| 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 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. |