Faculty Bibliography

There are two Moralities of Law. The first is the Morality of Legality. The second is the Morality of the Rule of Law. The Morality of Legality is narrow. It calls for fidelity to existing law. It usually plays an important role within the executive branch, where violations of existing law are often (not always) experienced as taboo. The Morality of the Rule of Law is broader. It calls for (1) clear, general, publicly accessible rules laid down in advance; (2) prospectivity rather than retroactivity;(3) conformity between law on the books and law in the world; (4) hearing rights;(5) some degree of separation between (a) lawmaking and law enforcement and (b) interpretation of law; (6) no unduly rapid changes in the law; and (7). no contradictions or palpable inconsistency in the law. The Morality of Legality can be seen as an inference from the Morality of the Rule of Law and in particular from (3) and (5). Neither of the two Moralities of Law takes a stand on free markets, freedom of speech, economic equality, or democracy. Still, both moralities are important. A nation that lacks the Morality of Legality is in deep trouble. A nation that lacks the Morality of the Rule of Law is going to become authoritarian.

From the standpoint of both autonomy and welfare, use of willingness to pay (WTP) is a precious human achievement. At the same time, WTP might be infected by a lack of information and by behavioral biases. There are also philosophical objections to certain uses of WTP, pointing, among other things, to the problem of adaptive preferences and to turning certain goods into commodities. In the end, we have two cheers for WTP, and possibly two-and-a-half.

All over the world, governments are using nudges as regulatory tools. Is this ethical? When? Much of the answer depends on whether nudges promote or instead undermine welfare, autonomy, and dignity. Many nudges, and those that deserve support, promote some or all of those ideals, and undermine none of them. If welfare is our guide, much nudging is actually required on ethical grounds, even if it comes from government. If autonomy is our guide, much nudging is also required on ethical grounds, in part because some nudges actually promote autonomy, in part because some nudges enable people to devote their limited time and attention to their most important concerns. Finally, nudges should not, and need not, compromise individual dignity, which many nudges actually promote. There is, however, a risk that some nudges might count as manipulation, as in the case of "dark patterns"; an emphasis on welfare, autonomy, and dignity helps to show how to avoid that risk.

The outpouring of empirical work on how and when human beings depart from perfect rationality has led to a wholesale rethinking of paternalism and its limits. Over the last decades, three camps have emerged: (1) coercive paternalists, who urge that behavioral findings undermine John Stuart Mill's Harm Principle and greatly strengthen arguments for paternalistic mandates and bans; (2) libertarian paternalists, who urge that behavioral findings justify a host of paternalistic but freedom-preserving interventions or "nudges," such as warnings, reminders, labels, and automatic enrollment; and (3) antipaternalists, who urge that behavioral findings do not justify paternalism and argue only, or at most, for efforts to strengthen or "boost" people's competences, or their capacities to make good choices. On welfare grounds, it is possible to identify the assumptions under which, and the policy domains in which, one or another approach would be best. Libertarian paternalism often has significant advantages over coercive paternalism, at least in circumstances in which choosers are heterogeneous. But when all or most choosers err, the welfarist argument for coercive paternalism is strengthened, and when choosers are not only heterogeneous but also adequately informed and free from behavioral biases, antipaternalism makes a great deal of sense.

Does Artificial Intelligence (AI) have rights? A plausible answer depends on the answer to another question: Is AI capable of experiencing emotions, such as sadness, pleasure, regret, anxiety, joy, and distress? A negative answer to that question means that AI lacks moral rights and that it is not entitled to legal rights (though such rights might be granted for instrumental reasons). It follows that if and when AI has emotions, it has moral rights, and it should be entitled to legal rights as well. The capacity to experience emotions can be seen as a necessary and sufficient condition for the recognition and conferral of rights. That conclusion might be rejected by those who emphasize (for example) a capacity for self-awareness or an ability to reason. A focus on emotions also leaves open the question of what rights AI has, supposing that it has rights, and the grounds on which its rights might be defeasible.

