Faculty Bibliography

How do private law institutions of developing countries differ from those of developed countries? A common view is that the legal systems of the Global South are often outdated, failed transplants of Global North models, or plagued by enforcement challenges. This book project offers a different perspective by focusing on legal innovation and adaptation in the Global South. We examine how countries in the Global South have embraced legal doctrines and solutions that deviate from approaches that currently hold the status of orthodoxy in richer countries, and pursue distinct and potentially broader public policy objectives or reflect different values, in response to conditions that are commonplace in developing countries. Our analysis points to reasons why the legacy of colonialism, limited fiscal capacity, economic dependence on richer countries and macro-economic volatility may encourage lawmakers in poor countries to develop heterodox doctrines. We explore different manifestations of legal heterodoxy across various areas of private law in a range of countries in the Global South. Recognizing legal heterodoxies in the Global South enlarges our understanding of legal experiences and possibilities, and contributes to our understanding about the driving forces and direction of legal evolution around the world.

Food waste is a major contributor to climate change and a barrier to environmental sustainability. As such, reducing food waste is estimated to be one of the most promising strategies to reverse global warming. One way to address food waste is to implement effective policies, which requires an understanding of the impact of current policies on food waste and other relevant outcomes. The current study examined the impact of United States (U.S.) states’ date label policies on food waste and foodborne illness. We found that states with more date label restrictions had greater waste, but this effect was not significant. In addition, date label restrictions and foodborne illness were not related. This shows that current date label policies do not help to reduce food waste or improve public health. In other words, current U.S. state food waste policies do not promote sustainability. We discuss the implications for date label policy content and offer future research directions.

Ruth Stout didn’t plow, dig, water, or weed—and now her “no-work” method is everywhere. But behind her secret to the perfect garden lay other secrets.

This Viewpoint discusses prospects for populating the regulatory landscape for health and health care AI in the coming years.

This study explores preferences for algorithmic versus human decision-making across six countries using nationally representative samples. Participants evaluated ten decision scenarios, typically involving serious risks of one or another kind, in which they choose between algorithmic or human decision-makers under varying informational conditions: baseline (no additional information), brief information about the expertise of the human decision-maker, brief information about the algorithm's data-driven foundation, and a combination of both. Across all countries, a strong majority preferred human decision-making. A brief account of the expertise of the human decision maker increased that majority percentage only modestly (by three percentage points). A brief account of the data on which the algorithm relies significantly reduced the size of the majority preferring the human decisionmaker (by eleven percentage points). When information about both the human and the algorithm was provided, the size of the majority preferring the human decisionmaker was also significantly reduced (by eight percentage points). Other variables, above all prior experience with algorithms, were correlated with increases or decreases in the size of the majority favouring human decision-maker or the algorithm. Prior experiences were significantly correlated with preferences, with positive interactions reversing the baseline preference for human decisionmakers when algorithmic information was provided. Methodological robustness was ensured through OLS-, Logit-, and Poisson regression, as well as Random Forest analyses. The findings suggest that informational interventions alone have a relatively modest effect on algorithm acceptance.

At defining points in American history, there have been massive shifts in constitutional understandings, doctrines, and practices. Apparently settled principles, and widely accepted approaches, are discarded as erroneous, even illegitimate, in favor of new principles and approaches. Less momentously, views that were once considered unthinkable do not quite become the law on the ground but instead come to be seen as plausible and part of the mainstream. Relatedly, Americans transform how they talk and think about their Constitution-its core commitments and underlying narratives-and those transformations change our practices. These radical, dizzying changes often trigger what we term a sense of "constitutional vertigo." Our goal is to provide a conceptual map and to describe how and why constitutional vertigo occurs. First, we ask whether theories of interpretation trigger radical change or whether desires for radical change impel people to generate new (or modify old) theories of interpretation. Second, we explore why so many people experience a form of vertigo. Third, we investigate the drivers of radical constitutional change, both the familiar bottom-up pressures from "We the People" and the less-familiar top-down approaches, where legal elites back and impose a new constitutional regime. Given that the Roberts Court's changes have triggered widespread vertigo, it is an apt moment to theorize about the phenomenon writ large.

