Absolute Priority, Relative Priority, and Valuation Uncertainty in Bankruptcy

Bankruptcy reformers advocate substituting relative priority for the prevailing absolute priority standard to promote a more consensual restructuring process. In deciding who does and does not get paid when there is not enough value to pay all creditors, bankruptcy’s prevailing absolute priority rule lines creditors up in rankorder, compensating highest ranking creditors in full before lower-ranking creditors get anything. By contrast, relative priority would account for the possibility that the firm could recover and become more valuable after the bankruptcy. Relative priority would compensate lower-ranking creditors for that chance of the debtor turning around, thereby reducing both their incentive to delay and seniors’ incentive to rush. Relative priority could have these and other potential advantages, but we show here that it would also introduce valuation difficulties. Valuation difficulties are important because under both priority rules the parties have the Coasean incentive to come to a deal that maximizes the total value of the firm, and then split that maximized value; indeed, we show that the absolute priority conflict structure that relative priority seeks to mitigate could readily reemerge under relative priority. A more difficult valuation could make both a deal among the parties and judicial resolution harder. Absolute priority requires point-estimate valuations of the enterprise, like valuing equity of a non-indebted enterprise. But relative priority would require judges, parties, and outside investors to make complex valuations needing additional information, as relative priority valuation requires that decisionmakers assess the chances of multiple future outcomes with more precision than absolute priority needs. Worse, the increased valuation uncertainty from relative priority’s added complexity would discourage full-firm sales. Indeed, relative priority could recreate the bargaining problems afflicting absolute priority. Relative priority would, moreover, work poorly with today’s population of large business bankruptcies, which increasingly is made up of private firms, for which we show relative priority valuation would be particularly difficult. Today, financial professionals generally do not trade or offer for sale similar financial instruments: stock options requiring substantially similar valuation analyses exist for stable public firms, but rarely for distressed firms. True, relative priority could have other advantages over absolute priority. These advantages, however, must outweigh the costs we identify here: namely, that relative priority entails greater valuation uncertainty for the parties, the courts, and outside investors, leads to more valuation conflict than absolute priority, and, in this dimension, would increase bankruptcy’s cost

Antitrust and eMarkets

Most antitrust offenses require proof of the defendant’s market power, or ability to control the market and raise prices above cost. For example, many exclusive contracts are harmless and lawful in competitive markets, but they can become anticompetitive when the firm imposing them has significant market power. The internet has created a large commercial market that rightfully merits attention from antitrust and competition law authorities. Much of the popular press and even some antitrust decisions treat the internet as a market unto itself. Unfortunate dicta in the Supreme Court’s Amex decision seemed to confirm this. The Court stated that “only other two-sided platforms can compete with a two-sided platform for transactions.” For a few products this is true, but not for most others. The implications for market definition are staggering. For example, Amazon’s share of ecommerce is around 40%, but its share of all commerce is 4%. So which is it? It is long past time to “normalize” online markets by treating them as markets, no different in principle from other markets. They are factually distinctive in some ways, but all markets differ from one another in detail. The only way to determine the scope of a relevant antitrust market is to identify the particular product in question and then make the best measurements that the data permit concerning the range of effective substitutes from all sources, both demand and supply. Market definition in antitrust cases presents a question of fact. This makes empirical study of consumer behavior essential, including such things as the ease and frequency of consumer switching and the range of realistically available alternatives. When this is done it becomes clear that some antitrust markets are properly limited to ecommerce. Others are properly limited to traditional commerce. For a large group in the middle, however, the market includes bot

