In this episode, Debbie Reynolds “The Data Diva” speaks with Evan Benjamin, President of Tier 3 Inc., about the growing challenges of privacy in AI systems, particularly in relation to inference, agent-based systems, and data lifecycle management.
Evan shares his transition from IT, e-discovery, and information security into privacy, highlighting how the rapid adoption of large language models has exposed gaps in how organizations approach privacy and data protection. The conversation explores the distinction between security and privacy, emphasizing that security focuses on protecting systems while privacy focuses on purpose, data use, and fundamental rights.
Debbie and Evan discuss the risks associated with AI-driven inference, including how systems generate insights about individuals based on context and historical data, often without user awareness or control. They also examine how AI memory and agent-based systems can extend data usage beyond original intent, raising concerns about purpose limitation and data minimization.
The discussion further addresses challenges with data retention, logging, and traceability, as well as the difficulty of deleting data from AI systems once it has been incorporated into model training. Evan highlights the technical limitations of data erasure in machine learning models and the implications for privacy rights such as the right to be forgotten.
Finally, the conversation explores issues related to data processing across multiple systems, including the complexity of managing controllers, processors, and sub-processors, as well as emerging risks related to liability when organizations deploy AI systems and autonomous agents.
By popular demand, Debbie Reynolds Consulting is now offering executive briefings on emerging data privacy risks and how companies can avoid them. To learn more, visit the Executive briefings page on my website.
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Debbie Reynolds Consulting, LLC
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