Whether social media platforms increase well-being can be explored from multiple angles. Three empirical studies raise corresponding puzzles, with implications for valuation, choice, and well-being in general. The first finds that people are willing to pay far less to use social media platforms than they would demand to stop using them. The second finds that people lose welfare from using Facebook, and that Facebook users become more anxious and depressed, but that even after experiencing a good month without Facebook, they would demand a significant amount of money to stop using the platform for an additional month. The third finds that while many people would demand a significant amount of money to stop using Instagram and Tik Tok, they would also be willing to pay to eliminate Instagram and Tik Tok from their community. Each of the three puzzles has a plausible solution, but we do not yet know the ground truth. A reasonable conclusion is that people would demand a lot of money to be excluded from social media networks, which suggests that inclusion confers significant benefits, contingent on their existence – but that if social media networks did not exist, many users would be better off. This conclusion has broad implications; it suggests that people often spend time or money on goods whose existence they deplore. The three puzzles offer broad lessons for choice and welfare, and for how to think about their relationship.

Many policies take the form of nudges, defined as liberty-preserving approaches that steer people in particular directions, but that also allow them to go their own way Some nudges attempt to correct self-control problems. Some nudges attempt to counteract unrealistic optimism. Some nudges attempt to correct present bias. Some nudges attempt to correct market failures, as when people are nudged not to emit air pollution. For every conventional market failure, there is a potential nudge. For every behavioral bias (optimistic bias, present bias, availability bias, limited attention), there is a responsive nudge. There are many misconceptions about nudges and nudging, and they are a diversion.

Both free markets and government regulators tend to use willingness to pay (WTP) as the measure of value of goods that people do not own, and willingness to accept (WTA) as the measure of value of goods that people do own. The challenge is WTP and WTA are not perfect proxies for the welfare effects of buying or selling goods, especially when people do not have experience with those goods. The reason for use of WTP and WTA is not that they are perfect, but that they seem to be the best and the most administrable method for capturing the relevant welfare effects. At the same time, WTP and WTA might be infected by a lack of information, by behavioral biases, and by hedonic forecasting errors (all of these might be either cured or aggravated by market processes). Challenges also arise when WTP is low because people do not have money and when distributional weights might be necessary to align WTP or WTA with welfare effects. There are questions about how to proceed when WTA is much higher than WTP for the same goods; the WTP-WTA disparity has yet to be fully understood. These questions are especially challenging when valuing environmental amenities, animal welfare, and social media.

Picture a community torn over a proposed zoning law. Some are angry, others defensive, and misunderstandings abound. On social media, they broadcast insults at one another; every nuanced perspective is reduced to a viral soundbite. Yet, when they meet face-to-face and start speaking, something changes: residents begin listening more than speaking, and people begin testing ideas together. Misunderstandings fade, and trust begins to form. By the end of their discussion, they have not only softened their hostility, but discovered actionable plans that benefit everyone. This is the kind of meaningful discourse our society desperately needs. Yet our digital platforms -- designed primarily for maximizing engagement through provocative content -- have pulled us away from these core community endeavours. As a constructive path forward, we introduce the idea of conversation networks as a basis for civic communication infrastructure that combines interoperable digital apps with the thoughtful integration of AI guided by human agency.

People often judge how embarrassing an activity or condition is on the basis of its perceived prevalence. They infer prevalence in part by considering how often they hear other people discussing it. But how often a condition is discussed is a function not only of its prevalence but also of how embarrassing it is. If people fail to take this into account, they will tend to judge embarrassing conditions as being rarer, which will accentuate their embarrassment, and, in turn, further amplify their reluctance to disclose those conditions - a "spiral" of shame and silence. We present results from two studies that support the existence of such a feedback process. The first, a cross-sectional survey study, asked respondents a series of questions about different embarrassing and non-embarrassing conditions. Respondents (1) indicated whether they had the conditions, (2) judged how embarrassing the conditions were, (3) reported whether they had disclosed, or would disclose, having the conditions to others, and (4) estimated what fraction of survey respondents had the conditions. As predicted, reports of disclosure were negatively related to judgments of embarrassment, and when embarrassment was greater, estimates of prevalence were lower, both for conditions that respondents had and for conditions they did not have. The second, an experimental study, manipulated whether people received a high or low estimate of population prevalence for 5 different conditions, and found that receiving a high prevalence estimate reduced embarrassment and increased self-reported willingness to disclose the condition to others, and vice versa.

