Unequal Outcomes in Resource Allocation
資源分配結果不平等
Verification & Validation
Risk Description
When an automated review system approves applications from a particular region at a markedly lower rate; due to unmitigated control gaps, the organization monitored fairness using the overall approval rate without disaggregating by region, and discovered the disparity only after receiving collective complaints, triggering compliance exposure and operational reputational costs.
Framework Mappings
EU AI ActArt.10
NIST AI 600-1Harmful Bias and Homogenization
NIST AI RMFMEASURE 2.11
ISO/IEC TR 24027
ISO/IEC 5338運作與監控
MIT AI Risk RepositoryDomain 1
Risk Treatment & Implementation Guidance
Split fairness monitoring by region and subgroup rather than aggregate pass rates; Audit decisions for significantly disadvantaged groups, tracing the model's basis; Set alert thresholds and periodic review for collective disparities