I’ve curated a list of recent works on privacy, AI, and tech that will be worth your time checking out. For earlier editions of Works Worth Your Attention, see here.
Privacy, AI, and Tech Works Worth Your Attention October 2026
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The AI Inference Problem in Privacy Law
Originally published as Daniel J. Solove The AI Inference Problem in Privacy Law, Wolters Kluwer Cybersecurity Policy Report (Oct. 19, 2026)
You can download a PDF of the piece here:
Abstract
AI provides an unprecedented ability to determine patterns in aggregated data which can produce inferences about people. There are two ways in which AI inferences undermine privacy laws. First, when AI allows inferences to be made, the inferred data is beyond what was disclosed to people in the privacy notice. Second, many privacy laws protect sensitive data differently from regular personal data. With AI inferences, sensitive data can readily be inferred from combining pieces of regular personal data. Determining which data should be classified as sensitive becomes nearly impossible. Whether they recognize inferences or not, privacy laws are in a bind. There is no easy escape from the AI inference problem. The laws must start to reckon with it.
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What’s AI Slop? What Should We Do About It?
I had a fascinating conversation with Jessica Silbey (BU Law) and Woodrow Hartzog (BU Law) about their thought-provoking article, AI Slop.
A few interesting relevant quotes:
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Disclosing AI Use in Writing Is Complicated
As scholars increasingly use AI in scholarly writing, journals and book publishers are starting to require disclosures of AI use. But these disclosures are sometimes unclear, difficult to comply with, and vague. How AI use affects article selection decisions remains uncertain.
I recently had terrific conversation about these issues with Andrew Guthrie Ferguson (GW Law) who looked into law review AI disclosure requirements.
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Rethinking Privacy of the Mind: Why Protecting Neural Data Is Insufficient
I recently wrote a new short essay: Daniel J. Solove Rethinking Privacy of the Mind: Why Protecting Neural Data Is Insufficient, Wolters Kluwer Cybersecurity Policy Report (Oct. 6, 2026).
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AI in Scholarship: Yes, Sometimes, or Never?
To what extent should AI be used in scholarship? Which uses are okay? Which aren’t? Should AI ever be used? What impact will AI have on scholarship in the future?
I recently had a very insightful conversation about these issues with Nita Farahany (Duke Law) and Orin Kerr (Stanford Law).
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Meaningful Data Minimization
I recently posted a new paper draft co-authored with Professor Woodrow Hartzog: Meaningful Data Minimization. You can download it here for free. We welcome your feedback.
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Teaching AI Law
I recently had a very insightful conversation with a group of professors who teach AI law or related tech law topics. Below, I’ll provide some resources related to our conversation. First, here’s our discussion:
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Teaching AI Law – Video
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Silicon Valley’s Hilarious COPPA Scene
In the terrific comedy TV series, Silicon Valley (2014-2019), there’s a classic scene for privacy law nerds. The show depicts the world of Silicon Valley and the culture of the tech industry. The show illustrates the frenetic pace of building a tech startup, the frequent pivots and existential moments, the constant quest for funding, and the ruthless competition. The potential harms of technologies are often ignored in the potent quest for power and success.
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