Designing AI Systems that Support Fairness Across Distributive, Procedural, and Interactional Justice Dimensions

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AI fairness encompasses distributive, procedural, and interactional justice to foster trust and legitimacy.
The design of AI systems can incorporate processes aimed at achieving fair distribution of resources and results.
Techniques like bias mitigation and algorithmic transparency are critical for enhancing fairness in AI applications.
Addressing current issues such as data bias remains essential for better human values alignment in AI systems.

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This article explores design principles for AI systems, highlighting fairness in distributive, procedural, and interactional justice.

Singh et al. (2025) studied this question.

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