Prospect Theory Fails for LLMs: Revealing Instability of Decision-Making under Epistemic Uncertainty

• URL: http://arxiv.org/abs/2508.08992v1
• Date: Tue, 12 Aug 2025 15:02:16 GMT
• Title: Prospect Theory Fails for LLMs: Revealing Instability of Decision-Making under Epistemic Uncertainty
• Authors: Rui Wang, Qihan Lin, Jiayu Liu, Qing Zong, Tianshi Zheng, Weiqi Wang, Yangqiu Song,
• Abstract summary: It remains largely unexplored whether Prospect Theory applies to contemporary Large Language Models.<n>We propose a more general and precise evaluation framework to model LLMs' decision-making behaviour under PT.<n>Our findings suggest that modelling LLMs' decision-making with PT is not consistently reliable.
• Score: 41.94502767947584
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Prospect Theory (PT) models human decision-making under uncertainty, while epistemic markers (e.g., maybe) serve to express uncertainty in language. However, it remains largely unexplored whether Prospect Theory applies to contemporary Large Language Models and whether epistemic markers, which express human uncertainty, affect their decision-making behaviour. To address these research gaps, we design a three-stage experiment based on economic questionnaires. We propose a more general and precise evaluation framework to model LLMs' decision-making behaviour under PT, introducing uncertainty through the empirical probability values associated with commonly used epistemic markers in comparable contexts. We then incorporate epistemic markers into the evaluation framework based on their corresponding probability values to examine their influence on LLM decision-making behaviours. Our findings suggest that modelling LLMs' decision-making with PT is not consistently reliable, particularly when uncertainty is expressed in diverse linguistic forms. Our code is released in https://github.com/HKUST-KnowComp/MarPT.

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