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Research map / Learning theory and algorithms / Fairness

Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results

AAAI 2023 · Learning theory and algorithms › Fairness · approach: Causal and policy fairness in decisions · 9 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Require statistical parity in allocation alongside statistical parity in outcomesContextual resource allocation policies · General resource allocationOutcome parityHurt
Prioritize using a vulnerability score, even when it is perfectly calibratedPolicies satisfying conditional statistical parity in allocation · General resource allocationOutcome disparityHurt
Condition allocation on treatment-effect information as well as baseline-risk informationConditional statistical parity allocation policies · General resource allocationPairwise outcome disparityHelped
Use contextual features beyond baseline risk and treatment effects, without group statusPolicies conditioned on baseline-risk and treatment-effect information · General resource allocationPairwise outcome disparityHelped
Use group status in addition to baseline-risk and treatment-effect informationPolicies using all available information · General resource allocationPairwise outcome disparityHelped
Use group status when treatment effects are sufficient to offset baseline outcome differencesGroup-aware allocation policies · General resource allocationOutcome parityHelped

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