David Sella-Villa (U South Carolina Joseph F. Rice Law) has posted “Regulating AI as a Person?” (34 Mich. St. Int’l L. Rev. (Forthcoming 2026)) on SSRN. Here is the abstract:

The world’s first AI Treaty sets out a bold agenda for AI regulation. The Council of Europe’s Framework Convention on Artificial Intelligence opened for signature in September 2024. It commits signatories, including the United States, to regulate AI in ways that promotes human rights, democracy, and the rule of law. Yet the treaty offers little specific guidance on implementation. This Article applies Professors Crootof and Ard’s Structuring Techlaw approach to the AI Treaty to illuminate options for regulating generative artificial intelligence (GenAI).

The analysis reveals that GenAI’s greatest source of legal uncertainty lies not in its data or hardware—which existing transnational legal regimes largely address—but in its algorithms. Unlike traditional regulatory targets, GenAI algorithms operate through probabilistic processes immune to the sanctions and incentives legal systems typically deploy. These algorithms process data throughout GenAI’s lifecycle, creating normative uncertainties about whether existing laws can accomplish their intended aims. The AI Treaty’s procedural requirements suggest a precautionary regulatory approach.

In developing new regulations consistent with the AI Treaty, the Structuring Techlaw approach suggests that policymakers look to an analogous legal regime. To match GenAI’s features and the AI Treaty’s goals, this regime must assess the provenance, capabilities, and potential impacts of its regulatory object; combine bright-line rules with case-by-case assessments; operate across multiple institutions and jurisdictions; and account for changing circumstances over time. Immigration law – or the regulation of people in new contexts – emerges as a powerful analogy for the regulation of GenAI. Immigration law could provide a foundation for understanding how signatories might implement lifecycle-based regulation that addresses algorithmic data processing’s unique challenges to human rights, democracy, and the rule of law.

Melanie Fink (Leiden U Europa Institute) and Simona Demkova (Leiden Law Europa Institute) have posted “The Constitutional Foundation of Explanation Rights in EU Digital Regulation: A Contextual Approach” on SSRN. Here is the abstract:

EU digital regulation increasingly requires organisations to explain automated decisions affecting individuals. Yet explanation rights across instruments such as the GDPR, DSA, and AI Act have developed without systematic attention to their shared constitutional foundations or their relationship to parallel rights. This fragmentation creates two problems. First, the absence of common principles undermines coherence across explanation requirements, weakening legal certainty and enforcement. Second, constitutional and sectoral explanation rights possess distinct strengths that could inform one another, but when developed in isolation they fail to reach their full potential. 

This Article develops a contextual approach that grounds sectoral explanation rights in the constitutional duty to state reasons, operating at two levels: legislative design and interpretation of existing law. This contextual approach identifies and then draws upon the complementary strengths that constitutional and sectoral rights possess: constitutional principles are valueoriented, resilient against legislative and technological change, and bind public authorities across all decision-making contexts, while sectoral provisions offer domain-specific precision, regulatory flexibility, and functional reach to private actors.

Through two scenarios involving organisations facing overlapping obligations and explanation duties distributed across AI decision-making chains, the Article demonstrates how these strengths enable constitutional and sectoral rights to reinforce each other. Sectoral provisions extend constitutional values to private actors, while constitutional principles fill gaps where sectoral legislation does not apply and provide substantive standards that give concrete meaning to open-textured concepts. While interpretation can mitigate practical challenges and create coherence, the contextual approach demonstrates why future explanation requirements must be grounded in constitutional reasoning principles and coordinated with parallel sectoral provisions from the outset.

Jillian Bommarito (273 Ventures) et al. have posted “Governing AI Agents: Risk, Compliance, and Accountability in Law and Finance” on SSRN. Here is the abstract:

Agentic AI systems—capable of autonomous goal pursuit, environmental perception, and iterative action—are rapidly entering legal and financial services, yet existing governance frameworks were not designed for software that acts rather than merely responds. Unlike passive AI tools, agentic systems can stray from their intended objectives and take consequential actions without human approval, creating risks that traditional compliance models often fail to address. This chapter proposes a governance framework that can be used to scale oversight requirements to match each system’s risk profile, based on factors like degree of autonomy, how long it operates, whose interests it serves, and how its objectives are set and modified. The framework situates agentic AI within a five-layer regulatory stack encompassing foundational law, professional ethics, sector-specific regulation, emerging AI-specific rules (including the EU AI Act), and voluntary assurance standards such as NIST and SOC 2.

The chapter argues that in law and finance—industries built on trust and non-delegable professional duties—human-in-the-loop and human-in-command architectures are not merely best practices but critical designs for satisfying fiduciary and regulatory obligations. To operationalize accountability without fragmenting ownership, the chapter evaluates three organizational models—centralized, federated, and embedded—and demonstrates how responsibility-assignment tools such as RACI matrices can allocate oversight duties with precision. It concludes by outlining a maturity-based adoption path that enables legal and financial institutions to adopt agentic AI while managing liability exposure and reputational risk.

Jinho Lee (Salpida Institute Consciousness Science (SICS)) has posted “Why AI Governance Fails Without a Legal and Scientific Definition of Consciousness” on SSRN. Here is the abstract:

Artificial intelligence governance is widely recognized as one of the most urgent challenges of the twenty-first century. Governments, international organizations, and technology institutions have proposed ethical guidelines, legal frameworks, and safety principles intended to regulate increasingly autonomous AI systems. Yet despite unprecedented attention, AI governance continues to fail in practice. This paper argues that these failures are not primarily technological, political, or ethical in nature. Rather, AI governance fails because it is constructed upon an undefined and scientifically ungrounded concept of consciousness. Current legal and ethical frameworks implicitly rely on assumptions about intention, agency, responsibility, alignment, and decision-making-concepts that presuppose consciousness-while refusing to define consciousness in any measurable, operational, or legally interoperable manner. As a result, AI governance collapses into abstraction, cultural conflict, and non-enforceable norms. This paper reframes AI governance failure as a definition failure rather than a policy failure, and demonstrates why no durable AI governance system can exist without a shared legal and scientific definition of consciousness. This work functions as a diagnostic and connective document. It does not introduce new measurement models or governance mechanisms. Instead, it explains why such models are structurally required, and situates AI governance within a broader civilizational transition toward operationally defined consciousness systems already established in the Consciousness Civilization Framework (CCF) and its constitutional and operational records.