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Accounting for Context: Shaping Moral Credences for Value Alignment

arXiv 2606.06972 ↗First posted 5 Jun 2026cs.AIcited by 0

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Abstract (arXiv)

Ensuring that agent behaviours are aligned with human moral values inevitably raises the problem of how to account for the plurality of moral perspectives that societies -- and even individuals -- typically adopt. Work on moral uncertainty proposes mechanisms to fairly and democratically aggregate evaluations of actions across different moral theories. However, this paper argues that one needs to account for contextual factors when aggregating moral evaluations. For example, consequentialist perspectives assume an ability to accurately determine how an agent's actions change the world; an assumption that often does not hold in real world settings. We, therefore, formalise agent decision making under moral uncertainty, while also accounting for these kinds of contextual factors. We thereby show that a seemingly commonsensical property -- the weak Pareto principle -- is violated. We argue that this apparent problem is, in fact, a variation of Simpson's paradox, and hence reveals the limitations of aggregation mechanisms that ignore the impact of contextual factors.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 29 references that are in the map. First posted on arXiv 5 Jun 2026.

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References · 5

  1. 2020Artificial Intelligence, Values and Alignmentcited by 448
  2. 2016Cooperative Inverse Reinforcement Learningcited by 300
  3. 2024Representative Social Choice: From Learning Theory to AI Alignmentcited by 8
  4. 2023On the Computational Complexity of Ethics: Moral Tractability for Minds and Machinescited by 2
  5. 2023Moral Uncertainty and the Problem of Fanaticismcited by 1

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