Under scarcity, higher ranking accuracy amplifies between-group disparities exponentially, so debiasing inputs alone cannot eliminate allocative inequality.
Liu, Solon Barocas, Jon Kleinberg, and Karen Levy
4 Pith papers cite this work, alongside 7 external citations. Polarity classification is still indexing.
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Perspective paper proposing an integrated framework for automated decision systems that shifts priority from prediction accuracy to accounting for changes in organizational workflows and intervention effects.
Prioritization algorithms in public services generate relative disparities among intersectional groups as resources become scarce, intensifying perceptions of inequality.
citing papers explorer
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The Accuracy Trap: Structural Scarcity Amplifies Relative Inequality in Algorithmic Allocation
Under scarcity, higher ranking accuracy amplifies between-group disparities exponentially, so debiasing inputs alone cannot eliminate allocative inequality.
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Bridging Predictions and Interventions: An Integrated Framework for Automated Decision-Systems
Perspective paper proposing an integrated framework for automated decision systems that shifts priority from prediction accuracy to accounting for changes in organizational workflows and intervention effects.
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The Paradox of Prioritization in Public Sector Algorithms
Prioritization algorithms in public services generate relative disparities among intersectional groups as resources become scarce, intensifying perceptions of inequality.
- Scarcity and Predictive Uncertainty: Implications for Societal Resource Allocation