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Intersectionality is a critical framework that, through inquiry and praxis,allows us to examine how social inequalities persist through domains ofstructure and discipline. Given AI fairness' raison d'etre of "fairness", weargue that adopting intersectionality as an analytical framework is pivotal toeffectively operationalizing fairness. Through a critical review of howintersectionality is discussed in 30 papers from the AI fairness literature, wedeductively and inductively: 1) map how intersectionality tenets operate withinthe AI fairness paradigm and 2) uncover gaps between the conceptualization andoperationalization of intersectionality. We find that researchersoverwhelmingly reduce intersectionality to optimizing for fairness metrics overdemographic subgroups. They also fail to discuss their social context and whenmentioning power, they mostly situate it only within the AI pipeline. We: 3)outline and assess the implications of these gaps for critical inquiry andpraxis, and 4) provide actionable recommendations for AI fairness researchersto engage with intersectionality in their work by grounding it in AIepistemology.

Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness