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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.
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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.
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