In free markets, countless goods may be bought and sold. What was once not traded on markets-for example, access to public parks or sexual and reproductive capacitiesmight be turned into a commodity. Time and again, allowing things to be bought and sold increases both autonomy and welfare. Still, there are pervasive objections to commodification. The first set of objections points to illicit preferences and values and the importance of delegitimating, or not legitimating, those preferences and values (for example, employers cannot "buy" the right to engage in sexual harassment). A second set of objections involves collective action problems: commodification might create such problems (consider the right to vote). A third set of objections invokes equality (as, for example, when people reject the idea that access to public parks should be allocated on the basis of willingness to pay). A fourth set of objections points to information failures and behavioral biases, potentially producing blocked exchanges. A fifth set of objections emphasizes what may be the corrosive effects of commodification on the goods in questions (consider prostitution). These objections sometimes depend on doubtful empirical assumptions, and are frequently overstated. They have different levels of force in different contexts.

It is rational to care about proximity; closer is often better. Proximity bias can be found when people overweight proximity and are willing (for example) to suffer serious welfare losses in terms of health or wealth in return for modest welfare gains as a result of proximity. In extreme cases, proximity bias leads people to stay where they are, at significant cost to their own welfare. Proximity bias is paralleled by proximity neglect, which can be found when people underweight the welfare benefits of proximity. Proximity bias can be seen as a product of present bias, though it often has additional or distinctive characteristics (including overestimation of the welfare costs of getting from one place to another). Extreme forms of proximity bias can be counted as pathological (“hodophobia”). There is clear evidence of the importance of proximity, and suggestive evidence of proximity bias, in diverse contexts, including medical care; vaccination; eviction; voting; and public assistance. Proximity bias has significant implications for policy and law. It suggests that there may be large effects from increasing (or reducing) proximity or making proximity less (or more) salient, perhaps through the use of debiasing, online alternatives, or various forms of choice architecture.

Can AI be liberal? In what sense? One answer points to the liberal insistence on freedom of choice, understood as a product of the commitment to personal autonomy and individual dignity. Mill and Hayek are of course defining figures here, emphasizing the epistemic foundations for freedom of choice. "Choice Engines," powered by AI and authorized or required by law, might promote liberal goals (and in the process, produce significant increases in human welfare). A key reason is that they can simultaneously (1) preserve autonomy, (2) respect dignity, and (3) help people to overcome inadequate information and behavioral biases, which can produce internalities, understood as costs that people impose on their future selves, and also externalities, understood as costs that people impose on others. Different consumers care about different things, of course, which is a reason to insist on a high degree of freedom of choice, even in the presence of internalities and externalities. AI-powered Choice Engines can respect that freedom, not least through personalization. Nonetheless, AI-powered Choice Engines might be enlisted by insufficiently informed or self-interested actors, who might exploit inadequate information or behavioral biases, and thus co5mpromise liberal goals. AI-powered Choice Engines might also be deceptive or manipulative, again compromising liberal goals, and legal safeguards are necessary to reduce the relevant risks. Illiberal or antiliberal AI is not merely imaginable; it is in place. Still, liberal AI is not an oxymoron. It could make life less nasty, less brutish, less short, and less hard - and more free.

Extremism is often made possible or fueled by group polarization: Like-minded people, engaged in discussions with one another, adopt a more extreme position in line with their prediscussion inclinations. Group polarization often promotes and influences norm entrepreneurs, who in turn help direct, unify, and energize those who listen to them, who in turn direct and energize norm enterpreneurs. The result can be a kind of spiral or tornado. Because of habituation, understood as diminishing sensitivity to stimuli, the energy provided by a transgressive or outre position is often less intense on Wednesday than it was on Monday, which means that norm entrepreneurs are often incentivized to up the ante. Spare as they are, these points suggest the importance of seeing extremism as a product of dynamic interactions among (1) group polarization; (2) norm entrepreneurship; and (3) habituation and thrill-seeking. These interactions might be formalized and subjected to empirical testing.

