The Moral Mind(s) of Large Language Models

• URL: http://arxiv.org/abs/2412.04476v2
• Date: Tue, 11 Feb 2025 10:35:02 GMT
• Title: The Moral Mind(s) of Large Language Models
• Authors: Avner Seror,
• Abstract summary: Key questions arise as large language models (LLMs) become integrated into decision-making across various sectors.<n>We present approximately forty models from major providers with a structured set of ethical scenarios.<n>Our rationality tests revealed that at least one model from each provider exhibited behavior consistent with approximately stable moral principles.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As large language models (LLMs) become integrated into decision-making across various sectors, key questions arise: do they exhibit an emergent "moral mind" - a consistent set of moral principles guiding their ethical judgments - and is this reasoning uniform or diverse across models? To investigate this, we presented approximately forty models from major providers with a structured set of ethical scenarios, creating one of the largest datasets of its kind. Our rationality tests revealed that at least one model from each provider exhibited behavior consistent with approximately stable moral principles, effectively acting as if nearly optimizing a utility function encoding ethical reasoning. We estimated these utility functions and found that models tend to cluster around neutral ethical stances. To further characterize moral heterogeneity, we applied a non-parametric permutation approach, constructing a probabilistic similarity network based on revealed preference patterns. This analysis showed that while approximately rational models share a core ethical structure, differences emerged: roughly half displayed greater moral adaptability, bridging diverse perspectives, while the remainder adhered to more rigid ethical structures.

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