If you're injuring someone, you should stop—and pay for the damage you've caused. Why, this book asks, does this simple proposition, generally accepted, not apply to climate change? In Climate Justice, a bracing challenge to status quo thinking on the ethics of climate change, renowned author and legal scholar Cass Sunstein clearly frames what's at stake and lays out the moral imperative: When it comes to climate change, everyone must be counted equally, regardless of when they live or where they live—which means that wealthy nations, which have disproportionately benefited from greenhouse gas emissions, are obliged to help future generations and people in poor nations that are particularly vulnerable. Invoking principles of corrective justice and distributive justice, Sunstein argues that rich countries should pay for the harms they have caused and that all of us are obliged to take steps to protect future generations from serious climate-related damage. He shows how “choice engines,” informed by artificial intelligence, can enable people to save money and to reduce the harms they produce. The book casts new light on the “social cost of carbon,”—the most important number in climate change debates—and explains how intergenerational neutrality and international neutrality can help all nations, crucially the United States and China, do what must be done.

The magazine has three golden rules: never write about writers, editors, or the magazine. On the occasion of our hundredth anniversary, we’re breaking them all.

Merger review should reflect basic precepts of decision analysis, best practices in industrial organization economics, and teachings from related fields. Unfortunately, the analytical methods in modern merger guidelines fall short. Protocols violate standard prescriptions for information collection and decision-making, rely on a market definition paradigm that deviates significantly from core models of competitive interaction, fail to leverage central advances in understanding the efficiency consequences of mergers, and contravene or ignore fundamental dynamics relating to entry. This article elaborates correct analysis and contrasts it with that embodied in modern merger guidelines generally employed throughout the developed world, including the 2023 Merger Guidelines revision in the United States.

This paper examines the impact of defense counsel at first appearance (CAFA) on criminal justice outcomes using randomized control trials in two Texas counties. The study evaluates the influence of CAFA on bond amounts, pretrial release, conditions, and post-magistration outcomes such as recidivism and failure to appear. Results show that while CAFA reduces bond amounts and influences bond types in one jurisdiction, its effects on pretrial release and recidivism are limited. These findings highlight jurisdictional differences and suggest that CAFA’s impact may be more modest than previous studies indicate, underscoring the need for further research in this area.

A workaround is a maneuver that seems, on its face, consistent with the formal rules, but that employs those rules in an unanticipated way to circumvent a legal obstacle. Though some workarounds are tolerated or even celebrated, workarounds (and proposed workarounds) often provoke instinctive skepticism or hostility. When, if ever, is such skepticism justified? Do workarounds raise distinctive legal or public policy concerns? This Article seeks to provide a systematic normative assessment of workarounds in American public law. We argue, first, that from a general public interest perspective, the desirability of a workaround depends primarily on the desirability of the rule that is being worked around. Put simply, workarounds will typically advance the public interest when the legal obstacle being worked around does more harm than good, while workarounds will set back the public interest when the obstacle being worked around serves an important public purpose. Other objections to workarounds—for example, that they will erode government legitimacy, weaken norms of self-restraint, undermine the credibility of government commitments, or sap energy for more substantial reforms—are either empirically implausible or relatively insignificant when compared to the first-order question of whether the obstacle being circumvented is itself in the public interest. Questions concerning the legality of workarounds raise different issues. While adjudicators who emphasize the primacy of legal text should have no intrinsic objections to workarounds as such, adjudicators who place significant weight on fidelity to the purposes or functions of legal rules (or rule systems) should embrace an anti-workaround presumption. But this presumption can and should be overcome in certain cases. Most significantly - and perhaps most controversially—we argue that the anti-workaround presumption should give way when the obstacle that the challenged workaround would sidestep is itself inconsistent with the larger purposes of the rule system. The question should not be whether the alleged workaround, viewed in isolation, is inconsistent with the purposes of the relevant rules, but whether the combination of obstacle and workaround, considered together, is more inconsistent with the purposes of those rules than the obstacle standing alone. Therefore, even strong purposivists might embrace certain workarounds—including workarounds to the Senate filibuster, the statutory debt ceiling, and the Electoral College.