Artificial Intelligence and the Anti-Authoritarian Fourth Amendment

AI-enabled surveillance and policing technologies facilitate authoritarian drift. That is, the systems of observation, detection, and enforcement that AI makes possible tend to reduce structural checks on executive authority and to concentrate power among fewer and fewer people. In the wrong hands, they can help authorities detect subversive behavior and discourage or punish dissent, while enabling corruption, selective enforcement, and other abuses. These effects, although subtle in today’s relatively primitive AI-enabled systems, will become increasingly significant as AI technology improves. Today, the most influential branch of Fourth Amendment scholarship conceives of the Fourth Amendment’s central purpose as preserving citizen privacy against intrusive government observation. Another, less prominent line of scholarship emphasizes the Fourth Amendment’s role in preventing government authoritarianism, focusing on concepts like power, security, and citizen autonomy. The insights of this latter branch of Fourth Amendment theory are likely to be increasingly relevant as artificial intelligence (AI) comes to play a larger role in surveillance and law enforcement. The pro-authoritarian nature of AI law enforcement should influence how courts assess such law enforcement under the Fourth Amendment. This symposium Essay examines the role that Fourth Amendment law can play in regulating AI-enabled enforcement and preventing authoritarianism. It contends that, among other things, courts assessing whether networked camera or other sensor systems implicate the Fourth Amendment should account for the risks of unregulated, permeating surveillance by AI agents. Judges evaluating the reasonable use of force by police robots should consider the dangers of allowing AI systems to monopolize the use of force in a jurisdiction and the diminished justifications for self-defense. Likewise, courts can incorporate factors specific to the AI context into their totality of the circumstances analyses of Fourth Amendment reasonableness. Whether there is a “human in the loop” during enforcement encounters, and whether there is meaningful civilian oversight over AI-enabled enforcement programs, should play a substantial role in assessing the reasonableness of AI- centered police practices. By adopting the principles of the anti-authoritarian Fourth Amendment to the new frontier of AI law enforcement, legal actors can restrain the pro- authoritarian effects of emerging law enforcement technologie

The Class Certification of Exchange-Listed Options in Securities Class-Action Litigation

Class-action litigation for fraud on the market typically focuses on purchasers and sellers of stock. Yet those that bought and sold options on the shares can likewise be harmed. Drawing from experience in In re Apple, Inc. Securities Litigation (N.D. Cal. 2022), the authors describe the issues related to including options traders in a certified class. This article explains how to overcome the obstacles to certifying an investor class that includes buyers and sellers of option

Using Experience Smartly to Ensure a Better Future: How the Hard-Earned Lessons of History Should Shape The External and Internal Governance of Corporate Use of Artificial Intelligence

Artificial intelligence or “AI” has transformative potential. But that reality should not obscure the fact that our society has longstanding experience with the corporate development of novel technologies that pose the simultaneous potential to better human lives and to create massive harm. This article, prepared for the occasion of the 50th anniversary of the Journal of Corporate Law and for the Rome Conference on AI, Ethics, and the Future of Corporate Governance, looks backward at the prior experience with corporate profit-seeking through the development and use of transformative technologies to suggest policy measures that might help ensure that the benefits of AI’s development by for-profit business entities to society far exceed its downside

The Great Unsettling: Administrative Governance After Loper Bright

“Chevron is overruled.” These three words surely captured more attention than any others in the U.S. Supreme Court’s thirty-five-page opinion in Loper Bright Enterprises v. Raimondo. For forty years, the Chevron doctrine had been virtually synonymous with administrative law. Now that the Court has taken a step that many scholars thought unfathomable even just a few years ago, speculation abounds about the possible downstream impacts of Loper Bright on both what agencies will be able to do in the future and how lower courts will respond when reviewing agency action. The vast majority of early expert commentaries suggest major changes to the future of administrative governance. This article aims to put this early prognostication into perspective. We explain why it is difficult to know whether or how much Loper Bright will matter at this time, if we will ever really be able to tell. Both as a legal text and as an intervention into the complex web of institutional politics that constitute administrative governance, Loper Bright contains ambiguities that significantly cloud the picture of the future. In fact, the decision might best be thought of as something of a Rorschach test inside a crystal ball: different people can see different things in it, especially when they try to envision what comes next. And what they see may reflect more of what they are primed to see by their own cultural or ideological predispositions than by an underlying, confirmable reality. That is not to say that Loper Bright has not changed nor will not change administrative law. Nor is it to say that it will not have influential effects on the future practice of administrative governance. Rather, it is to say that predictions about the decision’s impacts cannot be made with anything approaching precision or certitude. We know that Loper Bright has shaken up the legal landscape—much like we can feel an earthquake when it literally shakes up the ground beneath our feet. But just as with real earthquakes, it will take time to assess what the full impacts of the Court’s legal tremors have been—and on which particular structures. Rather than make any definitive predictions about Loper Bright’s unsettling consequences, lawyers and scholars alike would do well to be attentive to the multiple ways that Loper Bright may (or may not) shape the future of administrative governance. We suggest here some of those possible ways and explain why it is so difficult to predict Loper Bright’s precise impact on future administrative governance—a conclusion that may itself prove to be as unsettling as the overturning of a forty-year-old precedent itself

Antitrust\u27s Forensic Tools

Most areas of law enforcement require investigative tools to provide evidence of violations and harm. Antitrust law’s single-minded focus on prices, output, and innovation explains its selection of economic tools. These tools were pro-enforcement and were embraced consistently by the Supreme Court, including proponents of scientific evidence such as Justice Brandeis

