Using Language Models to Decipher the Motivation Behind Human Behaviors

Abstract

AI presents a novel tool for deciphering the motivations behind human behaviors.  By varying prompts to a large language model, we can elicit the full range of human behaviors in a variety of different scenarios in classic economic games. By analyzing which prompts elicit which behaviors, we  infer (decipher) the motivations behind the human behaviors.  We also show how one can analyze the prompts to reveal relationships between the classic economic games, providing insight into what different economic scenarios induce people to think about. We also show how this deciphering process can be used to understand differences in the behavioral tendencies of different populations. We show how AI offers a new way to examine the thinking and framing that produce different behaviors.

Keywords: large language model, human behavior, behavioral code, artificial intelligence, AI behavior, experiments, games