Using AI in NEPA Review: Legal Challenges and Judicial Scrutiny
Examines the procedural obligations and judicial review risks of AI-assisted environmental impact statements, with safeguards for transparency, explainability, and human oversight.
01 / SCHOLARSHIP
Research & writing
My work examines the procedural foundations of environmental governance: how decisions are made, whose reasoning counts, and how institutions remain accountable as technologies change.
Publications & forthcoming work
Bridging Efficiency and Legitimacy: The Role of Community Benefits Agreements in NEPA’s Offshore Wind Review
Explores how community benefits agreements can strengthen participation and procedural legitimacy while supporting renewable energy permitting.
The Algorithmic Hard Look 2.0: Rethinking Judicial Oversight of AI-Generated EISs
Develops a reliability-based framework for reviewing AI-generated environmental analyses under NEPA’s “hard look” doctrine.
AI Attribution and Reliability in U.S. Federal Environmental Review
Proposes an Attribution and Adoption Test and a Hard Look 2.0 standard to assess agency ownership and the reliability of AI-assisted environmental analysis.
Preprints & working papers
Who Speaks for the Algorithm? Attribution in Environmental Decision Making
Examines when algorithmic analysis can be treated as agency reasoning for judicial review, through the Attribution and Adoption Test.
The Invisible Analyst: AI-Assisted Decisionmaking and the Administrative Record
Investigates how internal generative AI changes the relationship between analytical production, agency review, and the NEPA administrative record.
AI Data Centers in a NEPA Void
Introduces “Shadow NEPA” to explain how local agreements reconstruct disclosure, participation, and accountability around AI infrastructure.
Large Language Model-Facilitated National Review on the Use of Ecological Tools and Processes in Environmental Impact Statements (EIS) in the U.S. with Demonstrated Use Cases for Environmental Planners, Legal Practitioners, and Researchers
An interdisciplinary study using a RAG–LLM pipeline to analyze more than 2,000 federal environmental impact statements.
Work in progress
What the Agency Hears: AI, Public Comments, and the Construction of the NEPA Administrative Record
Examines AI-assisted classification and summarization of public comments and proposes a reviewable representation standard for agency validation, adoption, and record preservation.
Let’s connect.
For academic opportunities, research conversations, and collaboration.