Lubin on Out of Time: Artificial Intelligence, Self-Help, and International Law’s Temporal Logic

Asaf Lubin (Indiana U Maurer Law) has posted “Out of Time: Artificial Intelligence, Self-Help, and International Law’s Temporal Logic” (The Cambridge Handbook of Public Law and Artificial Intelligence, Gregory, Williams, & Zerilli eds., Cambridge Univ. Press, forthcoming 2027.) on SSRN. Here is the abstract:

The rule of law has a tempo. It unfolds in time, organizes through time, and relies on time as a condition of its own functioning. Legality is sustained through an iterative practice of claim and counterclaim, argumentation and contestation. That exchange has a temporal structure. Time is needed for any claim to be formulated, any premise to be tested, any objection to be heard, and any judgment to be revised. In this sense, law is more than just a system of rules, institutions, and sanctions. It is also a system of pauses and intervals: the space between power’s first impulse and law’s second thought.

Law’s discursive and temporal character is most acute in international law. In a decentralized system lacking compulsory jurisdiction, states make law meaningful by arguing through it. Nowhere is this more evident than in the international law of self-help. The doctrines of self-defense, countermeasures, and retorsions govern the circumstances in which each state may invoke its own interests as grounds for unilateral protective action. The risk, of course, is that self-help will become self-licensing; that states, moving first, moving alone, and moving in secret, will be incentivized toward abuse and vigilantism. International law responds to this concern by forcing structured moments of argumentation around unilateral uses of power. The necessity, imminence, and proportionality of a use of force must be assessed and defended. The attribution of a prior wrong, together with the notice, purpose, and reversibility of a countermeasure, must likewise be tested and justified. These requirements are what prevent the law of self-help from becoming a vocabulary for disobedience.

And yes, these assessments also require time. Lots of time. Time for inquiry and for dissent. Time for simmering and for digestion. Time for contemplation and for meditation. Time for sleep, even. Indeed, some of the world’s greatest inventors and creators credit their creativity to the power nap. The sleeping mind consolidates, reconsiders, and sometimes resolves what the waking mind cannot.

But AI does not sleep. AI is built to increase efficiency through automation. It promises to offload cognition onto the machine, thereby removing the supposed waste and cost of “human friction.” AI does not deliberate, simmer, or meditate. It does not toss and turn at night. It does not wake at three in the morning with a reconsidered judgment. It does not pray or consult a loved one. It only processes. And it processes fast. Extraordinarily fast. So fast, in fact, that it outpaces law’s intervals. As this book chapter reveals, the very features that make AI attractive to national security decision-makers—its speed, scale, and tirelessness—are precisely the features that make it dangerous as a substitute for legal judgment. The chapter therefore asks not whether AI must be kept outside the national security state, for it will not be, but whether the state can use it without surrendering the pauses, frictions, and second thoughts through which law makes power answer.

Chouldechova et al. on Race-Conscious Admissions Algorithms and the Law

Alexandra Chouldechova (Carnegie Mellon U H. John Heinz III Public Policy and Management) and Daniel J. Hemel (New York U Law) have posted “Race-Conscious Admissions Algorithms and the Law” on SSRN. Here is the abstract:

In 2023, the U.S. Supreme Court held in Students for Fair Admissions v. Harvard that higher education institutions cannot admit students “on the basis of race.” This article addresses what it means for an admissions algorithm to operate on the basis of race. We develop a taxonomy of race consciousness in the algorithmic decision making context that provides lawyers and machine learning researchers with a shared vocabulary for exploring the implications of the Court’s ruling. We distinguish between “first-order” and “second-order” race consciousness at both the training and predictive phases of machine learning, and we argue that each category of race consciousness raises distinct legal and normative issues. We go on to explain why the Court’s decision need not be read as a flat-out ban on all types of race consciousness in admissions, and why certain forms of race consciousness might even advance the goals of justices who voted to strike down affirmative action policies inSFFA.

Bronsther on When the Cheapest Cost Avoider Is the Machine: Direct Sanctions for Autonomous AI

Jacob Bronsther (Michigan State U College Law) has posted “When the Cheapest Cost Avoider Is the Machine: Direct Sanctions for Autonomous AI” on SSRN. Here is the abstract:

The scholarship on artificial intelligence and legal liability assumes that the cheapest cost avoider is always a human being: a designer, deployer, or user. This Article identifies the conditions under which that premise fails. As an AI system’s behavior becomes less observable to its developer and more autonomous from human direction, the system may become the actor best positioned to foresee and forestall harmful outcomes. When such a system is also sensitive to the threat of legal penalties, the economic logic of AI-liability theory requires sanctions to reach the system itself. To the extent the system is judgment-proof, those sanctions must take nonmonetary form: limits on the computational resources it can use, the capabilities it can exercise, or its continued operation, calibrated to the severity of harm and the difficulty of detection. Human liability remains for the upstream risks humans could efficiently prevent; direct sanctions apply only to the residual conduct-level choices the system is best positioned to control.

