Uncovering the fairness of AI: exploring focal point, inequality aversion, and altruism in ChatGPT's dictator game decisions

Eleonore Dodivers () and Ismael Rafai ()
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Eleonore Dodivers: GREDEG, Université Côte d'Azur, CNRS
Ismael Rafai: Toulouse School of Economics and Toulouse School of Management

Economics Bulletin, 2025, vol. 45, issue 4, 1818 - 1825

Abstract: This paper investigates Artificial intelligence Large Language Models (AI-LLM) social preferences' in Dictator Games. Brookins and Debacker (2024, Economics Bulletin) previously observed a tendency of ChatGPT-3.5 to give away half its endowment in a standard Dictator Game and interpreted this as an expression of fairness. We replicate their experiment and introduce a multiplicative factor on donations which varies the efficiency of the transfer. Varying transfer efficiency disentangles three donation explanations (inequality aversion, altruism, or focal point). Our results show that ChatGPT-3.5 donations should be interpreted as a focal point rather than the expression of fairness. In contrast, a more advanced version (ChatGPT-4o) made decisions that are better explained by altruistic motives than inequality aversion. Our study highlights the necessity to explore the parameter space, when designing experiments to study AI-LLM preferences.

Keywords: Artificial Intelligence; Large Language Models; Dictator Games; Experimental Economics; Social Preferences (search for similar items in EconPapers)
JEL-codes: C9 D7 (search for similar items in EconPapers)
Date: 2025-12-30
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