In our 2025 book, Algorithmic Harm, we contend that the use of algorithms can benefit consumers in many ways (largely because of greater personalization), but that it can also cause harm in the face of information deficits and behavioral biases (again, largely because of greater personalization). Unsophisticated consumers, as we call them, are especially vulnerable to algorithmic harm. In this short response to a set of excellent comments on our book, we explore some of the benefits of personalization; some of the costs of forbidding it; some challenges, in terms of feasibility, to our preferred approaches; and the intriguing question whether and in what sense algorithms might be said to have an unconscious.

Whatever the party of the new president, elected in 2028, it would be worthwhile for the incoming administration to consider eight ideas, to be explicitly embodied in executive orders or presidential memoranda: (1) a clear commitment to the independence of the Federal Reserve Board, certainly with respect to monetary policy; (2) a broad commitment to freedom of speech and the press, building on constitutional requirements; (3) a firm commitment not to interfere with the prosecutorial decisions of the Department of Justice; (4) an insistence on the centrality of cost-benefit analysis, designed to work against both overregulation and underregulation; (5) new restrictions on the pardon power, designed to regularize relevant processes; (6) reasonable (not excessive or expressive) restrictions on conflicts of interest and self-dealing, applicable to executive branch officials and the president personally; (7) a presumption against suits brought by the president in his personal capacity (a voluntary presidential disability, meant to parallel and accompany presidential immunity); (8) perhaps most controversially, a presumption (not a rule) against prosecution, by the current administration, of members of the previous administration. All of these ideas would have to be specified, but they are worthy of serious consideration, no matter the political party of the new administration.

The Hiss-Chambers saga stemmed from a stunning accusation, by Whittaker Chambers, that Alger Hiss, a law clerk to Oliver Wendell Holmes, Jr., and a golden boy of Franklin Delano Roosevelt's New Deal, was a Communist who had engaged in espionage on behalf of the Soviet Union. Initially, Chambers's accusation seemed implausible. But the evidence mounted, and Hiss's firm claims of innocence split the country. The Hiss-Chambers saga helped define, for a long period, the right and the left. In all probability, Chambers told the truth. Still, the Hiss-Chambers saga contains many mysteries, one of which is this: Why did Hiss proclaim his innocence for all of his life? What was in his mind? The Hiss-Chambers saga also casts a bright light on contemporary law and politics. There is no question that the Hiss Case helped to define modern conservatism; Chambers' great book, Witness, is one of its foundations. For decades, many conservatives thought that Hiss's guilt confirmed a large point, or a series of large points, about liberalism, the left, godlessness, disloyalty, otherness, loyalty, and patriotism. One could easily draw a straight line from the right-of-center conception of Alger Hiss, in the 40s, 50s, and 60s, to widespread views about enemies-on-the-left today.

Suppose that one has a choice between two otherwise identical restaurants: one is close and the other is far. Closer is often better; it is rational to care about what is proximate and hence to choose the closer restaurant. Now suppose that one has a choice between two different medical facilities: one is close but average, and the other is far but superb. On plausible assumptions about the welfare effects, it is not rational to choose the closer medical facility. Proximity bias can be found when people are willing to suffer serious welfare losses in terms of (say) health or wealth in return for modest welfare gains in terms of proximity. In extreme cases, proximity bias leads people to stay where they are. Proximity bias can be seen as a form of present bias, or even as the thing itself, though it often has distinctive characteristics (including overestimation of the intrapersonal welfare costs of getting from one place to another). Some extreme forms of proximity bias can be counted as pathological ("hodophobia"). There is clear evidence of the importance of proximity, and suggestive evidence of proximity bias, in the contexts of medical care; vaccination; eviction; voting; and public assistance. Policy implications include the potentially large effects of increasing (or reducing) proximity or making it less (or more) salient, perhaps through the use of online alternatives or other forms of choice architecture.

