# Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions

arXiv: https://arxiv.org/abs/2604.21871 · HTML: https://mlsanity.com/paper/2604.21871/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 31 references that are in the map.
- First posted on arXiv 23 Apr 2026.

## Builds on (most cited first, 6 of 6)

- [Language Model Alignment in Multilingual Trolley Problems](https://mlsanity.com/paper/2407.02273/) (2024)
- [Measuring Moral Dimensions in Social Media with Mformer](https://mlsanity.com/paper/2311.10219/) (2023)
- [Decolonial AI Alignment: Openness, Vi'sedsa-Dharma, and Including Excluded Knowledges](https://mlsanity.com/paper/2309.05030/) (2023)
- [Exploring Persona-dependent LLM Alignment for the Moral Machine Experiment](https://mlsanity.com/paper/2504.10886/) (2025)
- [A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptive](https://mlsanity.com/paper/2402.11005/) (2024)
- [Moral Outrage Shapes Commitments Beyond Attention: Multimodal Moral Emotions on YouTube in Korea and the US](https://mlsanity.com/paper/2601.21815/) (2026)

## Built on by (most cited first, 1 of 1)

- [Hidden in the Request: Explaining Unethical LLM Compliance through Token Relevance](https://mlsanity.com/paper/2608.23264/) (2026)

## Abstract (arXiv)

Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decision-support systems, determining whether they encode these social nuances is critical. We characterize machine behavior using the Whistleblower's Dilemma by varying two experimental dimensions: crime severity and relational closeness. Our study evaluates three distinct perspectives: (1) moral rightness (prescriptive norms), (2) predicted human behavior (descriptive social expectations), and (3) autonomous model decision-making. By analyzing the reasoning processes, we identify a clear cross-perspective divergence: while moral rightness remains consistently fairness-oriented, predicted human behavior shifts significantly toward loyalty as relational closeness increases. Crucially, model decisions align with moral rightness judgments rather than their own behavioral predictions. This inconsistency suggests that LLM decision-making prioritizes rigid, prescriptive rules over the social sensitivity present in their internal world-modeling, which poses a gap that may lead to significant misalignments in real-world deployments.