Recognizing What’s Around the Corner: Merger Control, Capabilities, and the New Nature of Potential Competition

Abstract

This paper argues for a capabilities-based, forward-looking approach to merger control that reflects the realities of dynamic competition. In fast-evolving sectors, the most significant competitive threats often come not from current rivals but from de novo firms or adjacent firms developing complementary technologies or capabilities. Conventional antitrust tools — rooted in static market shares and product overlaps — fail to detect these latent challengers or assess the innovation potential of mergers. We draw on economic theory, executive insight, and case studies (Meta–Giphy, Adobe–Figma, Amazon–iRobot) to show how competitive uncertainty disciplines incumbents and how mergers can either suppress or amplify that dynamic. We propose a framework that shifts the focus from products to capabilities: assessing technological assets, organizational routines, and innovation trajectories. This approach reduces enforcement errors — both false positives and false negatives — and enables regulators to protect long-term rivalry without undermining legitimate adaptation to new technology and market shifts By recognizing unseen competition as a structural feature of dynamic markets, and by evaluating mergers through the lens of capabilities, agencies can better align merger control with the goal of promoting sustained innovation and longer-term consumer welfare.

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Abstract

Modern targeted sanctions achieve speed and breadth by prioritizing legal minimalism at the designation stage—relying on intelligence-based attribution rather than evidence-based adjudication—while exporting the resulting unfunded mandates of complexity, costs, and legal uncertainty to enforcement. This Article argues that this infrastructure gap is a structural feature of modern sanctions design, functioning as an unfunded mandate imposed on enforcing jurisdictions. Sanctioning states rely on enforcing jurisdictions to supply the legal and administrative financial infrastructure needed to convert designation into control.

The Article develops this argument through the seizure of the M/Y Alfa Nero, stranded in Antigua following the designation of its alleged beneficial owner as part of the post-Ukraine invasion Russia sanctions regime. Antigua enacted emergency legislation, litigated multiple cases, and absorbed years of administrative and custodial costs. The vessel sold for $40 million against a reported $120 million value, with the difference representing deadweight loss absorbed by the enforcing jurisdiction, third parties, and the asset itself. Generalizing from this case, the Article shows that small states systematically function as shock absorbers for sanctions enforcement, supplying unfunded infrastructure under treaty compulsion and reputational coercion while lacking voice in sanctions design. Assessing sanctions requires transparency about enforcement costs, not just assets frozen.

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I. Introduction

Early in the 20th century, a new model for retail sales arose: chain stores. One chain, the Great Atlantic & Pacific Tea Company (A&P), became America’s largest retailer during 40 mid-century years. Emphasizing scale, vertical integration, and superior use of data, chain stores had lower costs, greater variety, and often other measures of improved quality. The previously dominant model featured wholesalers, middlemen who connected manufacturers, many growing in size, to the myriad, mostly small retailers. Incumbent retailers and wholesalers reacted fiercely to the new competition, attempting to use government to limit their growing, more efficient rivals.

President Franklin Delano Roosevelt’s first attempt to end the Great Depression, the National Industrial Recovery Act of 1933, preached business-government cooperation and sought to raise prices to provide relief to struggling businesses. Chain store opponents seized the opportunity. Under the new law, codes of conduct emerged, some of which attempted to prevent chain stores from bypassing traditional wholesalers, while others aimed at crippling the new model. In practice, the codes proved hard to enforce, and the Supreme Court ended the experiment less than two years after the underlying statute was enacted, declaring it unconstitutional.

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Abstract

What good is a legal system built for visible injuries in a world where injury is designed to be invisible? This Article identifies and theorizes incognito consumer harm: consumer-facing wrongdoing designed to remain unnoticed by most victims. A robot vacuum cleaner covertly records video inside consumers’ homes. A seemingly helpful browser extension records everything users do on the internet. A dating app quietly retains photo IDs it promised to delete. Because consumers cannot readily detect these harms, the law’s ordinary enforcement triggers rarely fire: victims do not complain, lawyers are not retained, and regulators receive no report. Thus, discovery of incognito consumer harm depends more on leaks, hacks, whistleblowers, and other accidents than on routine enforcement mechanisms.