“The Enemy of My Enemy is My Friend” – so it was said in ancient times, and so it is said, often, today. But is it rational to think and act that way? The meaning of the statement is unclear. So is its justification, and so its scope of application. In deciding whether to treat the enemy of one’s enemy as a friend, there is an analysis to undertake, involving the costs and benefits of doing so. To assess those costs and benefits, one needs to know what, exactly, it means to treat someone as a friend. There might also be deontological reasons not to treat some enemies of one’s enemies as friends. The statement makes clearest sense in the context of war: If someone is willing to fight on one’s side, he is the enemy of one’s enemy, and might be essential to one’s very survival. If so, he might be treated, at least for the relevant time, as if he is one’s friend (with mutual forbearance, genial relationships, certain norms of reciprocity, and perhaps pooling of resources). “The Enemy of My Enemy Is My Friend” might be a rallying cry during some kind of battle. Note, however, that the enemy of my enemy need not be my literal friend; this might simply be an alliance, and a temporary one, of selfinterest. In contexts that do not involve war or (literal) battle, one might accept the enemy of one’s enemy as a friend, in some sense, in order to widen the tent and strengthen one’s capacity (perhaps in politics, perhaps in intellectual life, perhaps in a neighborhood). Friendship, in this context, might refer to a degree of collaboration and reciprocity, and again some pooling of resources. But there are pervasive problems. Among other things, the enemy of one’s enemy might really be an enemy, in some intelligible sense, and if one enters into an alliance, one might dirty one’s hands or put at risk one’s deepest values, and potentially one’s survival, at some later date.

A longstanding puzzle for regulatory theory and practice has been the valuation of children's lives, or more precisely, the valuation of mortality risks faced by children. There is data about parents' willingness to pay (WTP) to reduce such risks, and that data might be used to produce a Valuation of Statistical Lives (VSL) for children. The problem is that any such VSL comes from the parents' valuations; it might not adequately capture the welfare effects of risk reduction for children themselves. It can be shown, however, that use of parental WTP, and the resulting VSL, is justified if (1) patents have adequate information, (2) parents do not suffer from a relevant behavioral bias, (3) parents are motivated to care about their children's welfare, so that parental judgments about how to allocate limited resources for their children promote their children's welfare; and (4) parents have a limited budget for expenditures on their children, and regulation would amount to a forced exchange, producing a dollar-for-dollar reduction from that budget. If we relax one or more of these assumptions, the VSL for children might be higher than the VSL that emerges from use of parental WTP. If we relax (1), (2), and (3), the analysis of how to proceed is straightforward, at least in principle. If we relax (4), it is probably best not to tinker with VSL, even if the assessment of welfare and distributional effects is not straightforward.

The explosion of empirical work on how and when human beings depart from perfect rationality has led to a wholesale rethinking of paternalism and its limits. Over the last decades, three camps have emerged: (1) coercive paternalists, who urge that behavioral findings undermine John Stuart Mill's Harm Principle and greatly strengthen arguments for mandates and bans; (2) libertarian paternalists, who urge that behavioral findings justify a host of freedom-preserving interventions or "nudges," such as warnings, reminders, labels, and automatic enrollment; and (3) antipaternalists, who urge that behavioral findings justify only, or at most, efforts to strengthen or "boost" people's competences, or their capacities to make good choices. On welfare grounds, it is possible to identify the assumptions under which one or another approach would be best. There are certainly domains where antipaternalism (alongside boosting) on the one hand or coercive paternalism on the other hand is best, but libertarian paternalism often has significant advantages, whether our focus is on welfare or autonomy.

Nudges are behavioral interventions that influence decision-making by subtly altering the choice environment without restricting freedom. Rooted in behavioral economics, they have shown promise in health care by improving adherence to guidelines and promoting preventive behaviors. Learning Health Systems offer infrastructure for implementing nudges at scale through tools like electronic health records and decision support systems. In cardiovascular-kidney-metabolic care, nudges targeting both patients and providers, ranging from defaults and reminders to gamification, have improved prescribing, vaccination rates, and physical activity. Frameworks such as EAST and MINDSPACE guide effective design, emphasizing timing, audience, and framing. Looking ahead, artificial intelligence–powered nudges promise personalized, adaptive interventions that respond to real-time behavior and performance, enhancing scalability and sustainability. By aligning behavioral science with health technology, nudges can help optimize care delivery, reduce variation, and improve outcomes across complex health systems.

