The emergence of economic rationality of GPT

It is increasingly important to examine the capacity of large language models like Generative Pre-trained Transformer model (GPT) beyond language processing. We instruct GPT to make risk, time, social, and food decisions and measure how rational these decisions are. We show that GPT's decisions are mostly rational and even score higher than human decisions. The performance is affected by the way questions are framed, but not by settings of demographic information and randomness. Moreover, the estimated preference parameters of GPT, compared to those of human subjects, are slightly different and exhibit a substantially higher degree of homogeneity. Overall, these findings suggest that GPT could have the potential in assisting human decision-making, but more research is needed to fully assess their performance and underpinnings.