Overseeing Private Rulemaking: Evidence from SEC Review of SRO Rules

Securities markets rely heavily on private rulemaking by self-regulatory organizations (SROs) such as FINRA and the stock exchanges, supervised by the Securities and Exchange Commission. The SRO-centric model is marred by problems with democratic accountability and inherent conflicts of interest, where insiders might prioritize private benefits over public needs. For these and related reasons, the SRO model is in a moment of transition— with increasing judicial scrutiny of SROs’ roles and powers within separation-of-powers and administrative-law frameworks. Scholars, meanwhile, know little about how the SROs and SEC jointly produce rules for capital markets. Previous securities regulation scholarship has focused on specific aspects of SRO rulemaking, such as the stock exchanges’ corporate governance rules, largely without addressing systemic issues in the production and SEC oversight of SRO rules. Yet SRO rulemaking practices have important consequences for the regulation of securities markets, including the role of procedural reform on regulatory effectiveness and public participation. This article’s approach uses a comprehensive new dataset drawn from every issue of the Federal Register from 2000 to 2023, providing a unique macro perspective that reveals significant inefficiencies and oversight challenges in the current system. By employing a political economy lens, this study focuses on procedural inadequacies while aligning them with policy concerns about accountability, oversight, and democratic control over regulation. This article argues that the SRO rulemaking system is not functioning well, producing a firehose of securities law that is at once a massive drain on agency resources, as well as an impediment to robust public participation in the rules governing capital markets. After the Dodd-Frank Act, most rule change proposals go effective immediately upon filing unless the SEC takes action to halt effectiveness and need not require preapproval. The dominance of this mode of SRO rulemaking, I suggest, alters both the incentives as well as opportunities the SEC has to engage in robust oversight. I also find evidence that the SEC’s oversight responds to a judicial-review shock. I assess the Dodd-Frank reforms under a framework that recognizes the tradeoff between the costs of deciding and the costs of making wrong decisions, and connect this tradeoff to deeper debates about the role of SROs in our constitutional structure. This project contributes to our understanding of the political economy of capital markets regulation, as well as our understanding of federal oversight of SRO rulemaking

Truth and Technology: Deepfakes in Law Enforcement Interrogations

The increasing deployment of generative artificial intelligence (AI) in law enforcement raises pressing theoretical and normative questions, particularly regarding its potential to infect a critical aspect of a police investigation, the custodial interrogation. A central issue is whether, and to what extent, police may lawfully employ generative AI tools to induce confessions from suspects during custodial questioning. Historically, courts have permitted law enforcement officers to use certain deceptive tactics during interrogations without running afoul of constitutional protections. Permissible forms of deception have included the presentation of falsified forensic evidence, fabricated witness statements, and pretend polygraph results. These methods, though controversial, have long been accepted as part of the strategic repertoire of law enforcement, on the premise that they do not overbear the suspect’s will to a constitutionally impermissible degree. However, the advent of generative AI introduces new dimensions of manipulation that may significantly intensify the inherent compulsion of a custodial interrogation. AI-generated deepfakes —synthetic audio, video, or images that appear convincingly authentic—can be used to fabricate incriminating evidence with unprecedented realism. Imagine a scenario in which police confront a suspect with a deepfaked video depicting a purported eyewitness who falsely claims to have observed the suspect committing the crime, or a video of an “accomplice” confessing and implicating the suspect. Such fabrications, made possible by AI, could profoundly distort a suspect’s perception of the evidence against them, potentially exceeding the bounds of due process and exacerbating the potential for false confessions. Beyond the presentation of false evidence, generative AI may also enable real-time interrogation enhancements. Advanced models may soon analyze inputs, such as a suspect’s facial expressions, vocal tone, posture, and demographic characteristics, and generate immediate feedback or strategy suggestions for interrogators. These AI-driven analytics could guide law enforcement toward more psychologically effective, and possibly more coercive, techniques tailored to the individual suspect. The potential use of such data-driven, adaptive interrogation strategies raises serious concerns under established voluntariness jurisprudence. To address the unprecedented risks posed by generative AI in the interrogation context, courts should adopt a clear and administrable per se rule: that the use of fabricated evidence generated by AI to elicit a confession renders that confession involuntary. As generative AI enables increasingly persuasive and deceptive forms of evidence fabrication, a categorical prohibition on its use in custodial interrogations is both doctrinally sound and normatively imperative. This approach would preserve the integrity of the criminal justice system and ensure that constitutional protections remain robust in the face of rapidly advancing digital manipulation