Both free markets and government regulators tend to use willingness to pay (WTP) to measure the value of goods. The reason for use of WTP is that it is the best and the most administrable method for (1) capturing the relevant welfare effects and (2) respecting personal autonomy. At the same time, WTP might be infected by a lack of information and by behavioral biases. There are also philosophical objections to certain uses of WTP, pointing, among other things, to the problem of adaptive preferences and to turning certain goods into commodities.

At defining points in American history, there have been radical constitutional changes, defined as massive shifts in constitutional understandings, doctrines, and practices. Apparently settled principles and widely accepted frameworks are discarded as erroneous, even illegitimate, in favor of new principles and frameworks. 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. These radical, dizzying changes often trigger a sense of “constitutional vertigo,” particularly in those wedded to the old order. Our goal is to provide a conceptual map and to describe how and why radical constitutional change occurs and the vertigo that it precipitates. First, we ask whether theories of interpretation trigger radical change, or whether desires for fundamental 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” (sometimes authorizing or leading to radical change driven by the president or Congress) and the less familiar top-down approaches, where legal elites push for and then impose a new constitutional regime.

Sometimes people want to know; sometimes people do not want to know; sometimes people want not to know. Deliberate ignorance, or information avoidance, is often fueled by a belief that the relevant information is not useful or would be affirmatively harmful. It is often fueled by a belief it would induce negative emotions, such as sadness, fear, despair, anger, guilt, or shame. In short, the costs of receiving information may exceed the benefits. With respect to animal welfare, many people show deliberate ignorance because they believe that receiving information about the suffering of animals would (1) require unwelcome behavioral changes and (2) induce sadness, anger, guilt, and possibly shame. For those who care about animal welfare and seek to change human behavior, it is best to confront (1) and (2) directly, because deliberate ignorance is a continuing and fundamental obstacle to the reduction of suffering. A possible response is to suggest that the behavioral changes will be easy and pleasant, and a kind of adventure. Another possible response is to suggest that learning about animal welfare is intriguing and even thrilling in multiple ways, and that acting in ways that decrease animal suffering fits well with people's preferred self-image. These points bear more generally on deliberate ignorance about preventable suffering and hardship.

How should one respond to an argument that one believes to be wrong, or egregiously wrong? What is the proper tone? Does disagreement have an internal morality? Does contempt have a place? Is respect the coin of the realm? These questions are relevant to everyone: family members, teachers, students, columnists, priests, United Nations ambassadors, academic writers of all kinds, scientists, lawyers and judges, politicians, and many more. A partial answer comes from the Rapoport Rules, which require a vivid, charitable statement of the argument that one is addressing, alongside an emphasis on what one accepts in it, and on what one has learned from it. The Rapoport Rules lower the volume and take down the temperature. From the social point of view, the Rapoport Rules might be taken as an effort to establish norms from which all or most benefit; they might solve or reduce a collective action problem. Widespread adoption of the Rapoport Rules would be a start toward acting in accordance with the internal morality of reasoned disagreement. They might well lead to better understanding and more in the way of truth. Still, it must be said that the argument in favor of the Rapoport Rules is contingent; much depends on the goals of the speaker or writer, and on their level of confidence, and the nature of the audience and the occasion. Some audiences are more likely to enjoy, and to be persuaded by, arguments that slash and burn. Notwithstanding these points, there is a reasonable argument for a presumption in favor of the Rapoport Rules in academic circles, in judicial opinions, and in legal briefs. There is also a reasonable argument for a presumption in favor of understatement and kindness, rather than "angry science." These points can be seen as an effort to capture the internal morality of reasonable disagreement.

When and how should an individual or an institution act in response to extortion? What should an individual or an institution do to oppose tyranny, illegality, oppression, or horror, if we suppose that the consequences of opposition might not be so good or might be terrible? These questions arose in stark form in 2025 in the context of efforts by the Trump administration to punish and bring to heel law firms, individuals, universities, and others. The underlying debates can be connected with longstanding debates in legal and political philosophy involving act utilitarianism, rule utilitarianism, and deontology.

