Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants 事件

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants arXiv:2508.08337v3 Announce Type: replace-cross Abstract: Algorithmic fairness research has largely framed unfairness as discrimination along sensitive attributes. However, this approach limits visibility into unfairness as structural injustice instantiated through social determinants, which are contextual variables that shape attributes and outcomes without pertaining to specific ind