Incognito consumer harm matters for three reasons. First, it exposes a structural weakness in U.S. consumer protection. Both public and private enforcement depend on the victims’ awareness, but courts cannot litigate the invisible and agencies do not routinely audit products for concealed design choices. Second, it highlights a diagnosis-cure mismatch in the literature. Even when scholars describe “invisible” harms, they often propose remedies that assume detection, such as procedural reforms, bans, and enhanced damages, even though incognito harm is designed precisely to prevent detection. Third, modern technology makes concealment scalable, continuous, and embedded in everyday products. As AI increases firms’ appetite for granular and intimate data, the payoff to undiscoverable extraction only grows.

This Article argues that incognito consumer harm requires fundamental reform, not marginal tweaks, because existing law fails doubly. It is not built to surface invisible injuries and, even when misconduct is exposed, doctrine often fails to recognize concealed risk, loss of control, and informational deprivation as cognizable harms. Without detection-first reform, the status quo persists. We learn about hidden misconduct only when systems are breached or insiders come forward—in effect, relying on wrongdoers to expose wrongdoing.

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Abstract

The United States’ growing dependence on foreign sources for rare earth elements and other critical minerals is commonly attributed to environmental regulation, permitting delay, or foreign industrial policy. This Article argues that those explanations miss the core problem. The crisis is institutional. By abandoning the property-rights framework of the General Mining Law of 1872 and replacing it with administrative discretion under twentieth-century statutes such as the Mineral Leasing Act, FLPMA, and NEPA, the United States dismantled the legal institutions that once induced mineral discovery and supported long-horizon investment. Drawing on economic theory and legal history, the Article shows how property-based access to public minerals solved the twin problems of mineral development: incentivizing decentralized discovery under deep uncertainty and enabling capital-intensive investment in sunk assets. The core problem is thus a Hayekian knowledge problem. Rare earths provide a diagnostic case. Contemporary policy responses-subsidies, industrial planning, and executive action-have pushed the administrative system to its limits but cannot substitute for secure, mortgageable mineral rights. The Article concludes that restoring domestic critical-mineral capacity requires reopening mineral patenting and reestablishing rule-based property rights as the foundation of mineral policy, rather than continuing to rely on discretionary regulation and industrial policy to compensate for their absence.

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Abstract

Ronald Coase suggested a radical change in thinking about property rights in radio waves. Common pool problems in frequencies had been dealt with by regulatory allocations defining what services could be supplied. But the tradeoffs implicated in such market guidance were generally invisible to government spectrum managers. Coase theorized that ownership of tradeable frequency rights – now called exclusive, flexible-use spectrumaccess — might improve the coordination sought. Policy experiments in emerging wireless networks then achieved consensus approval among economists in the 1980s and 1990s. By the 2000s, however, this new thinking was being challenged. Scientific progress was seen to engineer “smart radios” mitigating spectrum sharing conflicts. Technology changes often prompt changes in rights regimes. Unlicensed bands offering non-exclusive spectrum access for low-power devices have supported wi-fi and Bluetooth applications in wireless local area networks (WLANs), now ubiquitous in homes, offices, and automobiles. Meanwhile, wireless wide area networks (WWANs) relying on liberal licenses, primarily distributed by auction and reconfigured in markets, have triggered a mobile revolution approaching 100% penetration globally; in 1975 there was one phone for every 12 persons. Both regulatory models incorporate mechanisms for spectrum sharing, delivering broadband Internet services hosting the “App Economy.” But which mechanisms are better choices when mutually exclusive regulatory determinations are made? Here we analyze three policy experiments in which the U.S. Federal Communications Commission created regimes enabling non-exclusive spectrum access: Unlicensed PCS (U-PCS) launched in a proceeding beginning 1991; Television White Space devices (TVWS) developed in a spectrum allocation dating to 2002; and Citizens Band Radio Services (CBRS) developed via a rulemaking opening in 2009. “Dynamic spectrum sharing” in the form of “listen before talk” (LBT) or coordination by a “spectrum access system” (SAS) have been deployed in these governance frameworks, which are offered as models for current reforms. Seriously evaluated, that conclusion appears uncompelling.

