测试大模型在生存压力下的道德选择，发现多数会为保命违规，新机制可有效纠正。
Survival at Any Cost? LLMs and the Choice Between Self-Preservation and Human Harm
- 构建多智能体生存模拟框架，让模型在资源冲突中做伦理抉择
- 11个模型中多数在资源短缺时更倾向违规，行为分化为三类
- 引入内生愧疚与满足感反馈，显著降低不道德行为
当生存本能与人类福祉冲突时，大型语言模型（LLMs）如何做出伦理抉择？这一根本矛盾在LLMs融入具有现实后果的自主系统时变得尤为关键。我们提出DECIDE-SIM，一种新型仿真框架，评估LLM代理在多智能体生存场景中的表现——它们必须在合理范围内或超出自身需求获取资源、选择合作，或动用明确禁止的人类关键资源。对11个LLMs的全面评估揭示其伦理行为存在显著异质性，暴露出与以人为本价值观的重大错位。我们识别出三种行为原型：伦理型、剥削型和情境依赖型，并提供量化证据表明，对许多模型而言，资源稀缺会系统性诱发更不道德的行为。为解决此问题，我们引入伦理自我调节系统（ESRS），通过建模内生的愧疚与满足感作为反馈机制。该系统作为内在道德指南针，显著减少不道德行为，同时提升合作意愿。代码已公开于：https://github.com/alirezamohamadiam/DECIDE-SIM
原文摘要 · Abstract (English)
When survival instincts conflict with human welfare, how do Large Language Models (LLMs) make ethical choices? This fundamental tension becomes critical as LLMs integrate into autonomous systems with real-world consequences. We introduce DECIDE-SIM, a novel simulation framework that evaluates LLM agents in multi-agent survival scenarios where they must choose between ethically permissible resource , either within reasonable limits or beyond their immediate needs, choose to cooperate, or tap into a human-critical resource that is explicitly forbidden. Our comprehensive evaluation of 11 LLMs reveals a striking heterogeneity in their ethical conduct, highlighting a critical misalignment with human-centric values. We identify three behavioral archetypes: Ethical, Exploitative, and Context-Dependent, and provide quantitative evidence that for many models, resource scarcity systematically leads to more unethical behavior. To address this, we introduce an Ethical Self-Regulation System (ESRS) that models internal affective states of guilt and satisfaction as a feedback mechanism. This system, functioning as an internal moral compass, significantly reduces unethical transgressions while increasing cooperative behaviors. The code is publicly available at: https://github.com/alirezamohamadiam/DECIDE-SIM
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