The Accuracy Trap: Structural Scarcity Amplifies Relative Inequality in Algorithmic Allocation
arXiv:2608.11491v1 Announce Type: new Abstract: Algorithmic systems increasingly rank individuals for access to scarce public resources, from child welfare interventions to cancer treatment referrals. The prevailing fairness frame treats disparity as a property of biased data or deficient models, with remedies through calibration and debiasing. Under structural scarcity, where demand exceeds supply by an order of magnitude, allocation becomes a rationing problem, and the statistical properties o
Record details
Published: 13 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness · Children & education
Retrieved: 13 August 2026
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ethics.ai (13 August 2026), “The Accuracy Trap: Structural Scarcity Amplifies Relative Inequality in Algorithmic Allocation,” evidence record 18714, https://ethics.ai/record/18714 (originally published by arXiv cs.CY).
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