This essay joins recent scholarship in arguing that FAccT's fundamental framing of the potential to achieve the normative conditions for justice through bettering the design of algorithmic systems is counterproductive to achieving said justice in practice. Insofar as the FAccT community's research tends to prioritize design-stage interventions, it ignores the fact that the majority of the contextual factors that practically determine FAccT outcomes happen in the implementation and impact stages of AI/ML lifecycles.
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Gansky et al. (2022) studied this question.
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