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In episode 251 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Ilia Dubovtsev, Founder of Dub Consulting, joining from Moscow, Russia. he discussion centers on the complexities of privacy in the workplace and how emerging technologies, especially AI, are reshaping the boundaries of personal data and institutional responsibility. Ilia shares his framework for operationalizing privacy—built on the principles of accountability, fairness, and balancing interests, and explains why this model is essential when managing employee data in digitally driven environments.

Ilia shares his belief that privacy is the maximum expression of individual liberty. He developed a three-pillar framework for privacy programs: accountability, balance of interest, and fairness. He explains how these principles can be applied across jurisdictions, whether in Russia, Europe, or the United States. Despite the United States’ lack of a comprehensive federal privacy law, Ilia notes that core principles like non-discrimination and transparency often serve as common ground for workplace privacy protections.

Debbie and Ilia dive deep into the complexities of employee privacy, comparing regulatory and cultural variations. They acknowledge that workplace data, often governed by contract law, labor law, and surveillance practices, is uniquely sensitive because employees have fewer choices about whether and how their data is collected. The conversation shifts to the influence of AI in the workplace. Ilia envisions AI empowering employees by reducing dependency on traditional corporate structures, potentially shifting employer-employee dynamics to a more equitable “peer” relationship. He proposes a new privacy policy model that includes (1) transparent data practices, (2) distinct policy boundaries across employment stages, and (3) accessible remedies for challenging data misuse. Ilia stresses the need for literacy, both technical and legal, to protect workers and hold employers accountable.

The episode concludes with a thoughtful exchange on liberty, trust, and the potential of fair AI governance. Ilia emphasizes that privacy must be preserved through principled regulation and public education, rather than a proliferation of fragmented, burdensome rules. He cites the U.S. scholarly conversation around the “duty of loyalty” and calls for frameworks that ensure both data accountability and empowerment for individuals.

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