mlsanityData to 7 Oct 2026

Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics

arXiv 2311.05227 ↗First posted 9 Nov 2023cs.AIcited by 1

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Abstract (arXiv)

Deontological ethics, specifically understood through Immanuel Kant, provides a moral framework that emphasizes the importance of duties and principles, rather than the consequences of action. Understanding that despite the prominence of deontology, it is currently an overlooked approach in fairness metrics, this paper explores the compatibility of a Kantian deontological framework in fairness metrics, part of the AI alignment field. We revisit Kant's critique of utilitarianism, which is the primary approach in AI fairness metrics and argue that fairness principles should align with the Kantian deontological framework. By integrating Kantian ethics into AI alignment, we not only bring in a widely-accepted prominent moral theory but also strive for a more morally grounded AI landscape that better balances outcomes and procedures in pursuit of fairness and justice.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 15 of its 66 references that are in the map. First posted on arXiv 9 Nov 2023.

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15 of 66 references.

References · 15

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3 more
  1. 2023Beneficent Intelligence: A Capability Approach to Modeling Benefit, Assistance, and Associated Moral Failures through AI Systemscited by 9
  2. 2021Toward a Theory of Justice for Artificial Intelligencecited by 7
  3. 2023Disentangling and Operationalizing AI Fairness at LinkedIncited by 7

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