A great deal of work in behavioral science emphasizes that statistical predictions often outperform clinical predictions. Formulas tend to do better than people do, and algorithms tend to outperform human beings, including experts. One reason is that algorithms do not show inconsistency or “noise”; another reason is that they are often free from cognitive biases. These points have broad implications for risk assessment in domains that include health, safety, and the environment. Still, there is evidence that many people distrust algorithms and would prefer a human decisionmaker. We offer a set of preliminary findings about how a tested population chooses between a human being and an algorithm. In a simple choice between the two across diverse settings, people are about equally divided in their preference. We also find that that a significant number of people are willing to shift in favor of algorithms when they learn something about them, but also that a significant number of people are unmoved by the relevant information. These findings have implications for current findings about “algorithm aversion” and “algorithm appreciation.”

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53% of institutions identified data security as a primary concern, followed by lack of clinician trust (50%) and AI bias (44%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.

The field of artificial intelligence (AI) has entered a new cycle of intense opportunity, fueled by advances in deep learning, including generative AI. Applications of recent advances affect many aspects of everyday life, yet nowhere is it more important to use this technology safely, effectively, and equitably than in health and health care. Here, as part of the National Academy of Medicine’s Vital Directions for Health and Health Care: Priorities for 2025 initiative, which is designed to provide guidance on pressing health care issues for the incoming presidential administration, we describe the steps needed to achieve these goals. We focus on four strategic areas: ensuring safe, effective, and trustworthy use of AI; promotion and development of an AI-competent health care workforce; investing in AI research to support the science, practice, and delivery of health and health care; and promotion of policies and procedures to clarify AI liability and responsibilities.

In this response to a recent symposium on Common Good Constitutionalism in the American Journal of Jurisprudence, I principally take up themes related to democracy, disagreement, pluralism, and authority. I emphasize that the classical legal tradition is teleological, oriented to performance standards rather than design standards. Thus it does not attempt to prescribe an identical set of constitutional and institutional arrangements for all polities everywhere, but asks whether constitutional arrangements are ordered to the common good and (thus) compatible with natural and divine law. Subject to those conditions, political authority is natural, inevitable, inescapable, and good. The possibility of social and political disagreement is just a precondition for all law, not an objection to the classical legal framework. None of this entails judicial supremacism in any form, which the classical legal tradition squarely rejects.

People are said to show “algorithm aversion” when they prefer human forecasters or decision-makers to algorithms, even though algorithms generally outperform people (in forecasting accuracy and/or optimal decision-making in furtherance of a specified goal). Algorithm aversion also has “softer” forms, as when people prefer human forecasters or decision-makers to algorithms in the abstract, without having clear evidence about comparative performance. Algorithm aversion has strong implications for policy and law; it suggests that those who seek to use algorithms, such as officials in federal agencies, might face serious public resistance. Algorithm aversion is a product of diverse mechanisms, including (1) a desire for agency; (2) a negative moral or emotional reaction to judgment by algorithms; (3) a belief that certain human experts have unique knowledge, unlikely to be held or used by algorithms; (4) ignorance about why algorithms perform well; and (5) asymmetrical forgiveness, or a larger negative reaction to algorithmic error than to human error. An understanding of the various mechanisms provides some clues about how to overcome algorithm aversion, and also of its boundary conditions. These clues bear on the numerous decisions in law and policy, including those of federal agencies (such as the Department of Homeland Security and the Internal Revenue Service) and those involved in the criminal justice system (such as those thinking about using algorithms for bail decisions).

