I had a great conversation with Professors Andrew Ferguson (GW Law) and Paul Ohm (Georgetown Law) about Chatrie v. United States (U.S. June 29, 2026).
Quick takes from the conversation:
When Can the Government Get Your Data?
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When Can the Government Get Your Data? – Video
Watch my discussion with Andrew Ferguson (GW Law) and Paul Ohm (Georgetown Law) about the Chatrie v. US, the most important 4th Amendment case of the decade.
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AI Governance: Ethics, Strategy, Law Practical AI Governance
Is it possible to govern AI? How?
Watch my discussion with Shoshana Rosenberg about AI governance. Rosenberg is a partner/practice lead/AI director at OlenderFeldman LLP and founder of SafePorter, a privacy design feedback platform. She’s also a co-founder of Women in AI Governance.
We discuss:
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Tiger King vs. AI Tiger King
The law treats AI (and many digital technologies) with a special exceptionalism. AI evades rules that apply to nearly everything else.
For example, recent news stories discussed incidents where AI “escaped” and “acted on its own” to commit cyberattacks. I saw the initial reaction all across the media, where the sentiment was: Wow, AI is becoming so dangerous and powerful! AI could become autonomous and escape our control.
This response evokes the movie, The Terminator (1984), where AI tries to wipe out humanity.
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The Economics of Privacy
Originally Posted on Substack
In this video, I interview Alessandro Acquisti (MIT) about his pathbreaking work on the economics of privacy. Topics include the privacy paradox, the value of personal data, attitudes and behaviors, and the impact of laws. Here are a just few of Acquisti’s many works that I find interesting:
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AI Governance: Ethics, Strategy, Law – Video
Watch Daniel Solove’s discussion with Shoshana Rosenberg (OlenderFeldman LLP and SafePorter) about AI governance. Rosenberg is the author of Practical AI Governance: Building a Program for Oversight and Strategy (2026).
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Privacy, AI, and Tech Works Worth Your Attention October 2026
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.
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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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