Regulation

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Comment
Volume 93.4
When a Mass Resignation Becomes a Merger: Rethinking Asset Acquisitions for the AI Era
Nina Fridman
B.A. 2022, Northwestern University; J.D. Candidate 2027, The University of Chicago Law School.

I would like to thank Professors Douglas Baird and Eric Posner for their thoughtful advice and insight and the members of The University of Chicago Law Review for their invaluable feedback and edits.

This Comment argues “reverse acquihires”—deals in which a Big Tech firm poaches an AI startup’s team and then paysits shell hundreds of millions—constitute asset acquisitions subject to Hart-Scott-Rodino (HSR) Act review. While regulators typically review only tangible asset acquisitions under the Act, this Comment argues that regulators can mandate review of certain intangible asset transfers as well. Drawing on regulatory treatment of intellectual property licensing agreements, language from divestiture orders, and guidance from foreign competition authorities, this Comment demonstrates that reverse acquihires are acquisitions of AI startups’ most valuable assets: their business information and know-how.

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Essay
Second Chances and the Second Amendment: A Smarter Way to Reboot § 925(c)
Ian Ayres
Ian Ayres is the Oscar M. Ruebhausen Professor of Law at Yale Law School. The authors thank Iris Chen, Mingyi Hua, Jiyoung Kim, Jacob Slaughter and Sam Zou for their research assistance.
Fredrick E. Vars
Fredrick E. Vars is the Robert W. Hodgkins Chairholder of Law at the University of Alabama School of Law.

In February of this year, we published a call for the government to relaunch the federal Gun Control Act’s § 925(c) petition process, which empowers anyone subject to a federal restriction (“disability”) on their ability to purchase or possess firearms to apply to the Department of Justice for restoration of their gun rights.

The Trump Justice Department has moved with some dispatch to relaunch the program—using a workaround we suggested in our piece. In this short Essay, we propose several improvements to the proposed regulation.

Online
Essay
Tiktok Bans: A Takings Clause Blunder?
Bridget Gilchrist
Bridget Gilchrist is a J.D. Candidate at the University of Chicago Law School, Class of 2025.

She thanks Henry Gilchrist, Timothy Burke, Kimberly Burke, and Alexis Berg for their support, and the University of Chicago Law Review Online team for all their hard work.

This Case Note explores the possibility that, in a world where TikTok is banned or heavily regulated, individual TikTok users could sue states under a Takings Clause theory. Any such cases would have to wrestle with two core questions (1) whether the account holders hold an actionable property interest in their accounts; and (2) if so, whether permanently and totally depriving users of access to their accounts constitutes a taking.

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Snow, Rain, and Theft: The Limits of U.S. Postal Service Liability Under the Federal Tort Claims Act
Margaret Schaack
Margaret Schaack is a J.D. Candidate at the University of Chicago Law School, Class of 2026.

The author thanks the University of Chicago Law Review Online team for their helpful feedback.

This Case Note first reviews the origins of the postal-matter exception and the FTCA. Then, it analyzes the Fifth Circuit’s holding in Konan and explores contrasting precedent in other circuits, most notably in the First and Second Circuits. Finally, this Note discusses the difficulty of balancing USPS’s interests against enabling suits under the FTCA and considers the implications of providing a tort remedy.

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Essay
How Artificial Intelligence Will Shape Securities Regulation
Gabriel V. Rauterberg
Professor of Law, University of Michigan

My views on these subjects owe much to my collaborators, especially Michael Barr, Megan Shearer, and Michael Wellman, with whom I have been studying the behavior of algorithmic traders in financial markets, and Howell Jackson, with whom I have been presenting on social media and capital markets at PIFS-IOSCO’s trainings for securities regulators. All errors are my own. Thanks to the participants at the University of Chicago’s Symposium on “How AI Will Change the Law” for helpful comments, and to the editors of the University of Chicago Law Review for their helpful insights.

This Essay argues that the increasing prevalence and sophistication of artificial intelligence (AI) will push securities regulation toward a more systems-oriented approach. This approach will replace securities law’s emphasis, in areas like manipulation, on forms of enforcement targeted at specific individuals and accompanied by punitive sanctions with a greater focus on ex ante rules designed to shape an ecology of actors and information.

Online
Essay
Automation Rights: How to Rationally Design Humans-Out-of-the-Loop Law
Orly Lobel
Orly Lobel is the Warren Distinguished Professor of Law and Director of the Center for Employment and Labor Policy (CELP) at the University of San Diego.

She graduated from Tel-Aviv University and Harvard Law School. Named as one of the most cited legal scholars in the United States, and specifically the most cited scholar in employment law and one of the most cited in law and technology, she is influential in her field. Professor Lobel has served on President Obama’s policy team on innovation and labor market competition, has advised the Federal Trade Commission (FTC), and has published multiple books to critical acclaim. Her latest book, The Equality Machine, is an Economist Best Book of the Year.  

This Essay argues for the development of more robust—and balanced—law that focuses not only on the risks, but also the potential, that AI brings. In turn, it argues that there is a need to develop a framework for laws and policies that incentivize and, at times, mandate transitions to AI-based automation. Automation rights—the right to demand and the duty to deploy AI-based technology when it outperforms human-based action—should become part of the legal landscape. A rational analysis of the costs and benefits of AI deployment would suggest that certain high-stakes circumstances compel automation because of the high costs and risks of not adopting the best available technologies. Inevitably, the rapid advancements in machine learning will mean that law soon must embrace AI; accelerate deployment; and, under certain circumstances, prohibit human intervention as a matter of fairness, welfare, and justice.