Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology and artificial intelligence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional models try to explain human behaviour as a function of the outcomes of available actions, recent experimental research reveals that linguistic content significantly impacts decision-making, thus prompting a paradigm shift from outcome-based to language-based utility functions. This shift is more urgent than ever, given the advancement of generative AI, which has the potential to support humans in making critical decisions through language-based interactions. We propose sentiment analysis as a fundamental tool for this shift and take an initial step by analysing 61 experimental instructions from the dictator game, an economic game capturing the balance between self-interest and the interest of others, which is at the core of many social interactions. Our meta-analysis shows that sentiment analysis can explain human behaviour beyond economic outcomes. We discuss future research directions. We hope this work sets the stage for a novel game-theoretical approach that emphasizes the importance of language in human decisions.

Capraro, V., Di Paolo, R., Perc, M., Pizziol, V. (2024). Language-based game theory in the age of artificial intelligence. JOURNAL OF THE ROYAL SOCIETY INTERFACE, 21(212), 20230720-20230728 [10.1098/rsif.2023.0720].

Language-based game theory in the age of artificial intelligence

Pizziol, Veronica
2024

Abstract

Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology and artificial intelligence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional models try to explain human behaviour as a function of the outcomes of available actions, recent experimental research reveals that linguistic content significantly impacts decision-making, thus prompting a paradigm shift from outcome-based to language-based utility functions. This shift is more urgent than ever, given the advancement of generative AI, which has the potential to support humans in making critical decisions through language-based interactions. We propose sentiment analysis as a fundamental tool for this shift and take an initial step by analysing 61 experimental instructions from the dictator game, an economic game capturing the balance between self-interest and the interest of others, which is at the core of many social interactions. Our meta-analysis shows that sentiment analysis can explain human behaviour beyond economic outcomes. We discuss future research directions. We hope this work sets the stage for a novel game-theoretical approach that emphasizes the importance of language in human decisions.
2024
Capraro, V., Di Paolo, R., Perc, M., Pizziol, V. (2024). Language-based game theory in the age of artificial intelligence. JOURNAL OF THE ROYAL SOCIETY INTERFACE, 21(212), 20230720-20230728 [10.1098/rsif.2023.0720].
Capraro, Valerio; Di Paolo, Roberto; Perc, Matjaž; Pizziol, Veronica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/992269
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