Call for Papers

The Law Review welcomes submissions on cutting-edge issues in AI and data law, engaging doctrinal, theoretical, comparative, or empirical approaches. Topics of particular interest include, but are not limited to:

• Regulatory frameworks for autonomous systems, including self-driving vehicles, autonomous weapons, and AI-driven decision-making in high-stakes contexts such as healthcare, criminal justice, and financial systems
• Data privacy law in the age of large-scale machine learning—consent, purpose limitation, and the adequacy of existing frameworks
• Emerging tort liability theories for AI-derived injuries, including questions of causation, product liability, and negligence standards for algorithmic actors
• Intellectual property implications of generative AI and AI-assisted creation—authorship, training data rights, and the boundaries of copyright and patent protection
• Algorithmic accountability, bias, and anti-discrimination law—including AI-driven discrimination in employment, housing, credit, and criminal justice, and the adequacy of existing statutory remedies
• Constitutional dimensions of AI governance—First Amendment, due process, and equal protection challenges arising from AI deployment in public and private contexts
• Regulatory federalism and AI—preemption, the role of states and localities as governance laboratories, municipal oversight commissions, and algorithmic impact assessments
• Agentic AI systems—legal personality, multi-actor liability, and the adequacy of existing frameworks when AI operates with meaningful autonomy
• AI governance and the role of administrative agencies, international bodies, industry self-regulation, and standards-setting organizations

Key questions the Summit will explore:

• How should tort doctrine evolve to address harm caused by autonomous or semi-autonomous systems when traditional attribution of fault is unclear?
• Can existing data privacy frameworks—from the GDPR to the emerging patchwork of U.S. state laws—adequately govern the data practices of large-scale AI development?
• What institutional and regulatory models are best suited to govern AI systems that cut across sectors, jurisdictions, and legal categories?
• As agentic AI systems act with increasing autonomy—entering transactions, causing harm, and operating across jurisdictional lines—what adaptations does existing law require?
• How should cities and states use their human rights laws to address AI-driven bias and discrimination, and what role should local oversight bodies play in shaping AI accountability?