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Argues that algorithmic justifiability improves AI's fairness and trustworthiness while addressing decision-making concerns.
Most ethical guidelines on AI tout algorithmic transparency, the openness of an algorithm’s inner workings to human scrutiny, as an important desideratum in algorithmic deployment. Algorithmic transparency has been touted as important for valuable goals like procedural fairness, AI trustworthiness, contestability and planning around AI decision-making. This paper argues that these goals are better served by a distinct desideratum, algorithmic justifiability, the ability of an algorithm to provide understanding about why the algorithm’s decision is correct.
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Muralidharan et al. (2026) studied this question.
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