Areas of Focus

Artificial intelligence is creating legal problems that do not fit neatly within a single doctrine, regulator, or practice area. As AI systems become capable of making decisions, communicating with third parties, executing transactions, and acting with increasing autonomy, questions that once belonged primarily to technology law are reaching into evidence, agency, corporate governance, financial regulation, healthcare, professional responsibility, and other established areas of law.

My work focuses on the places where those systems meet legal frameworks built for a different technological environment. Across scholarship, legal practice, and policy work, I am particularly interested in questions of authority, attribution, accountability, and institutional design: who can authorize an AI system to act, how responsibility should be allocated when it does, what evidence is necessary to reconstruct its behavior, and how organizations should govern technologies whose capabilities may evolve faster than the rules surrounding them.

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    Autonomous AI & Agentic Systems

    Authority, delegation, attribution, liability, evidentiary integrity, machine identity, and the legal consequences of AI systems capable of planning and acting with decreasing human supervision.

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    AI Governance & Regulation

    The governance structures surrounding advanced AI systems, including organizational oversight, model deployment, risk allocation, regulatory design, and the widening gap between technical capability and existing legal doctrine.

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    AI in Regulated Industries

    How artificial intelligence interacts with legal regimes in sectors where mistakes carry unusually high consequences, particularly healthcare, financial markets, and other heavily regulated environments.

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    AI, Markets & Corporate Governance

    Algorithmic market behavior, AI-related disclosure, prediction markets, securities regulation, board oversight, and the emerging responsibilities of companies deploying autonomous systems.

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