“Choice engines,” powered by Artificial Intelligence (AI) and authorized or required by law, might produce significant increases in human welfare. A key reason is that they can simultaneously (1) preserve autonomy and (2) help consumers to overcome inadequate information and behavioral biases, which can produce internalities, understood as costs that people impose on their future selves. Importantly, AI-powered choice engines might also take account of externalities, and they might nudge or require consumers to do so as well. Different consumers care about different things, of course, which is a reason to insist on a high degree of freedom of choice, even in the presence of internalities and externalities. Nonetheless, AI-powered choice engines might show behavioral biases, perhaps the same ones that human beings are known to show, perhaps others that have not been named yet, or perhaps new ones, not shown by human beings, that cannot be anticipated. It is also important to emphasize that AI-powered choice engines might be enlisted by insufficiently informed or self-interested actors, who might exploit inadequate information or behavioral biases, and thus reduce consumer welfare. AI-powered choice engines might also be deceptive or manipulative, and legal safeguards are necessary to reduce the relevant risks.

When and how should an individual or an institution act in response to extortion? What should an individual or an institution do to oppose tyranny, illegality, oppression, or horror, if the consequences of opposition might not be so good, or might be terrible? These questions arose in stark form in 2025, in the context of efforts by the Trump administration to punish, and to bring to heel, law firms, individuals, universities, and others. These efforts are connected with longstanding debates in legal and political philosophy. In particular, they put act utilitarianism on trial; those who decide what to do on the basis of an assessment of the likely consequences might produce bad consequences. Rule utilitarianism, or a commitment to a deontological norm, might be necessary to solve a collective action problem. The difficulty, and a grim truth, is that there can be no assurance that rule utilitarianism, or a commitment to a deontological norm, will accomplish anything. Patrick Henry's famous words, "Give Me Liberty or Give Me Death," is galvanizing, as is the slogan, popular in the 1950s and 1960s: "Better Dead Than Red." These propositions are briefly illustrated with reference to the behavior and experiences of scientists under Nazism.

The Morality of Legality holds that it is a moral wrong, and essentially taboo, for those who work in the executive branch to act unlawfully, even if high-level officials much want to act unlawfully, even if circumstances clearly call for the action in question, and even if there is a strong public demand for the unlawful action. The Morality of Legality is less innocuous and more directive than it might seem. It is a red light; it is a conversation-stopper; it empowers law and lawyers. Those who are committed to it will not engage in unlawful action even if no court will be available to strike the action down, and even if there would be significant gains, including political gains, from undertaking the action. The Morality of Legality distinguishes nonauthoritarian from authoritarian systems, and it is a fundamental (and puzzlingly unrecognized) feature of the rule of law. In U.S. constitutional law, it can be taken to be codified in the Take Care Clause. Those who are committed to the Morality of Legality are willing to face "litigation risk" and to seek changes in existing law, even if those e=orts are more likely than not to fail. The Morality of Legality is often felt as a matter of duty, rather than a product of some consequentialist calculation; but it is probably best justified on rule consequentialist grounds. By itself, the Morality of Legality is (mostly) agnostic on the allocation of interpretive authority as between the executive branch and the judiciary. Under emergency circumstances, very narrowly defined, the Morality of Legality might have to yield. The Morality of Legality might also be followed in other places, including of course legislatures and courts, and also private institutions.

One way to evaluate various legal interventions in people’s lives is to ask whether they make choosers better off by their own lights, or “as judged by themselves.” This criterion can be understood to borrow from the liberal political tradition insofar as it makes the judgments of choosers authoritative. If lawyers, judges, and policymakers give ultimate authority to choosers, this might be taken as respecting choosers’ own judgments and promoting their welfare (insofar as people are uniquely situated to know whether choices make them better off). But for certain decisions, the “as judged by themselves” criterion is indeterminate. In these situations, which involve life-changing, transformative experiences, the criterion does not offer a unique solution; people might be happy with their choices either way. It is possible that welfarist criteria will resolve the indeterminacy, despite serious questions about incommensurability.

