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Bounded Morality: Defining the Space of Moral Computation

A new paper proposes Bounded Morality, a formal framework that extends bounded rationality to moral cognition, modeling ethical theories as locally efficient strategies within a tradeoff between moral breadth and depth.

SourcearXiv AIAuthor: Max Kanwal, Caryn Tran, Patrick Mineault

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[Submitted on 1 Apr 2026]

Title:Bounded Morality: Defining the Space of Moral Computation

View a PDF of the paper titled Bounded Morality: Defining the Space of Moral Computation, by Max Kanwal and 2 other authors

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Abstract:Moral cognition has traditionally been modeled as adherence to fixed ethical theories--deontology, consequentialism, virtue ethics--implemented as static rules or value functions. We propose Bounded Morality, a formal framework for analyzing the computational demands of moral problems faced by finite agents. Extending Herbert Simon's notion of bounded rationality, we formalize moral situations along two orthogonal dimensions: moral breadth, the scope of entities treated as morally relevant, and moral depth, the inferential integration required to evaluate their interactions. Limited resources impose an unavoidable tradeoff between these dimensions, defining a feasible space of moral computation. Within this space, ethical theories correspond to locally efficient strategies adapted to different demand regimes rather than competing accounts of moral truth. The framework yields a formal notion of moral regret and moral progress under constraint, and implies that moral alignment in artificial systems depends on the scaling and allocation of moral reasoning capacity rather than on direct imitation of human judgments.

Comments: 24 pages, 2 figures; Proceedings of the AAAI-26 Workshop on Machine Ethics

Subjects:

Artificial Intelligence (cs.AI); Computers and Society (cs.CY)

Cite as: arXiv:2607.00002 [cs.AI]

(or arXiv:2607.00002v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2607.00002

arXiv-issued DOI via DataCite

Submission history

From: Max Kanwal [view email] [v1] Wed, 1 Apr 2026 17:35:43 UTC (85 KB)

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