Ard et al. on Technology Law Chapter 6: Upset Equilibria

Bj Ard (U Wisconsin Law) and Rebecca Crootof (U Richmond Law) have posted “Technology Law Chapter 6: Upset Equilibria” on SSRN. Here is the abstract:

Based on years of experience teaching the subject, we have produced a first draft of a “Technology Law” coursebook. It teases out fundamental concepts, introduces our methodology for resolving tech-fostered legal uncertainties, and identifies the strengths and weaknesses of different regulatory choices. Through a mixture of readings, exercises, and discussion questions, it helps readers develop facility in:

– Recognizing the recurring techlaw and policy questions and discerning the application, normative, and institutional uncertainties associated with a particular technology;

– Working through the process of resolving legal uncertainties, which includes consciously selecting a regulatory approach, identifying legally salient characteristics and relevant analogies, and weighing the benefits and drawbacks of various regulatory choices (law-by-analogy, creating new law, or reconfiguring legal institutions); and

– Developing familiarity with employing and countering common rhetorical strategies for advancing, opposing, or shaping regulation.

This course is designed to be accessible and useful to all students, regardless of career interests or prior experience with technology. New technologies challenge every area of the law, and the regulatory and rhetorical strategies we’ll explore are transferable across subjects.

This posting includes Chapter Six: Upset Equilibria. Future chapters will be posted bi-monthly.

We welcome feedback at the link included in the document; additional chapters will be updated regularly. If you are interested in teaching from this text, in whole or in part, please let us know, as we would be happy to share our class notes and slides.

Yu on Toward a New Research Agenda for Artificial Intelligence and International Law

Peter K. Yu (Texas A&M U Law) has posted “Toward a New Research Agenda for Artificial Intelligence and International Law” (UCLA Journal of International Law & Foreign Affairs, Vol. 30, 2026, Forthcoming) on SSRN. Here is the abstract:

Over the past few years, artificial intelligence—in particular, generative AI—and the changes brought about by this new technology have garnered priority attention from policymakers, commentators, and the mass media. Issues such as job displacement, the unauthorized use of personal information and likeness, the protection of intellectual property rights, and environmental sustainability have attracted analyses through an AI lens. What is less explored, however, is how AI will change the future development of international law.

To provide an overview of the issues that have received attention thus far and that will continue to emerge at the intersection of AI and international law, this short essay, which was expanded from the opening remarks on the “Artificial Intelligence and the Boundaries of International Law” panel at International Law Weekend—West 2026, identifies eight issues that deserve greater policy and scholarly engagement. Together, these issues help demonstrate the need for a new research agenda for AI and international law and provide content to fill this agenda.

Solow-Niederman on Clickwrap Accountability

Alicia Solow-Niederman (George Washington U Law) has posted “Clickwrap Accountability” (95 Fordham L. Rev. (forthcoming 2026)) on SSRN. Here is the abstract:

Picture a public-facing generative AI chatbot on a government website that can answer questions about benefits eligibility. Systems like these expose a sociotechnical-legal divide: they route around the standard due process framework, because there has been no formal government determination, yet they induce reliance from users, above and beyond past rounds of automated legal guidance. Moreover, if there is an error, current doctrine on government errors and equitable estoppel makes relief unlikely.

Smith on Persons Real and Feigned A Metaphysics of the Legal Person

Thomas A. Smith (U San Diego Law) has posted “Persons Real and Feigned A Metaphysics of the Legal Person” on SSRN. Here is the abstract:

This essay asks what a legal person is, and argues that the law’s many nonhuman persons answer to a single account with three terms and no fourth. A legal person is either a rational substance, an individual being whose own nature is rational, which is what a human being is and the person in the fullest sense; or a unity of order, a body of rational persons held together by an order directed to a common good, which is what a corporation is, and a state, a person not in the full sense but by a true analogy, real and an agent yet possessed of no rational soul of its own; or a pure fiction, a name in the law behind which there stands no person at all, which is what an artificial agent is when the law makes a person of it.

The middle term is the essay’s contribution. Drawn from the metaphysics of Aristotle and Aquinas rather than from the natural law theory of recent decades, the unity of order supplies the category that the fiction, aggregate, and organic theories have each lacked, and it explains how a corporation can truly act, and persist beyond the members who compose it, while having no inner life or conscience of its own. The account refuses to remain idle: it is tested by prediction against the constitutional protections a corporation may and may not claim, across self-incrimination, speech, religious exercise, and the piercing of the corporate veil, and is then carried beyond the business corporation to the state, which is neither a mere aggregate nor a deified substance, and to the artificial agent, which proves to be the first legal person the medieval term persona ficta describes without remaind.

