Coglianese et al. on Fighting Risk with Risk

Cary Coglianese (U Pennsylvania Carey Law) and Oren Perez (Bar-Ilan U Law) have posted “Fighting Risk with Risk” (University of Illinois Law Review, forthcoming) on SSRN. Here is the abstract:

A growing scholarly and policy debate pits advocates of the precautionary principle, who prioritize risk minimization, against proponents of an innovation principle, who argue that regulation suppresses technological progress. Despite their differences, both camps share the assumption that contemporary regulatory law is shaped by a risk-averse orientation that is fundamentally at odds with the risk-seeking ethos of technological entrepreneurship in fields such as artificial intelligence. What this debate overlooks is an alternative approach altogether—one that deliberately embraces risk as a vehicle for risk reduction. Instead of fighting risk by restricting, delaying, or controlling risky activity, the government sometimes justifiably fights risk by embracing risk under legally structured conditions. 

In this article, we introduce and offer a theory of this overlooked strategy. Drawing on examples as varied as so-called ethical hacking used to expose cybersecurity vulnerabilities, prescribed forest burning to prevent catastrophic wildfires, and geoengineering to combat climate change, we explain how fighting risk with risk differs from—as well as shares affinities with some elements of—the two sides of the dichotomous precautionary and innovation-oriented paradigms that make up contemporary debate over risk governance.

We offer a framework for deciding when government is justified to fight risk with risk, and when it should revise or discontinue such efforts. This inquiry implicates first-order questions—namely, the welfare implications of risk–risk tradeoffs and the distributive consequences of shifting exposures to risks—and second-order questions concerning the epistemic challenges in authorizing or deploying risk as a strategy for risk governance. These challenges involve making decisions under uncertainty across the policy life cycle, mitigating institutional and behavioral biases, structuring liability and compensation regimes for the risks that law deliberately embraces, and building reflexivity in an often-fragmented institutional environment.

To address these challenges, we advance a meta-regulatory architecture rooted in reflexivity—the capacity of legal institutions to adapt and update policies as evidence, risks, and priorities evolve. This architecture rests on four interlocking elements, each of which corresponds with the main challenges we identify: dynamic updating; structures to counteract cognitive biases; targeted liability and compensation; and collaborative mechanisms that enable coordinated revision. Without such governance mechanisms, regulatory authorities that embrace risk may inadvertently entrench policies whose harms outweigh their benefits and whose inequitable effects deepen existing vulnerabilities in society.

By highlighting how government can affirmatively embrace risk as a risk governance strategy, we seek to bring a fresh perspective to the precaution-versus-innovation debate and point to other ways that law can confront the harms facing society today. The debate between precaution and innovation is incomplete, if not also overly simplistic. Regulating in a highly dynamic world necessitates an equally dynamic posture toward risk. In a fast-paced era defined by climate change and new technologies, society surely requires some precautionary forms of risk governance that minimize risk, as well as some government policies that promote innovation. But it will also at times require strategies that deliberately deploy risk to avert greater harm. The meta-regulatory framework we propose offers a blueprint for embracing risk by integrating economic efficiency with a commitment to distributive fairness. That framework also points to how regulators should act more generally in the face of the risks of new technologies and a changing world.

Aubrecht & Kovac on AI Regulation: A Comparison of Centralized and Decentralized Approaches in Federal Systems

Paul Aubrecht (U Passau) and Mitja Kovac (U Ljubljana) have posted “AI Regulation: A Comparison of Centralized and Decentralized Approaches in Federal Systems” on SSRN. Here is the abstract:

The regulation of artificial intelligence (AI) is at the forefront of legal scholarship, as its use has the potential to change nearly every aspect of human society. The potential for AI to impact society makes its regulation particularly relevant to legal scholars, practitioners, and lawmakers.

This research considers the benefits of centralization and decentralization in regulating AI and the implications of convergence or divergence in AI regulation within a federal system. We examine the United States (US) and European Union (EU) approaches to regulation of AI and show that there is a distinct difference in risk preferences related to the regulation of AI between the EU and US as well as a higher likelihood of negative externalities related to the regulation of AI emerging in the US than in the EU while also recognizing that the US approach of decentralized regulation of AI is more likely to lead to the identification of novel approaches to the regulation of AI which may eventually lead to positive externalities. Thus, we generally consider that each approach is not risk-neutral, though for very different reasons.

This examination focuses on the costs and benefits of centralization and decentralization within federal systems, i.e., systems in which regulatory competencies are divided between the federal and state levels. The US and EU provide useful examples of how federal approaches to regulating AI diverge. A quick look at the regulation of AI in the EU and the US shows a divergence in approaches to the regulation of AI within borders, between states inside federal systems (within the US), and across borders between different federal systems (EU and US).