Chapter 11 was widely viewed as a failure in the first decade of the Bankruptcy Code’s operation, the 1980s. Large firms were mired in bankruptcy for years; the process was seen as expensive, inaccurate, and subject to abuse. While basic bankruptcy still has its critics and few would say it works perfectly, the contrast with bankruptcy today is stark: bankruptcies that took years in the 1980s take months in the 2020s. Multiple changes explain bankruptcy’s success—creditor learning, statutory reform, better judging and lawyering, new techniques, fuller integration of the improved mechanisms that the 1978 Code added—and we do not challenge their relevance. But in our analysis, one major change is missing from the current understanding of bankruptcy’s success: bankruptcy courts and practice in the 1980s rejected market value; today bankruptcy courts and practice accept and use market value. This shift is a major explanation for bankruptcy’s success. It reduces opportunities for conflict in bankruptcy. It speeds up proceedings. It allows firms to be repositioned in market transactions. Deals among claimants and interests are more readily reached and the firm can ride through bankruptcy without the bankruptcy process materially scarring the enterprise. This switch to market values has multiple channels: more whole-firm sales, wider and deeper access to financing for bidders and bankrupts, growing judicial deference to market valuations, and a bigger and more sophisticated private equity and distressed debt industry that buys bankrupt companies and their securities. We argue that valuation improvements explain much of the increased speed and efficiency of Chapter 11 practice over the decades. We provide evidence that valuation conflicts narrowed and that the corporate reorganization process accelerated. This market-based-valuation result has implications for bankruptcy law reform around the world. Several European and Asian nations have looked to Chapter 11 to model their own restructuring laws. We urge caution. Chapter 11 works best in conjunction with institutions that facilitate market valuation and market transactions. The United States developed such institutions only in recent decades; many nations have not developed them yet. Chapter 11 went from being viewed by many as a deficient legal structure in the 1980s to a substantial success story by the twenty-first century. The switch to market thinking across the bankruptcy spectrum—in bankruptcy transactions, in judging, and in lawyering—goes far in explaining why.

Does Congress have authority to pass legislation regulating the counting of electoral votes? This is a consequential question for the legal framework governing presidential elections. In 2022, Congress passed the Electoral Count Reform Act ("ECRA"), which overhauled the statutory regime governing the counting of electoral votes. The ECRA's predecessor statute, which had been in place since 1887, had long been criticized as ambiguous and unnecessarily convoluted. Those deficiencies were widely seen as a contributing cause of the attacks on the Capitol of January 6, 2021, and a rare bipartisan majority in Congress passed the ECRA to address the earlier statute's shortcomings. Yet it did so against a backdrop of unresolved questions about Congress's authority to legislate in this area. The scholarly literature, however, lacks a sustained defense of Congress's power to regulate the counting of electoral votes. This Article aims to fill that gap. It does so in two ways. First, it engages with the skeptics of Congress's authority on their traditional terrain, locating ample congressional authority grounded in the text, structure, and history of Article II and the Twelfth Amendment. The Article then seeks to expand the analytic framework by focusing on a constitutional provision that tends to stay out of the limelight: the Twentieth Amendment, which reconfigures the period between Election Day and Inauguration Day. In defending Congress's authority to pass laws regulating the counting of electoral votes, this Article provides the first scholarly treatment of the Twentieth Amendment's significance in this area.

In the current era, product differentiation is increasing; it is often fueled by big data and artificial intelligence (AI). Whereas product differentiation is generally welfare enhancing when consumers are informed and fully rational, such differentiation might reduce welfare when consumers suffer from misperceptions, either because of a lack of information or because of behavioral biases. We show that the positive and normative implications of product differentiation depend on whether consumers over or underestimate the benefits from some products. In particular, overestimation of the benefits is a potential source of significant welfare losses. We also study sellers’ incentives to promote, or combat, misperception. Our analysis can inform policymakers who are debating regulation that can make product differentiation more difficult (or easier), especially when the differentiation is instigated by AI algorithms powered by big data.

