Introduces a taxonomy of model, feedback, and prediction uncertainty in sequential decisions and demonstrates that accounting for uneven uncertainty across groups can reduce outcome variance for disadvantaged populations while preserving institutional objectives.
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Fairness under uncertainty in sequential decisions
Introduces a taxonomy of model, feedback, and prediction uncertainty in sequential decisions and demonstrates that accounting for uneven uncertainty across groups can reduce outcome variance for disadvantaged populations while preserving institutional objectives.