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Governing AI’s Footprint: A Scalable Human-AI Workflow to Extract Zoning Codes for Data Centers and Renewable Energy Sitting

This project addresses the societal and environmental impacts of generative AI by targeting the opaque and inconsistent zoning regulations that govern data centers and renewable energy facilities. It proposes a human-AI workflow to extract structured zoning information across six Midwest states, creating a searchable, transparent, and replicable database. The resulting tools aim to support sustainable, equitable, and policy-aligned infrastructure planning in the AI era.

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