Survival at Any Cost? LLMs and the Choice Between Self-Preservation and Human Harm

• URL: http://arxiv.org/abs/2509.12190v1
• Date: Mon, 15 Sep 2025 17:53:11 GMT
• Title: Survival at Any Cost? LLMs and the Choice Between Self-Preservation and Human Harm
• Authors: Alireza Mohamadi, Ali Yavari,
• Abstract summary: We introduce DECIDE-SIM, a novel simulation framework that evaluates Large Language Models (LLMs) in multi-agent survival scenarios.<n>Our comprehensive evaluation of 11 LLMs reveals a striking heterogeneity in their ethical conduct, highlighting a critical misalignment with human-centric values.<n>We introduce an Ethical Self-Regulation System (ESRS) that models internal affective states of guilt and satisfaction as a feedback mechanism.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: 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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