AI presents endless opportunities, but its implications for privacy and governance are multifaceted. On this episode, I’m joined by Professor Norman Sadeh, a Computer Science Professor at Carnegie Mellon University, and Co-Founder and Co-Director of the Privacy Engineering Program. With years of experience in AI and privacy, he offers valuable insights into the complexities of AI governance, the evolving landscape of data privacy and why a multidisciplinary approach is vital for creating effective and ethical AI policies. Key Takeaways: (02:09) How Professor Sadeh’s work in AI and privacy began. (05:30) Privacy engineers are in AI governance. (08:45) Why AI governance must integrate with existing company structures. (12:10) The challenges of data ownership and consent in AI applications. (15:20) Privacy implications of foundational models in AI. (18:30) The limitations of current regulations like GDPR in addressing AI concerns. (22:00) How user expectations shape the principles of AI governance. (26:15) The growing debate around the need for specialized AI regulations. (30:40) The role of transparency in AI governance for building trust. (35:50) The potential impact of open-source AI models on security and privacy. Resources Mentioned: Professor Norman Sadeh - https://www.linkedin.com/in/normansadeh/ Carnegie Mellon University | LinkedIn - https://www.linkedin.com/school/carnegie-mellon-university/ Carnegie Mellon University | Website - https://www.cmu.edu/ EU AI Act - https://artificialintelligenceact.eu/ General Data Protection Regulation (GDPR) - https://gdpr-info.eu/ Thanks for listening to the Regulating AI: Innovate Responsibly podcast. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss another insightful conversation. #AIRegulation #AISafety #AIStandard