Colangelo on Is AI the End of the DMA as we Know It?

Giuseppe Colangelo (Università degli Studi della Basilicata) has posted “Is AI the End of the DMA as we Know It?” on SSRN. Here is the abstract:

The disruptive potential of AI-enabled applications for competitive dynamics and the core organisational forms of digital intermediation inevitably also has significant implications for the recent regulatory initiatives adopted to govern digital markets. Indeed, because these instruments were conceived without AI specifically in view, they risk becoming outdated within a very short period of time. Notably, while they have been shaped by a Big Tech-centred conception of digital markets, the possible emergence of new gatekeepers in the age of AI marks a turning point that calls into question the very rationale and foundations of these regimes in their present form. As a result, only a few years after its enactment, the role of the DMA, together with its rationale and claimed future-proof character, is already under scrutiny, as the deployment of AI applications raises the question whether policymakers should reopen the legislative framework in order to amend the Regulation. Against this background and in the context of the first review of the DMA, the paper argues that the rise of AI applications calls for a reconsideration of the DMA’s overall architecture and for the development of a distinct competition policy framework, rather than for a merely incremental fine-tuning exercise.

Velasco et al. on The Future of the AI Summit Series

Lucia Velasco (Maastricht U Business and Economics) et al. have posted “The Future of the AI Summit Series” on SSRN. Here is the abstract:

The AI Summit series – initiated at Bletchley Park in 2023 and continuing through Seoul in 2024 and Paris in 2025 – has become a distinct forum for international collaboration on AI governance. Its early achievements, including the Bletchley Declaration, the Frontier AI Safety Commitments, and the International Scientific Report on the Safety of Advanced AI, are a result of its unique format, regular schedule, and ability to secure concrete commitments from governments and industry.

To ensure its continuing impact, the Summit series must now transition from an improvised sequence of summits towards a more formalized structure. For this evolution to succeed, organizers must carefully examine past successes and realistically assess future challenges. This report examines both, with particular attention to a set of core summit design elements: hosting arrangement, secretariat format, participant selection, agenda setting, and summit frequency. Based on this analysis, we present six recommendations to strengthen the summit series’ impact.

The paper draws on existing international governance models to offer recommendations for each design element, addressing challenges such as a crowded summit landscape, geopolitical shifts, and rapid technological change.

Amadori et al. on Modeling the Geopolitics of AI Development

Alex Amadori (Conjecture) et al. have posted “Modeling the Geopolitics of AI Development” on SSRN. Here is the abstract:

We model national strategies and geopolitical outcomes under differing assumptions about AI development. We put particular focus on scenarios with rapid progress that enables highly automated AI R&D and provides substantial military capabilities. Under non-cooperative assumptions-concretely, if international coordination mechanisms capable of preventing the development of dangerous AI capabilities are not established-superpowers are likely to engage in a race for AI systems offering an overwhelming strategic advantage over all other actors.

If such systems prove feasible, this dynamic leads to one of three outcomes: (1) One superpower achieves an unchallengeable global dominance; (2) Trailing superpowers facing imminent defeat launch a preventive or preemptive attack, sparking conflict among major powers; (3) Loss-of-control of powerful AI systems leads to catastrophic outcomes such as human extinction.

Middle powers, lacking both the muscle to compete in an AI race and to deter AI development through unilateral pressure, find their security entirely dependent on factors outside their control: a superpower must prevail in the race without triggering devastating conflict, successfully navigate loss-of-control risks, and subsequently respect the middle power’s sovereignty despite possessing overwhelming power to do otherwise.

Jurcys on Copyright Registration Requirement in the U.S.

Paul Jurcys (U California) has posted “Copyright Registration Requirement in the U.S.” on SSRN. Here is the abstract:

This entry, prepared for the Elgar Encyclopedia of Intellectual Property Law (2026), provides an overview of copyright registration requirements in the United States. It explains that, unlike patents or trademarks, copyright protection in the U.S. arises automatically upon the creation of an original work fixed in a tangible medium. Registration with the U.S. Copyright Office is therefore optional for obtaining protection but essential for enforcement and evidentiary purposes. The entry traces the historical evolution of copyright formalities—from the 1790 Act’s mandatory filings to the modern system under the 1976 Act—and outlines the procedures, functions, and benefits of registration, including access to statutory damages, attorney’s fees, and prima facie evidence of ownership. It concludes with ongoing debates on formalities, modernization, and AI-related challenges.

