I’ve curated a list of recent works on privacy, AI, and tech that will be worth your time checking out. As I’m just launching this series, I have a backlog of recent works that I plan to include in future editions.
Alicia Solow-Niederman, The Supply Chain is a Circle: AI, Privacy, and People, 101 Notre Dame L. Rev. Reflection 29 (2026)
Another brilliant and insightful work by Solow-Niederman. She argues that AI governance focuses mostly on the entities developing AI systems rather than the users of them, and “this production-centered approach risks overlooking what happens when people use AI tools. That’s a mistake, because user interactions determine the real-world impact of AI.” She contends that “regulating AI and holding the appropriate actors responsible requires far more attention to what happens after deployment of an AI system.” Further, she argues: “Unless we account for the contextual ways that humans interact with AI systems on the ground, it is users who will bear the cost of harms, and our regulatory interventions will remain incomplete at best and pernicious at worst.”
Ted Chiang, “No, Artificial Intelligence Is Not Conscious,” The Atlantic (June 3, 2026)
Ted Chiang is a renowned sci-fi writer, author of STORY OF YOUR LIFE AND OTHERS (2002) and EXHALATION (2019), both of which are superb short story collections. Chiang recently wrote a terrific essay on AI in The Atlantic. A key quote:
Generative AI is harmful enough when we understand it as a conventional technology, but if we confuse fluency at generating text with consciousness or moral agency, we’re at risk of assigning responsibility to entirely the wrong parties whenever anyone uses a chatbot.
CARISSA VÉLIZ, PROPHECY: PREDICTION, POWER, AND THE FIGHT FOR THE FUTURE, FROM ANCIENT ORACLES TO AI (2026)
In her new book, Prophecy, Carissa Véliz provides a sophisticated account of attempts at prophecy, including today’s AI algorithmic predictions. Her book is highly engaging and filled with great anecdotes and examples. She combines accessible and lively prose with deep philosophical insights.
On AI predictions, Véliz argues that they “are fortune tellers, as opposed to truth tellers, and the ultimate prediction machine is also the ultimate bullshitter. . . . [A]lthough predictions appear to be descriptive claims, they are in fact veiled prescriptive assertions—they tell us how to act.”
I’ve written about AI predictions in my article with Yuki Matsumi: Hideyuki Matsumi & Daniel J. Solove, The Prediction Society: Algorithms and the Problems of Forecasting the Future, 2025 U. Ill. L. Rev. 1 (2025).
I also recently explored AI predictions in my Substack essay, Dangerous Oracles: Minority Report, Philip K. Dick, and AI Predictions.
Kashmir Hill and Aric Toler, “They Tried to Catch a Predator. They Trapped Themselves Instead.” N.Y. Times (June 10, 2026)
Hill and Toler’s article tells a harrowing story about life in today’s digital age, where vigilantes mete out “justice.” When these self-anointed warriors for justice are wrong, they can destroy lives.
I wrote about the dangers of online vigilantism nearly 20 years ago in my book, The Future of Reputation: Gossip, Rumor, and Privacy on the Internet (2007) (you can download a free PDF here). I predicted something like this happening:
Instead of enhancing social control and order, Internet shaming often careens out of control. It targets people without careful consideration of all the facts and punishes them for their supposed infractions without proportionality. Shaming becomes uncivil, moblike, and potentially subversive of the very social order that it tries to protect.
Sadly, my dystopian predictions are the ones coming true, not my more optimistic ones.
Neil M. Richards, Privacy Is Not Theft (June 3, 2026)
Richards’ essay discusses Dave Eggers’ novel, The Circle, which depicted an anti-privacy company that advanced the idea that “privacy is theft.” Richards’ essay draws from Jonathon Penney’s new book, Chilling Effects, to argue that “Penney’s work shows the hollowness of these curious suggestions that privacy is no longer a fundamental right but rather a kind of theft from the future, or at least a theft from people who think they are building a most excellent future for themselves and want your information as raw material to do that.”
Perla Khattar, Quantum Computing and Privacy (June 4, 2026)
Khattar argues that quantum computing threatens to render encrypted data today discernable tomorrow. In the abstract, she contends that “vast quantities of encrypted data collected today may become readable in the future once sufficiently powerful quantum systems emerge. This phenomenon—commonly described in technical literature as “harvest now, decrypt later”—creates what this Article conceptualizes as Deferred Privacy Breach: a condition in which privacy violations are probabilistic, delayed, and potentially inevitable.”
Current laws “evaluate security at the moment of data collection or breach, not across the lifespan of information. Quantum computing therefore exposes a mismatch between technological reality and legal doctrine, revealing that privacy law has long relied on an unstated premise of computational permanence.”
Theodore Christakis, You Trust Your Chatbot With Everything. Should You? (2026)
Professor Christakis has produced a very insightful two-part report on AI chatbots.
In Part 1: How the Controller Uses Your Chat Data, Christakis engages in an extensive examination and comparison of ChatGPT, Gemini, Claude, Grok, and DeepSeek. The study seeks to “map the internal privacy boundary of consumer chatbot conversations: how providers handle the data users entrust to them, where the protections fall short of what the interface invites users to expect, and what constraint-based alternatives could look like.” Christakis notes:
The findings do not reveal a landscape of abuse. They reveal a landscape of structural opacity. Every major provider now trains on consumer chats by default. Every provider reserves human access to conversations. Advertising has entered the chat, with personalisation enabled by default. And “no sale” commitments, however genuine, do not disclose the full scope of who may access a conversation inside the provider’s own supply chain.
