Using Large Language Models to Categorize Strategic Situations and Decipher Motivations Behind Human Behaviors

Significance In an increasingly fractured world, it is vital to understand when and why people cooperate with and trust others. Traditional social science techniques infer motivations from observed behaviors. We develop a technique based on the fact that as one varies the system prompts, one can get AI to generate different behaviors. Examining the content of these prompts allows us to categorize and contrast strategic situations. Because large language models are trained on extensive human-generated data and have internalized associations between motivations and behaviors, our approach provides a step toward inferring the thinking patterns associated with human decisions. We also use this technique to contrast the motivations underlying decisions across different human populations.