Millions in the United States have criminal records. Many of these records are eligible for some sort of concealment from public view, commonly known as expungement or sealing. In this Article, we analyzed criminal records in four counties in Pennsylvania and several counties in Kansas to determine the number of records eligible for such remedies. In Pennsylvania, the analysis included both expungement, defined here as petition-based suppression of information, and sealing, defined here as suppression that the government (usually the judicial system) undertakes without petitions. Kansas law only allows for petition-based expungement. Our analysis found approximately 100,000 charges eligible for expungement in Kansas and 180,000 charges eligible for expungement in Pennsylvania, supporting prior research that identified a so-called “second chance gap.” Our primary contribution is an analysis of which statutory reforms would render the largest number of cases or charges eligible for a record-clearing remedy. We found that elimination of criteria related to legally imposed financial obligations (“LIFOs”) would render a surprising number of files eligible for information suppression. In addition, our analysis identified approximately 200,000 charges that were eligible for sealing in Pennsylvania but were still available to the public online at the time of the data retrieval. This finding suggests that even when the government undertakes information suppression from its own databases, it finds the task challenging. Finally, we examine why certain records were not eligible for expungement or sealing in each state. This insight will inform legislatures and activists where their efforts can be most effective.

Do people like financial nudges? To answer that question we conducted a pre-registered survey presenting people with 36 hypothetical scenarios describing financial interventions. We varied levels of transparency (i.e., explaining how the interventions worked), framing (interventions framed in terms of spending, or saving), and ‘System’ (interventions could target either System 1 or System 2). Participants were a random sample of 2,100 people drawn from a representative Australian population. All financial interventions were tested across six dependent variables: approval, benefit, ethics, manipulation, the likelihood of use, as well as the likelihood of use if the intervention were to be proposed by a bank. Results indicate that people generally approve of financial interventions, rating them as neutral to positive across all dependent variables (except for manipulation, which was reverse coded). We find effects of framing and System. People have strong and significant preferences for System 2 interventions, and interventions framed in terms of savings. Transparency was not found to have a significant impact on how people rate financial interventions. Financial interventions continue to be rated positive, regardless of the messenger. Looking at demographics, we find that participants who were female, younger, living in metro areas and earning higher incomes were most likely to favor financial interventions, and this effect is especially strong for those aged under 45. We discuss the implications for these results as applied to the financial sector.

Sometimes legal systems are “noisy”; they show unjustified variability or “scatter,” which means that what emerges is likely to be unpredictable and unfair. Potential examples include assessment of whether a risk is “significant” or “unreasonable,” fines for environmental harms or safety violations, compensatory damage awards for libel, pain and suffering, hedonic losses, and sexual harassment, and punitive damage awards for corporate wrongdoing. To understand why and when law is noisy, it is useful to note that psychologists commonly distinguish between two kinds of scales: category scales and magnitude scales. Category scales are bounded and anchored in verbal descriptions at specified points. By contrast, magnitude scales are unbounded and defined by a meaningful zero point. In some settings, money might operate as a magnitude scale. For purposes of policy and law, here are the two key psychological findings. First, judgments on magnitude scales are often highly variable, or noisy, when there is no “modulus” to define the various points. The variability occurs even when there is no reason to believe that people actually disagree about anything meaningful. Second, distributions of judgments are “positively skewed,” with a long right tail. People involved in law and policy often use magnitude scales, above all money. High levels of noise, and susceptibility to bias (especially from anchors), are likely results. This is the problem of “noisy law,” an insufficiently explored area of behavioral public policy. Theories of optimal deterrence might help to reduce noise, but many policymakers, and many people involved in law and policy, do not accept those theories.

Since the 1980s, the Supreme Court’s decisions involving the permissible uses of non–Article III federal tribunals have repeatedly invoked two competing theories. A “historical-exceptions” or “formalist” model would insist that only Article III judges can exercise federal adjudicative power except in three categories of cases that history marks as exceptional. A rival approach, often labeled “functionalism,” would allow further deviations from the historical norm if they are supported by sound practical justifications and do not threaten the fundamental role of the Article III judiciary within the separation of powers. This Article explores the relationship between theory and practice in explaining why neither the historical-exceptions nor the functionalist paradigm has prevailed entirely over the other despite the vastly greater appeal of the former, when viewed in the abstract, to an increasingly originalist Court.

