilism,” and the very real risks of deploying biased systems in everyday and high-stakes contexts. Read the episode transcript here. Guest bio: As the global head of AI governance at Sony, Alice Xiang leads the team guiding the establishment of AI governance policies and governance frameworks across the company’s business units. She’s also the lead research scientist for AI ethics at Sony AI, which is working on cutting-edge sociotechnical research to enable the development of more responsible AI solutions. Xiang holds a Juris Doctor from Yale Law School, a master’s in development economics from Oxford University, and a master’s in statistics and bachelor’s in economics from Harvard University. *Please take our listener survey: ⁠mitsmr.com/podcastsurvey⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

AI Is Not Improving Productivity: Nobel Laureate Daron Acemoglu

In this bonus episode, Nobel Prize-winning economist Daron Acemoglu joins Sam to challenge some of the most common assumptions about artificial intelligence’s future. Drawing on his book Power and Progress, Daron argues that technology doesn’t have a fixed destiny — and that today’s choices will determine whether AI boosts workers or simply accelerates automation and inequality. He makes a case for focusing on new tasks that complement human skills, rather than replacing them, and warns that current incentives push AI toward centralization and automation by default. The conversation tackles productivity myths, reliability risks, and why regulation should proactively steer AI toward social good. Read the episode transcript here. Guest bio: Daron Acemoglu is an institute professor at MIT, faculty codirector of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work, and a research affiliate at MIT’s newly established Blueprint Labs. He is an elected fellow of the National Academy of Sciences, American Philosophical Society, the British Academy of Sciences, the Turkish Academy of Sciences, the American Academy of Arts and Sciences, the Econometric Society, the European Economic Association, and the Society of Labor Economists. He is also a member of the Group of Thirty. He has authored six books, including Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity with Simon Johnson. His work in economics has been recognized around the world, notably with the Nobel Prize in economic sciences, along with co-laureates Johnson and James A. Robinson, in 2024. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

Connecting Language and (Artificial) Intelligence: Princeton’s Tom Griffiths

In this bonus episode, Princeton University professor and artificial intelligence researcher Tom Griffiths joins Sam to unpack The Laws of Thought, his new book exploring how math has been used for centuries to understand how minds — human and machine — actually work. Tom walks through three main frameworks shaping intelligence today — rules and symbols, neural networks, and probability — and he explains why modern AI only makes sense when you see how those pieces fit together. The conversation connects cognitive science, large language models, and the limits of human versus machine intelligence. Along the way, Tom and Sam dig into language, learning, and what humans still do better — like judgment, curation, and metacognition. Read the episode transcript here. *Please take our listener survey: ⁠mitsmr.com/podcastsurvey⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.