In Part 2: Governments, Courts, and the Battle Over Your Chatbot Conversations, Christakis examines AI chatbot conversations in “the four places they can be exposed (police referral, government demand, civil discovery, data breach) and asks what should be done.” Although people speak to chatbots for legal or medical advice, chatbots are not shielded with the protections of relationships with lawyers or doctors. Christakis observes:
The very choices that make a chatbot useful (retention, memory, logging, personalisation, connected tools) are the choices that make the resulting record preservable, searchable, discoverable, disclosable and exploitable. A single stored conversation is, at the same moment, a candidate for police referral, a target for a government demand, evidence in a lawsuit, and an asset in a data breach. No prior work, to the author’s knowledge, has examined these four exposures together.
Both parts offer many recommendations for policy improvements.
Paul M. Schwartz, Data Privacy Federalism 3.0, 29 Chapman L. Rev. 465 (2026)
Schwartz continues his excellent scholarship on federal preemption, following up on his earlier piece, Preemption and Privacy. In this new short essay, he argues that federal privacy law shouldn’t be preemptive of state laws: “State lawmaking about data privacy is supported by the classic Brandeisian notion of the states as laboratories for innovative policymaking. In addition, there is the potential of states to serve as catalysts for bipartisan policy cooperation.”
Schwartz also argues:
There have also been important recent developments concerning the sharing of personal data among different levels of government. These changes significantly implicate the anti-commandeering doctrine. Data-driven unilateral actions by the Trump administration toward the states represent “agonistic federalism,” to use a term recently coined by Professors Aziz Huq and Zachary Clopton. The executive branch has engaged in a hostile attack on the states by weaponizing personal data collected through federal-state programs. In response, this Article proposes that anti-commandeering provisions should extend to personal information. The states should develop this constitutional doctrine as part of their opposition to the Trump administration’s seizures of personal data.
Chinmayi Sharma, Thomas Kadri, & Sam Adler, Brokering Safety, 114 Cal. L. Rev. 478 (2026)
Sharma, Kadri, and Adler have written a great article on how privacy law fails to protect victims who try to hide from their highly-dangerous abusers. They argue that “today, no number of name changes and relocations can prevent data brokers from sharing a victim’s personal information online. Thanks to brokers, abusers can find what they need with a single search, a few clicks, and a few dollars. For many victims, then, the best hope for safety lies in obscurity—that is, making themselves and their information harder to find.”
As they contend, the law is inept at addressing the situation:
[A] web of privacy laws props up a fragmented and opaque system that forces victims to navigate potentially hundreds of distinct opt-out processes, wait months for their information to be removed, and then repeat this process continuously to ensure their information doesn’t resurface. The status quo compels victims to manage their own privacy, placing the burden of maintaining obscurity on already-overburdened shoulders.
They propose a new regulatory regime to address these problems.
Woodrow Hartzog & Evan Seligner, On the Right to Obscurity, Cal. L. Rev. Online (June 2026)
In this essay, Hartzog and Selinger continue their terrific work on obscurity (here and here), plus previous work by Hartzog and Frederic Stutzman (here). In their latest essay on the topic, they reiterate their conclusion that “practical obscurity” is an essential and “underappreciated form of privacy.” Obscurity “allows us to live freely and with dignity.”
Hartzog and Selinger argue:
In this Essay, which reflects on Chinmayi Sharma, Thomas E. Kadri, and Sam Adler’s thoughtful and urgent article Brokering Safety, we argue in favor of a legally protected right to obscurity that is tied to human dignity and capabilities. Appealing to this organizing principle can help lawmakers better mitigate the ongoing obscurity harms that people suffer every day. Indeed, a right to obscurity grounded in human dignity and capabilities can anchor a robust approach to surveillance reform that includes interventions, ranging from procedural rules to outright bans. Crucially, it can offer robust justification for bespoke interventions, such as one proposed in Brokering Safety, that protects our most common but underappreciated form of privacy.
BART VAN DER SLOOT, FROM AUTONOMY TO AMBIGUITY: RECONFIGURING THE LEGAL LANDSCAPE IN THE AGE OF AI (2026)
Van der Sloot’s new book is brimming with wisdom. I loved it, and I wrote a blurb for it, which I quote below:
In this deeply philosophical and interdisciplinary book, Bart van der Sloot presents a sophisticated and nuanced account of human nature―one that is conflicted and in flux, complicated and elusive, ambiguous and paradoxical―and how modern technologies are wreaking havoc with the complex and confounding forces that push and pull within us. Brimming with insights, van der Sloot’s book shows how current regulation is far too simplistic for the complicated ways technology is affecting humanity.
Ifeoma Ajunwa, Ravi B. Parikh, & I. Glenn Cohen, When Patients Share Everything with an AI Chatbot: Risks and Opportunities of Large Language Models, JAMA (June 11, 2026)
This piece explores the dangers of using chatbots for healthcare and the lack of adequate legal protections. From the abstract:
The expansion of medical records by LLMs also raises new legal risks for patients. When a patient uploads their entire EHR to an LLM, is that information legally protected as private? The Health Information Portability and Accountability Act of 1996 (HIPAA) enables patients to get a copy of their EHR to feed to an LLM for a “digital second opinion” (45 CFR §164.524). However, because an LLM is not a “covered entity” within the meaning of HIPAA, once a patient uploads their EHR, HIPAA does not limit or regulate what the LLM or its developer can do with it.
I wrote about these issues in my post, AI Companies Should Have Information Fiduciary Duties.
* * * *
Daniel J. Solove is the Bernard Professor of Intellectual Property and Technology Law at the George Washington University Law School. He is the founder of TeachPrivacy, a company that provides workforce privacy, cybersecurity security, and AI training to companies and organizations around the world. He is the author of 10+ books and 100+ articles.
You can follow his events, writings, training, cartoons, and resources by subscribing to his free weekly newsletter.
Subscribe to Solove’s Free Substack
A supplement to Solove’s regular newsletter with more in-depth discussions
