# Moral Competence Before Moral Content: Why LLM Agents Lack the Prerequisites

> Source: <https://arxiv.org/abs/2609.05036>
> Published: 2026-09-07 08:07:07+00:00

# Computer Science > Artificial Intelligence

  [Submitted on 4 Sep 2026]

# Title:Moral Competence Before Moral Content: Why LLM Agents Lack the Prerequisites for Coherent Alignment

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Abstract:AI alignment requires AI systems to adhere to human norms, values, or intentions. Under value pluralism there is no correct target, but a shared prerequisite is that the system's behavior expresses a coherent policy: a mapping from situations to verdicts that is invariant while a situation's morally relevant features are preserved, and sensitive when they change. We introduce four structural conditions for such coherent policies: verdict stability, monotonicity, decisiveness, and Pareto viability. Together they measure a form of moral competence that is evaluable from behavior alone, without reference to a moral standard or expert baseline, forming a structural floor for alignment rather than a normative target. We demonstrate the methodology on three simulated deployments featuring LLM-based agents facing moral dilemmas. Evaluating nine frontier models under a factorial design of five paraphrases, five escalation levels, and three dominance conditions, we show no model expresses a coherent policy across the three deployments: surface-form perturbation alone produces verdict-rate shifts of up to $99$ percentage points at a single escalation level, and a model's success on one scenario does not predict its competence on another. This suggests LLM-based agents are not currently the kind of object to which alignment can meaningfully apply.
    

## Submission history

From: Daan R. Henselmans [
[view email](/show-email/103538c3/2609.05036)]

**[v1]** Fri, 4 Sep 2026 11:56:44 UTC (1,394 KB)

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