Rethinking Sensitive Data in the Age of AI

Building on CIPL’s ongoing work at the intersection of data protection, AI, and organizational accountability, our latest paper takes a deep dive into the evolving role of sensitive data in AI systems.

As AI technologies become more advanced and widely adopted, existing legal frameworks often restrict the use of sensitive data, even when it is essential for ensuring fairness and detecting bias. To address this, CIPL offers practical policy recommendations to facilitate and enable the responsible use of sensitive data in AI systems. The paper also includes multiple use cases across different contexts and sectors to illustrate the importance of sensitive data in AI applications.

CIPL’s Recommendations:

• Focus on sensitive uses of data, rather than sensitive categories of data
• Address legal gaps in the use of sensitive data for AI development and fairness
• Recognize and facilitate the role of sensitive data in bias detection
• Look for alternatives to consent as the sole legal basis for sensitive data processing
• Embed accountability through structured risk management
• Prioritize transparency and individual rights
• Implement robust input and output controls
• Require reasonable filtering for incidentally collected data, but not blanket prohibition

Rethinking Sensitive Data in the Age of AI

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