Language-based game theory in the age of artificial intelligence
<|reference_start|>Language-based game theory in the age of artificial intelligence: 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 analyzing 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.<|reference_end|>
@article{capraro2024language-based,
    title={Language-based game theory in the age of artificial intelligence},
    author={Valerio Capraro, Roberto Di Paolo, Matjaz Perc, Veronica Pizziol},
    journal={J. R. Soc. Interface 21, 20230720 (2024)},
    year={2024},
    doi={10.1098/rsif.2023.0720},
    archivePrefix={arXiv},
    eprint={2403.08944},
    primaryClass={cs.GT cs.AI cs.CY econ.TH}
}