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Bounded Morality Framework Defines AI Ethical Computation Limits.

Max Kanwal, Caryn Tran, Patrick Mineault· July 2, 2026 View original

Summary

This paper introduces "Bounded Morality," a framework extending bounded rationality to moral cognition, formalizing moral situations by "moral breadth" and "moral depth" to analyze the computational demands faced by finite agents, including AI. It suggests ethical theories are efficient strategies within these computational limits.

Traditional views of moral cognition often frame it as adherence to fixed ethical theories like deontology or consequentialism. However, new research proposes "Bounded Morality," a formal framework that extends Herbert Simon's concept of bounded rationality to the realm of moral problems, particularly for agents with finite computational resources, such as AI. The framework characterizes moral situations along two dimensions: "moral breadth," which is the scope of entities considered morally relevant, and "moral depth," which refers to the inferential complexity needed to evaluate their interactions. It argues that limited resources necessitate a trade-off between these dimensions, defining a feasible space for moral computation. Within this space, established ethical theories are seen as locally efficient strategies adapted to different computational demands, rather than competing truths. This perspective implies that aligning AI morally depends on how its moral reasoning capacity is scaled and allocated, rather than simply imitating human judgments.

Why it matters

For AI developers and ethicists, this framework provides a new lens to understand the inherent computational limits of moral reasoning in AI, guiding the design of more realistic and robust ethical AI systems.

How to implement this in your domain

  1. 1Assess the "moral breadth" and "moral depth" requirements for specific AI applications.
  2. 2Design AI systems with explicit resource allocation strategies for moral reasoning.
  3. 3Develop evaluation metrics for AI morality that account for computational bounds and trade-offs.
  4. 4Consider how different ethical theories can be implemented as efficient strategies within AI's computational limits.

Who benefits

AI DevelopmentEthics & GovernanceRoboticsAutonomous Systems

Key takeaways

  • Moral cognition, like rationality, is bounded by computational resources.
  • Moral problems can be analyzed by "moral breadth" and "moral depth."
  • Ethical theories are efficient strategies within these computational limits.
  • AI moral alignment depends on scaling and allocating reasoning capacity, not just imitation.

Original post by Max Kanwal, Caryn Tran, Patrick Mineault

"arXiv:2607.00002v1 Announce Type: new 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…"

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Originally posted by Max Kanwal, Caryn Tran, Patrick Mineault on X · view source

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