Goicouria on Extraterritoriality in AI: Harmonizing the Digital Market Act and US Antitrust Law

Daniel Goicouria (affiliation not provided to SSRN) has posted “Extraterritoriality in AI: Harmonizing the Digital Market Act and US Antitrust Law” (Vanderbilt Journal of Transnational Law, Volume 58, No. 4 pp. 1055-1110) on SSRN. Here is the abstract:

International AI markets currently operate under divergent and often conflicting competition laws. This splintered approach fosters uncertainty, invites regulatory failure, and risks entrenching dominant firms at the expense of emerging innovators. This Note proposes harmonized enforcement mechanisms to safeguard fair competition and minimize extraterritorial effects on global AI platforms. Recent academic discourse has discussed the domestic effects of ex ante regulations in AI markets, but international harmonization and extraterritoriality remain largely undiscussed. 

This Note proposes treaty-based coordination and uniform enforcement guidelines to ensure consistent international oversight. It synthesizes comparative insights from differing competition frameworks to identify best practices and encourage cross-border cooperation. In effect, this analysis closes jurisdictional gaps and mitigates risks of fragmented enforcement in rapidly expanding AI markets. The Note offers an actionable roadmap to unify competition laws globally, protect consumers, and foster continuing innovation.

Ferguson on Personal Medical AI: A Framework for Individual-Based Healthcare Monitoring SubTitile: Personal Medical AI Framework

John Ferguson (The Ferguson Clinic) has posted “Personal Medical AI: A Framework for Individual-Based Healthcare Monitoring SubTitile: Personal Medical AI Framework” on SSRN. Here is the abstract:

Current healthcare AI systems compare patient data against population norms, potentially missing clinically significant deviations that are abnormal for specific individuals. We propose a framework for personal medical AI that establishes individual baselines, learns patient-specific patterns, and detects deviations meaningful to each patient rather than comparing against population averages. This paradigm shift from population-based to individual-based monitoring requires addressing technical architecture, clinical integration, the radical transparency problem, impacts on the doctor-patient relationship, and equity concerns. Personal medical AI represents not a replacement for clinical care but a transformation of the patient-AI-clinician relationship that requires careful implementation to preserve therapeutic value while enabling unprecedented longitudinal insight.

Burke on TikTok, Instagram, and the “Fourth Party”: The Impact of Technical Design on Personal Content Moderation

Caitlin Burke (Stanford U) has posted “TikTok, Instagram, and the “Fourth Party”: The Impact of Technical Design on Personal Content Moderation” (Ohio State Journal On Dispute Resolution 2025) on SSRN. Here is the abstract:

As policymakers debate Section 230, children’s online safety, andsocial media regulation, increasing attention has shifted from online content to the design of digital platforms. This article examines how thepersonal content moderation systems of TikTok and Instagram shape user experiences through interface design, reporting tools, appeals processes, and platform governance. Drawing ondispute system design, it introduces the concept of the “fourth party” to explain how technical design influences online disputes and redistributes power between platforms and users. The article argues thatplatform design is analytically distinct from protected speech and should therefore be evaluated separately from content moderation under theFirst Amendment. By reframing content moderation as a problem of product and interface design rather than speech alone, the article offers a framework forplatform accountability, consumer protection, and online safety that preserves free expression while addressing the harms of modern social media.

Zhang et al. on Balancing Data-Driven Competition and Privacy Protection: A Duopoly Analysis of AI-Powered Digital Assistants

Xiong Zhang (Beijing Jiaotong U) et al. have posted “Balancing Data-Driven Competition and Privacy Protection: A Duopoly Analysis of AI-Powered Digital Assistants” on SSRN. Here is the abstract:

Artificial Intelligence (AI) is rapidly empowering smart products, enhancing both work efficiency and quality of life. However, these improvements rely heavily on the continuous collection and processing of user data, raising significant concerns about privacy. In response, many countries have enacted regulations to protect personal data and consumer privacy. This study examines how privacy protection influences market competition in AI-powered digital assistant markets. We develop a stylized analytical model of a duopoly where firms differ in their ability to collect and monetize consumer data. The results reveal that stronger AI capabilities amplify the profitability of data-intensive firms, while data-light firms can strategically strengthen privacy protection to remain competitive, thereby generating mutual profit gains and enhancing consumer surplus as well as overall social welfare. These findings contribute to the theoretical understanding of data-driven competition and digital privacy management, while offering actionable insights for firms seeking to balance innovation, consumer trust, and regulatory compliance in smart product markets.