mlsanityData to 14 Oct 2026

Towards Theory-based Moral AI: Moral AI with Aggregating Models Based on Normative Ethical Theory

arXiv 2306.11432 ↗First posted 20 Jun 2023cs.AI cs.CLcited by 8

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Abstract (arXiv)

Moral AI has been studied in the fields of philosophy and artificial intelligence. Although most existing studies are only theoretical, recent developments in AI have made it increasingly necessary to implement AI with morality. On the other hand, humans are under the moral uncertainty of not knowing what is morally right. In this paper, we implement the Maximizing Expected Choiceworthiness (MEC) algorithm, which aggregates outputs of models based on three normative theories of normative ethics to generate the most appropriate output. MEC is a method for making appropriate moral judgments under moral uncertainty. Our experimental results suggest that the output of MEC correlates to some extent with commonsense morality and that MEC can produce equally or more appropriate output than existing methods.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 17 of its 35 references that are in the map. First posted on arXiv 20 Jun 2023.

Builds on

17 of 35 references.

References · 17

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5 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 4; 2026: 1.

8 papers.