Selection in the Presence of Implicit Bias: The Advantage of Intersectional Constraints
This addresses inequality in hiring and admissions for marginalized groups, offering a novel approach to mitigate bias, but it is incremental as it builds on prior work on constraints.
The paper tackles the problem of implicit bias in selection processes like hiring, where intersectionality (multiple affected groups) leads to extreme bias, showing that intersectional constraints can recover almost all utility achievable without bias, compared to non-intersectional constraints that only recover part.
In selection processes such as hiring, promotion, and college admissions, implicit bias toward socially-salient attributes such as race, gender, or sexual orientation of candidates is known to produce persistent inequality and reduce aggregate utility for the decision maker. Interventions such as the Rooney Rule and its generalizations, which require the decision maker to select at least a specified number of individuals from each affected group, have been proposed to mitigate the adverse effects of implicit bias in selection. Recent works have established that such lower-bound constraints can be very effective in improving aggregate utility in the case when each individual belongs to at most one affected group. However, in several settings, individuals may belong to multiple affected groups and, consequently, face more extreme implicit bias due to this intersectionality. We consider independently drawn utilities and show that, in the intersectional case, the aforementioned non-intersectional constraints can only recover part of the total utility achievable in the absence of implicit bias. On the other hand, we show that if one includes appropriate lower-bound constraints on the intersections, almost all the utility achievable in the absence of implicit bias can be recovered. Thus, intersectional constraints can offer a significant advantage over a reductionist dimension-by-dimension non-intersectional approach to reducing inequality.