This Article examines the striking parallels between contemporary privacy challenges and past public health crises involving tobacco, processed foods, and opioids. Despite surging state and federal privacy legislation, many of these new privacy law and policy activities follow familiar patterns: an emphasis on individual choice, narrowly defined rights and remedies, and a lack of holistic accounting of how privacy incursions affect society as a whole. We argue instead for a salutary shift in privacy law and advocacy: understanding privacy through the lens of public health.  By tracing systemic factors that allowed industries to repeatedly subvert public welfare—from information asymmetries and regulatory capture to narratives of individual responsibility—we explore a fundamental rethinking of privacy protection. Our analysis of case studies reveals remarkable similarities between public health challenges of the past half-century or so and the ongoing consumer privacy crisis. We explore how public health frameworks emphasizing preventative policies and reshaping social norms around individual choices could inform privacy advocacy. To do so, we examine a spectrum of proposals to align privacy with public health, from adopting public health insights to provocatively reframing privacy violations as an epidemic threatening basic wellbeing. This Article offers a novel framework for addressing the current privacy crisis, drawing on the rich history and strategies of public health. In reframing privacy violations as a societal health issue rather than a matter of consumer choice, we see new avenues for effective regulation and protection. Our proposed approach not only aligns with successful public health interventions of the past but also provides a more holistic and proactive stance towards safeguarding privacy in the digital age.

Research on psychedelic medicines is experiencing a revival. Some clinicians, scientists, and ethicists believe that psychedelics are so different from other treatments that they warrant special consideration in how they are researched, regulated, commercialized, and administered. Others argue that psychedelic medicines show clinical potential, but they should be treated like other medical interventions. In other words, identical standards should apply. This article analyzes whether psychedelic medicines warrant special consideration from a regulatory and ethical perspective.

Under both the Court's current Buckley test and under any plausible version of originalism, contributions to independent political action committees are regulable. SuperPACs are, therefore, not constitutionally required - 14 years of mistaken lower court rulings not with standing.

Over the past generation, conflicting trends have reshaped the ownership of corporate equity on the one hand and corporate debt on the other. In equity, the two great trends have been the shift from public markets to private ownership and the consolidation of American companies’ stock in the hands of powerful investment funds. In debt, by contrast, the great trends have been a shift from private loans to quasi-public markets and dispersed ownership. In this Article, we chronicle the recent and dramatic reversal of these trends in the debt markets. Private investment funds executing a “private credit” strategy have become increasingly important corporate lenders, bringing into corporate debt the same forces of privatization, concentration, and illiquidity that have been reshaping the equity markets. We offer new data that illustrate the meteoric rise of the now $1.5 trillion private credit industry, and we explore the allure and implications of private credit. For many corporate borrowers, private credit offers a faster, more efficient, and more accessible source of financing than either banks or the public (and quasi-public) debt markets. Yet the transition from bank-intermediated finance to private credit will transform not only corporate finance, but also firm behavior and economic activity more generally. First, as the corporate debt markets follow the equity markets in going dark, information about many large firms will be lost to the investing public. For better or worse, these firms will act with unprecedented discretion—having been shielded from the discipline and scrutiny of regulators, the trading markets, and the general public. Second, corporate debt—like corporate equity—will become the dominion of investment funds, some of which are already unimaginably large. These funds will influence everything from firm operations and strategy to corporate distress, with uncertain consequences.

The U.S. has one of the highest incarceration rates in the world, with over seven million admissions to jails each year. Incarcerated individuals are the only group in the U.S. that have a constitutional right to receiving "reasonably adequate" health care. Yet, there is little oversight and funding for health care accreditation to 44 jails across the U.S. Surveys of staff indicate that accreditation improves coordination between health and custody staff. We also find that accreditation improves quality standards and reduces mortality among the incarcerated, which is three times higher among control facilities than official estimates suggest. These health gains are realized alongside suggestive reductions in six-month-recidivism, such that accreditation is highly cost effective.

