Standard OLS fairness tests for deterministic pricing algorithms use invalid standard errors; corrected estimators reveal that all 34 tested Illinois auto insurers discriminate against minority zip codes.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
UD-DML creates balanced representative subsamples via uniform design in PCA space for efficient double machine learning estimation of average treatment effects on large datasets.
Data equity, prediction equity, and decision equity are distinct statistical requirements that need separate evaluations to address how racial biases in pulse oximetry measurements lead to treatment disparities.
citing papers explorer
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Fairness Testing for Algorithmic Pricing
Standard OLS fairness tests for deterministic pricing algorithms use invalid standard errors; corrected estimators reveal that all 34 tested Illinois auto insurers discriminate against minority zip codes.
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UD-DML: Uniform Design Subsampling for Double Machine Learning over Massive Data
UD-DML creates balanced representative subsamples via uniform design in PCA space for efficient double machine learning estimation of average treatment effects on large datasets.
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Data (in)equities in data science: Dissecting systemic and systematic biases in pulse oximetry
Data equity, prediction equity, and decision equity are distinct statistical requirements that need separate evaluations to address how racial biases in pulse oximetry measurements lead to treatment disparities.