Data Faces Podcast
Data Faces Podcast
Podcast Description
Data Faces is a podcast that brings the human stories behind data, analytics, and AI to the forefront. Join us for engaging interviews and discussions with the industry’s leading voices—the leaders, practitioners, and tech innovators who are shaping the future of data-driven decision-making. In each episode, we explore the culture, challenges, and real-life experiences of the people behind the numbers. Whether you're a tech executive, data professional, or just curious about the impact of data on our world, Data Faces offers a refreshing look at the individuals and ideas driving the next wave
Podcast Insights
Content Themes
The podcast covers themes such as the impact of AI on business, data integrity, historical lessons on technology, and ethical considerations in AI. Episodes include discussions on why 90% of Gen AI projects might fail, the role of trusted data in successful AI initiatives, and how historical revolutions inform our understanding of AI's future potential.
Data Faces is a data, analytics, AI, and marketing podcast that brings the human stories behind the numbers to the forefront. Hosted by David Sweenor, author and founder of TinyTechGuides, each episode features candid conversations with the data leaders, AI innovators, and marketing practitioners putting data and AI to work. Topics include why enterprise AI initiatives fail, AI-ready data and data quality, AI and agentic governance, AI agents, enterprise AI adoption, and B2B marketing. For CIOs, CDOs, analytics leaders, and product marketers.
Leigh Felton, President of the AI for Job Security Foundation, joins Data Faces on location at the 20th annual CDOIQ Symposium in Cambridge, Massachusetts. Had AI been screening job candidates when she started out, she says it would have rejected her. She was a pregnant, homeless teenager and a college dropout who went on to spend 20 years at Microsoft, where she headed the company's first ethical AI enablement program.Leigh shows her two-volume book series, I Could Have Been CEO Yesterday, and explains why she believes you cannot de-bias a system that is built to recognize historical patterns. She makes the case for governing AI as an environment that shapes how people think rather than as a tool you pick up and put down. She also challenges the assumption that faster AI output equals productivity, pointing to research showing AI has reduced productivity for some engineers by about 19 percent.What you will learn:1. Why de-biasing an AI system trained on historical patterns may be impossible2. How environmental-scale governance, in the spirit of OSHA, differs from governing AI as a tool3. Why collaborating with AI and pushing back on it beats publishing its first draft, even when the task takes longer4. Why junior employees and Gen Zers will question the things 30-year experts stopped questioningChapters:0:00 Welcome and the presidential icebreaker1:06 Inside the AI for Job Security Foundation1:36 Two books on AI bias and who gets hired4:48 AI as an environment6:55 Speaking the CDO's language on productivity10:09 Don't let AI genericize you13:30 Will AI ever be smarter than people?15:45 Where to find Leigh's booksWatch more Data Faces on location: https://tinytechguides.com/data-faces-podcast/?utm_source=youtube&utm_medium=video&utm_campaign=cdoiq2026-leigh-felton&utm_content=descriptionConnect with Leigh Felton on LinkedIn: https://www.linkedin.com/in/leighfelton/#DataFacesPodcast #CDOIQ #AIEthics #FutureOfWork
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