On April 26, 2024, the Office for Civil Rights (OCR) of the U.S. Department of Health and Human Services (HHS) issued a Final Rule titled “HIPAA Privacy Rule to Support Reproductive Health Care Privacy.” As per the attendant Federal Register, the Final Rule was to become effective on June 25, 2024. In so doing, HHS was complying with President Biden’s Executive Order 14076 the sole focus of which was “Securing Access to Reproductive and Other Healthcare Services.” The newly (announced Final Rule bolsters the Health Insurance Portability and Accountability Act of 1996 [HIPAA; Public Law No: 104–191) which “provides penalties” for “wrongful disclosure of individually identifiable health information.” Among its leading objectives, the Final Rule seeks to protect women who cross state lines in search of an abortion. Data reported by the Guttmacher Institute suggest that nearly one in five abortion patients sought out-of-state care during the first 6 months of 2023, a two-fold increase when compared with the same period in 2020. The Final Rule also protects those who provide or facilitate lawful reproductive health care who might otherwise be targeted by state prosecutors with criminal probes or lawsuits in mind. The administration and enforcement of the newly issued Final Rule will be the designated responsibility of the OCR. In a clear reference to Dobbs v. Jackson Women’s Health Organization, HHS Secretary Xavier Becerra made note of the reality that “with reproductive health under attack by some lawmakers, these protections are more important than ever.” It is the objective of this Commentary to review the multiple facets of the reproductive privacy imperative and the projected oversight thereof.

Legal scholarship and regulatory proposals for artificial intelligence (AI) have primarily focused on detecting or preventing AI misbehavior or mistakes. The proliferation of high-performance generative AI, such as ChatGPT and DALL-E, has quite saliently demonstrated that legal problems and policy challenges can also emerge when AI applications perform their assigned tasks too well rather than too poorly, as when humans improperly or unethically rely on AI to undertake tasks they are expected to do themselves or when ready access to high performance AI undermines demand for human services and thereby causes economic disruption. Beyond potential legal or policy challenges, this Article makes a stronger claim, arguing that the increasingly common phenomenon of too accurate AI could imminently create substantial particularized harms to individuals as well as widely dispersed costs to society. Recognizing high AI performance as a potential source of harm is an essential step towards better design and regulation of AI, particularly in horizontal regulatory initiatives such as the EU's AI Act and recent U.S. initiatives and proposals. The Article proceeds in four parts. Part I provides a motivating example of how accuracy is associated with both the problems and also the proposed solutions for a contested but common algorithmic practice: content recommendation. Part II shows how AI accuracy can undercut widely shared normative values, relating this observation to findings from digital ethics, economics, and computer science. Part III examines two recent federal legislative proposals and a recent executive action aimed at taming perceived threats from AI to demonstrate a persistent conceptual lacuna in proposed AI regulation: ignored accuracy harms. Part IV proposes a taxonomy of the mechanisms that bring about accuracy harms, empowering scholars and policymakers to systematically recognize and address accuracy harms from diverse sources. AI regulation will achieve better (and better-defined) outcomes when lawmakers recognize that high accuracy is one of many AI attributes that can shape society for better or for worse.

This chapter honors Cheryl Saunders’ insights into the importance of federalism and the allocation of fiscal powers in understanding how constitutional systems work and how they protect rights. Drawing on caselaw from three common law jurisdictions – Canada, Australia, and the United States – it argues that rights and structures, like federalism or the separation of powers or democratic voting systems, are interdependent. Structures may be understood necessarily to imply certain rights necessary to make the structure effective. Rights may require structures to secure their effective protection. At times, the chapter suggests, texts relating specifically to rights may be less effective in securing their protection than reasoning from more general structural provisions. Federalism, in particular, is a structure that may require certain rights; as a form of government, federalism can both protect rights and undermine their protection. And interdependencies may exist among different structural provisions. As a positive matter, rights and structures may find mutual grounding in basic constitutional norms of unity, liberty, and equality. Whether particular provisions are understood as rights or as structures, or even whether particular rights should be understood to exist, may vary over time and among judges. As a normative matter, the chapter suggests that errors may result from failing to consider the overall constitutional context in which a claim of right, or a very specific structural claim, is situated.