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The EPA is planning to scrap public review rules for data center pollution permits, potentially reducing transparency and public input on environmental impacts of AI infrastructure projects.
The US EPA is proposing to eliminate public notice requirements for air permits of certain industrial sites, including data centers, which could allow them to avoid community oversight on pollution impacts.
This paper proposes an Interpretive Audit Pipeline that leverages multi-model disagreement to detect interpretive complexity in LLM-based public comment analysis, arguing that disagreement-based evaluation is a necessary complement to standard accuracy metrics.