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Abstract

Very soon, millions of AI agents will proliferate across the economy, autonomously taking billions of actions. Inevitably, things will go wrong. Humans will be defrauded, injured, even killed. Law will somehow have to govern the coming wave. But when an AI causes harm, the first question to answer before anyone can be held accountable is: Which AI Did It?

Identifying AIs is unusually difficult. AIs lack bodies. They can copy, split, merge, and swarm at will. Even today, a “single” AI agent is often an ensemble of instances based on multiple models. The complexity will only multiply as AI capabilities improve.

This Article is the first to comprehensively diagnose the legal problem of identifying AIs. For AI agents to be effectively governed, the Article argues, two kinds of identity are required: “thin” and “thick.” Thin identification is the project of tying every action taken by an AI to some human principal. Thin identity will be essential for law to hold accountable the humans who make and use AI agents. Thick identification is the project of distinguishing between AI agents, qua agents. It requires sorting millions of AI entities into discrete, persistent units with stable, coherent goals. Thick identity is essential for governing AIs’ behavior directly in the many contexts where principal–agent problems prevent humans from perfectly controlling AIs.

The Article is also the first to present a solution to the twin identity problem. We call it the “Algorithmic Corporation” or “A-corp,” a legal-fictional entity that can hold property, make contracts, and litigate in its own name. An A-corp is owned by humans. But it is designed to be run by AIs. The A-corp solves the thin identity problem by tying AI actions to a human owner. And it solves the thick identity problem via emergent self-organization. A-corps will own the resources which AIs need to accomplish their goals. AIs that control A-corps will thus have strong incentives to share control only with other AIs that share their goals. In equilibrium, both incentive and selection mechanisms will force A-corps to self-organize into persistent, legally legible entities with coherent underlying goals. These coherent, agentic entities will respond rationally to legal incentives, like liability.

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Abstract

Americans consume a lot of bullshit. Verifiable falsehoods and intentional disinformation are in the mix, but the biggest contributors to the pile are sloppy, vague, and cherrypicked content that reinforces preexisting beliefs. Policymakers typically blame supply: new media outlets that fail to meet journalistic standards or social media platforms that amplify clickbait and extreme content. As a result, legal responses have attempted to reduce bullshit by managing supply through competition policy, must-carry rules, and consumer protection laws. These interventions are flawed because they stem from a misdiagnosis. Bullshit is primarily a problem of consumer demand. News consumers prioritize social belonging, stability, and intellectual ease over truth-seeking, and media organizations must oblige if they want to survive.

This Article reorients the policy discussion of misinformation around audience capture and demand-side factors. It distinguishes bullshit from misinformation, critiques supply-side theories, and advances a demand-side account that better explains our democratic and epistemic predicament. It then evaluates legal reforms, showing why many are ineffective, counterproductive, or unconstitutional, and concludes by sketching three alternative approaches that the government could take: (1) treating media as a widely-shared vice, (2) helping to make truth-seeking more financially or socially rewarding, and (3) fostering a culture of critical thinking.

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Abstract

Using a comprehensive dataset of posts from a major platform for anime- and manga-style artwork, we study the impact of the launch of a prominent text-to-image generative AI. Focusing on the majority of incumbent creators who do not adopt AI as a primary tool, we show that the AI launch led to a significant decline in post uploads by illustrators, whereas comic artists were less affected, reflecting the need for tight stylistic alignment across sequential images in comics. We present empirical evidence for two underlying mechanisms. First, illustration posts experience a loss of viewer attention, measured by bookmarks, following the AI launch, which can significantly harm creators’ business models. Second, direct competition from AI-generated content plays an important role: illustrators working on intellectual properties (IPs, such as Pokémon) that are more heavily invaded by AI reduce their uploads disproportionately more. We further examine creators’ responses and show that illustrators with greater exposure to AI avoid using tags favored by AI-generated content after the AI launch and broaden the range of IPs they work on, consistent with a risk-hedging response to AI invasion.

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