Rousseau et al. on Artificial Intelligence and the Board of Directors: AI Governance Frameworks and Disclosure Practices of Canadian-Listed Corporations

Stephane Rousseau (U Montréal Law) and Catherine Régis (U Montreal Law) have posted “Artificial Intelligence and the Board of Directors: AI Governance Frameworks and Disclosure Practices of Canadian-Listed Corporations” on SSRN. Here is the abstract:

This article examines the state of artificial intelligence (AI) governance among Canadian publicly listed companies, with a focus on the role of boards of directors in overseeing AIrelated risks and opportunities. Drawing on the Canadian corporate governance framework-including directors’ fiduciary duties and duty of care under corporate law, and the comply-or-explain approach adopted by the Canadian Securities Administrators (CSA)-the article situates board oversight of AI within both shareholder primacy and stakeholder theory perspectives. An empirical study of TSX-60 listed companies, based on regulatory filings and structured content analysis, reveals a significant gap between the widespread recognition of AI as a material risk factor and the formal integration of AI governance into corporate architecture. Building on this empirical foundation, the article surveys emerging best practices from academic literature, proxy advisory guidelines, shareholder proposals, and international governance codes. It concludes that existing Canadian governance standards, though partially responsive, remain insufficient to address the complexity and urgency of AI-related challenges. The article recommends that the CSA revise its corporate governance guidelines using the comply-or-explain approach to promote standardized disclosure, reduce fragmentation, and strengthen board accountability in an era of accelerating AI adoption.

Pandey on The Agentic AI Governance Framework: A Universal Model for Risk, Accountability, and Compliance in Autonomous Systems

Rajat Pandey (MindscopeAi LLP) has posted “The Agentic AI Governance Framework: A Universal Model for Risk, Accountability, and Compliance in Autonomous Systems” (https://orcid.org/0009-0001-8440-2191) on SSRN. Here is the abstract:

The rapid and enthusiastic interest in development and deployment of Agentic AI and especially autonomous agents which are capable of independent reasoning, leveraging and executing tools, has outpaced the definition of governance mechanism that is required to manage their operational, ethical and regulatory risks.There are existing AI governance models like NIST AI RMF, ISO/IEC 42001, do provide foundational controls however, they are very generic and lack the implementation depth for these conitnuously acting, multi-agent systems.

This paper introduces The Agentic AI Governance Framework, which is a six principled lifecycle model designed to ensure traceability, accountability, and regulatory alignment across agentic deployments. The framework formalizes quantifiable controls through two applied mechanisms: the Agentic Log Retention Index (ALRI), which defines evidenceretention periods based on agent risk and jurisdiction, and a Runtime Governance Architecture integrating human-in-loop escalation, tool-access allow-lists, and modelprovenance capture. Implementation mappings are provided for major orchestration environments including LangChain, Power Platform, and UiPath.

Adoption of the framework enables organizations to reconstruct agentic decisions within 24 hours, achieve ≥ 95 % provenance coverage, and detect behavioral drift within 10 % variance. The proposed model bridges the current gap between compliance principles and deployable governance practice, establishing a reusable baseline for safe and auditable Agentic AI operations.

Olson on Beyond Conception: AI, the America Invents Act, and the Temporal Anchor of Invention

David S. Olson (Boston College Law) has posted “Beyond Conception: AI, the America Invents Act, and the Temporal Anchor of Invention” (Brooklyn Law Review, Vol. 92 (Forthcoming)) on SSRN. Here is the abstract:

Artificial intelligence systems increasingly generate technical solutions before any human has anticipated, formulated, or understood them. Under current patent doctrine, these inventions may be unpatentable—not because they fail requirements of novelty, utility, or disclosure, but because they lack a psychologically framed moment of human conception. This Article argues that the continued centrality of conception is both historically contingent and doctrinally unnecessary. Conception arose as a priority-allocating device under the first-to-invent regime. The America Invents Act (AIA) eliminated that regime, replacing it with a first-inventor-to-file system in which priority turns on filing date. Yet conception persists as the definitional anchor of invention, retained by doctrinal inertia rather than functional necessity. Every substantive concern that conception might plausibly serve (screening for operability, ensuring disclosure, preventing trivial patenting) is already performed more directly by existing requirements of utility, enablement, written description, novelty, and obviousness. This Article proposes relocating the temporal anchor of invention from mental formulation to demonstrable technological achievement through actual or constructive reduction to practice. This realignment harmonizes patent doctrine with the AIA’s statutory structure, accommodates computational modes of innovation without inventorship metaphysics, and preserves every existing safeguard against speculative or overbroad patenting.