Recent reports have highlighted the importance of changing human behavior if climate change is to be mitigated. In this respect, behaviorally informed interventions are considered promising tools. In particular, these interventions could be applied in the transport sector, where the mitigation potential is high. However, a comprehensive synthesis of the evidence on behaviorally informed interventions in this field is lacking, although such syntheses are extremely useful for researchers, policymakers, and funding bodies alike. This study addresses this gap by presenting a systematic map of behaviorally informed interventions that target sustainable mobility decisions. An extensive review of more than 30,000 articles revealed a substantial corpus of 204 relevant studies. While studies on usage behavior (e.g. fuel-efficient driving) and studies addressing the private context are most prevalent, the synthesis highlights that existing studies investigated a remarkably diverse set of heterogeneous mobility decisions. Additionally, studies addressing the professional context or positioned at the intersection of the private and professional sphere were identified, highlighting the potential for behavior change interventions in multiple contexts. This study provides a foundational resource for understanding the scope of existing research and uncovering underexplored areas with high mitigation potential. The findings not only inform future academic research but also guide policymakers and practitioners in designing effective, behaviorally informed strategies to reduce transportation's environmental impact.

Will algorithms help people or hurt them? What about artificial intelligence in general? If consumers know what they need to know and do not suffer from behavioral biases, algorithms and AI are likely to be helpful. Consumers will be more likely to get what they want and need. But if consumers lack information, algorithms in particular will be able to convince them to make harmful or foolish choices. And if consumers suffer from behavioral biases, such as unrealistic optimism or a focus on the short term, algorithms will be able to produce serious harms. In Algorithmic Harm: Protecting People in the Age of Artificial Intelligence, Oren Bar-Gill and Cass Sunstein consider the harms and benefits of AI and algorithms and catalog the different ways in which algorithms are being or may be used in consumer and other markets. The authors identify the market conditions under which these uses injure consumers and consider policy and regulatory responses that could reduce the risks consumers, investors, workers, and voters face now—and in the future. Democracy and self-government are at risk; there is a great deal that can be done to reduce that risk.

How should one respond to an argument that one believes to be wrong, or egregiously wrong? The question is relevant to academic writers of all kinds, to scientists, to lawyers and judges, to politicians, and to many more. A proposed answer comes from the Rapoport Rules, which require something like a preliminary doff of the cap, or even a bow, in the form of a vivid, charitable statement of the argument that one is addressing, alongside an emphasis on what one accepts in it, and on what one has learned from it. The Rapoport Rules are most naturally defended in Kantian terms, as a way of showing respect for one's target. They are also kind. They reject what Daniel Kahneman called "angry science." They lower the volume and take down the temperature. On utilitarian grounds, there is a self-interested argument for following the Rapoport Rules, if one's goal is to persuade people; doing so might make both opponents and readers more likely to trust what one is saying, and more likely to like the person who is saying it, and so more likely to accept one's claims. From the social point of view, the Rapoport Rules might also be taken as an effort to establish norms from which all or most benefit; they might solve or reduce a collective action problem. Widespread adoption of the Rapoport Rules might well led to better understanding and more in the way of truth. Still, it must be said that some audiences are more likely to enjoy, and to be persuaded by, arguments that slash and burn. It must also be said that if the goal is to get clear on what is true, slashing and burning have their place. A preliminary doff of the cap, or a bow, may not make much sense in the face of palpable mistakes of logic or fact (or in the face of egregious misrepresentations or bad faith). Still, there is a reasonable argument for a presumption in favor of the Rapoport Rules in academic circles, in judicial opinions, and in legal briefs. There is also a reasonable argument for a presumption in favor of understatement and kindness, rather than "angry science."

