arXiv — NLP / Computation & Language · · 3 min read

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

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Computer Science > Artificial Intelligence

arXiv:2609.05036 (cs)
[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.
Comments: Accepted for publication in the Paris Journal of AI and Digital Ethics (2026); presented at PCAIDE 2026
Subjects: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computers and Society (cs.CY)
ACM classes: I.2.0; I.2.11; K.4.1
Cite as: arXiv:2609.05036 [cs.AI]
  (or arXiv:2609.05036v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2609.05036
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Daan R. Henselmans [view email]
[v1] Fri, 4 Sep 2026 11:56:44 UTC (1,394 KB)
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