Algorithmic approaches for assessing pollution reduction policies can reveal shifts in environmental protection of minority communities, according to Stanford researchers

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Applying machine learning to a U.S. Environmental Protection Agency initiative reveals how key design elements determine what communities bear the burden of pollution. The approach could help ensure fairness and accountability in machine learning used by government regulators.