Loper Bright, overruling Chevron, is unmistakably part of administrative law’s current “Grand Narrative,” which sees contemporary administrative agencies with suspicion, as a product of successive breaches of Article I, II, and III of the Constitution. The decision should be seen as our Marbury v. Madison—an effort to insist that it is emphatically the province and duty of the judicial department to say what the law is. But will the decision produce large changes? The answer depends, of course, on the meaning of both Chevron and Loper Bright. Under Chevron, courts hardly gave a blank check to agencies; on the contrary, they frequently invalidated agency interpretations of law. How much will invalidation rates rise? We cannot give a confident answer, in part (1) because Loper Bright retains Skidmore (which calls for respectful attention to agency interpretations); in part (2) because Loper Bright recognizes that Congress sometimes explicitly or implicitly delegates interpretive authority to agencies; and in part (3) because (and these must be counted as some of its effects) Loper Bright will (a) increase litigants’ incentive to attack agency interpretations and (b) reduce agencies’ incentive to adopt adventurous interpretations (though agencies may have other incentives to do that). Any numerical projection would be hazardous, but Loper Bright gives a clear signal, a green light to federal courts where Chevron gave a yellow light—which means that it is reasonable to predict a nontrivial increase in judicial invalidations (other things being equal). It is also safe to predict that in the near future, the combination of Loper Bright with increasing judicial skepticism about the administrative state will result in a nontrivial increase in invalidation of regulations designed to protect health, safety, and the environment. In the near future, Loper Bright will also lead to a significant increase in ideological divisions in the lower courts. Still, Loper Bright is our Marbury, and will, sooner rather than later, be seen as such in mounting conflicts between agencies and courts.

For decades, Kent v. Dulles, decided in 1958, was taken to be an iconic case. It helped to define the subject of administrative law. One reason was its singularly dramatic holding: The Supreme Court prohibited the Secretary of State from denying a passport to a Communist. Another reason was its reasoning: It relied on a strong version of the Avoidance Canon and also on what might be seen as an early version of the major questions doctrine (MQD), requiring clear congressional authorization for an "unheralded" and "transformative" exercise of executive authority. Seen against the background of Kent v. Dulles, the MQD might lose its political valence. It can easily operate as a check on right-of-center adventures from the executive branch, just as it has operated as a check on left-of-center adventures from the executive branch. An act of judicial courage, Kent v. Dulles is a beacon. It should be a principal case in all the relevant casebooks; it deserves to be restored to its iconic status.

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.

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.

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.

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.

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.”

For many decades, administrative law has been clouded, or perhaps haunted, by a Grand Narrative. According to that narrative, the Supreme Court has abdicated. It has allowed the modern administrative state to breach the safeguards established by Article I, Article II, and Article III. The Court permitted the breach of Article I by authorizing Congress to delegate broad discretionary authority to agencies (and thus to become legislators). The Court permitted the breach of Article II by authorizing Congress to create independent agencies immunized from presidential control. The Court permitted the breach of Article III in two ways: (1) by giving Congress broad authority to allow administrative agencies to engage in adjudication, unprotected by the Constitution's tenure and salary provisions and (2) by granting interpretive authority to such agencies. In recent years, the Court has acted as if the Grand Narrative is essentially right. It has sharply cabined Congress' power to create independent agencies; imposed new constraints on Congress' power to allow agencies to adjudicate; signaled the vitality of the nondelegation doctrine; insisted on independent judicial interpretation of law; and invoked the separation of powers, through the major questions doctrine, to limit the exercise of discretionary power by agencies. The Grand Narrative also affects other areas of administrative law, including "arbitrary or capricious" review. There are other grand narratives about administrative law (originalist, Burkean, Thayerian, and pragmatic), and they might well be more compelling. But in the current era, they are not nearly as grand, or as influential, as the Grand Narrative. A broader point is that law has multiple equilibria in which different narratives turn out to be grand. The current equilibrium, if it can be called that, is one in which the Grand Narrative is ascendent. "The rise of administrative bodies probably has been the most significant legal trend of the last century and perhaps more values today are affected by their decisions than by those of all the courts, review of administrative decisions apart. They also have begun to have important consequences on personal rights...They have become a veritable fourth branch of the Government, which has deranged our three-branch legal theories much as the concept of a fourth dimension unsettles our three-dimensional thinking. "[T]he dissent who would permit Congress to concentrate the roles of prosecutor, judge, and jury in the hands of the Executive Branch. That is the very opposite of the separation of powers that the Constitution demands." Who controls the past controls the future: who controls the present controls the past. -- George Orwell

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).