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This Case Note starts by summarizing current federal law and existing litigation surrounding state legislation in the context of foreign campaign contributions. It then turns to the parallels between state and federal proposals and concludes with the potential avenues policymakers may use to avoid future constitutional challenges.

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.

District courts should consider the value of percolation in a given case as part of their analysis in deciding whether to grant a § 1404(a) motion. The value of doing so is even more pronounced in cases with a clear pattern of repeat-player defendants moving for transfer for no apparent reason other than convenience—and perhaps a more amenable court. In such cases, district courts should directly weigh the benefits of percolation against those of judicial economy.

At first glance, the Ninth Circuit’s decision in Isaacson v. Mayes (2023) set the stage for the perfect law review student comment. It called out the Eleventh Circuit’s decision in Bankshot Billiards, Inc. v. City of Ocala (2011) by name. And the Congressional Research Service listed Bankshot and Isaacson among 2023’s circuit splits. By all accounts, the two circuits had split over a significant issue. They disagreed over whether a party needs to connect its injury to a constitutional right in order to establish standing for claims under 42 U.S.C. § 1983. Only one problem remained: the courts were on the same page. What emerged was the specter of a circuit split.

This Case Note first provides a background on the doctrine of absolute immunity. It then evaluates the court’s analysis in Gay and compares Gay with the Third Circuit’s decision in Williams v. Consovoy (3d Cir. 2006). Finally, this Case Note argues that Gay is more consistent with Supreme Court precedent on absolute immunity and more in line with historical understandings of the doctrine. This issue has particularly high stakes, as psychologists’ medical role can create a “guise of objectivity.” As a result, even a biased psychologist might still receive strong deference from a judge and could then be the reason a person spends the rest of their life in prison.

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.

Artificial intelligence (AI) has the potential to alter the interpretation of the duties of care, skill, and diligence. As these duties form the foundation for the BJR and equivalent provisions, the development of AI is also expected to impact the BJR. There is a broadening importance, in an increasingly data-driven business environment, of the requirement to gather sufficient information before making a decision and to use information in a valid manner. Changes are both quantitative (how much information to collect) and qualitative (which types of information to collect). The changes also relate to the methods of decision-making, including the role of measures and statistics over intuition.

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.

This Essay explores the two holy grails of AI and the law: predicting court decisions and predicting contracts. While there is some overlap between the two, because in order to draft contracts one needs to know the law, both issues can be functionally distinguished. These two areas, and their importance in the context of increasing AI development, are explored more deeply within the context of corporate insolvency law.

This Essay focuses largely on structural responses to AI pricing in antitrust, outlining the bulk of its argument in the context of merger law but also considers monopolization law and exclusionary conduct. It argues that the relationship between the strictness of the law and the sophistication of AI pricing is not straightforward. In the short run, a stricter approach to merger review might well make sense, but as AI pricing becomes more sophisticated, merger policy ought to become less strict: if anticompetitive outcomes are inevitable with or without a merger because of highly sophisticated AI pricing, antitrust interventions to stop mergers will not affect pricing and instead will create social losses by impeding efficient acquisitions. This Essay considers similar questions in the context of monopolization. It concludes by observing that the rise of AI pricing will strengthen the case for antitrust law to shift its focus away from high prices and static allocative inefficiency and toward innovation and dynamic efficiency.

Causal AI is within reach. It has the potential to trigger nothing less than a conceptual revolution in the law. This Essay explains why and takes a cautious look into the crystal ball. Causation is an elusive concept in many disciplines—not only the law, but also science and statistics. Even the most up-to-date artificial intelligence systems do not “understand” causation, as they remain limited to the analysis of text and images. It is a long-standing statistical axiom that it is impossible to infer causation from the correlation of variables in datasets. This thwarts the extraction of causal relations from observational data. But important advances in computer science will enable us to distinguish between mere correlation and factual causation. At the same time, artificially intelligent systems are beginning to learn how to “think causally.”

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.