Send us a text

In episode 241 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Phillip Mason, Global Privacy Program Manager at Corning, Inc. Phillip joins Debbie to discuss the complicated interplay between AI advancement, regulatory frameworks, and the ethical imperative of human judgment. Drawing from his diverse background in accounting, law, and privacy, Phillip offers an informed and multidimensional perspective on how businesses navigate emerging risks. He critiques overbroad AI legislation like the EU AI Act, which he believes may have unintended consequences for innovation, particularly among smaller firms lacking legal and compliance resources. Debbie and Phillip dive into examples of poorly executed AI rollouts that sparked public backlash, such as LinkedIn’s data harvesting practices and Microsoft’s Recall feature, emphasizing the importance of transparency and foresight. Phillip also unpacks the difference between having a “human in the loop” and placing real ethical judgment into practice. They discuss how organizations can build a culture of trust and accountability where data science and compliance work harmoniously. The conversation ultimately underscores that as algorithms get smarter, human oversight must also evolve, with thoughtful governance, interdisciplinary collaboration, and values-driven leadership.

Support the show

Send us a text

In episode 240 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Ian Glazer, Vice President of Product Strategy at SGNL (SGNL.ai) and co-founder of IDPro. With decades of leadership in digital identity, Ian shares insights on how identity, privacy, and security have become essential foundations of digital interaction.

They explore how identity has shifted from managing usernames and passwords to helping individuals assert who they are in digital spaces. Ian and Debbie examine the rise of “proofing creep,” where services now require government IDs and biometric selfies, raising questions about over-collection and user dignity. Ian explains that identity is how privacy controls are enforced, and that organizations need to ask what data they are collecting, what it represents, and how it should be protected.

The conversation covers mobile driver's licenses, biometric authentication, and government-backed digital ID programs. Ian raises concerns about fragmented identity systems that could create barriers to global access and digital inclusion. They also discuss challenges with age verification laws that translate physical-world practices poorly into online environments, often leading to excessive data demands.

Ian outlines how emerging AI systems acting on behalf of users present new identity challenges around authority, authentication, and accountability. He ties this to similar concerns around digital estate management, emphasizing the need for consistent identity frameworks across different contexts.

Closing the episode, Ian calls for an empathetic approach to designing identity systems, one that recognizes real-world conditions such as aging, accessibility needs, and unequal access to technology. Debbie and Ian agree that identity systems should be easy to use, respectful of users, and built to support everyone, not just tech-savvy individuals.

Support the show

Send us a text

In episode 239 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Saumya Gupta, Assistant Vice President for APAC and Japan at Platform 3 Solutions. Saumya brings a unique blend of deep technical expertise and strategic thinking to the conversation about data privacy in the modern enterprise. She and Debbie discuss how legacy systems represent one of the largest and most overlooked privacy risks—storing sensitive data long past its useful life and outside of governance controls. Saumya explains how data lake and lakehouse architectures can help businesses centralize, tag, and govern large volumes of structured and unstructured data more efficiently. She presents her open metadata model, a five-layer system that empowers organizations to classify data by technical properties, business relevance, operational quality, sensitivity, and compliance requirements. The conversation explores the collision between AI’s data hunger and privacy’s minimization mandate, and Saumya warns that enterprises cannot afford to ignore data lifecycle hygiene. They also discuss defensible deletion, audit readiness, and the importance of building data infrastructure with privacy as a foundational element. Saumya’s insights help organizations reframe legacy data not just as a cost center or liability, but as an opportunity to reset and future-proof their compliance strategies.

Support the show