The emergence of economic rationality of GPT by Yiting Chen and Tracy Xiao Liu
For VoxEU
As generative pre-trained transformer (GPT) and other large language models become more prevalent, their capabilities beyond language processing will be tested. This column examines GPT’s economic rationality through budgetary decisions in risk, time, sociability, and food preferences. GPT outperforms human subjects in rationality scores, while its preference parameters differ slightly from humans and show less heterogeneity. Rationality scores remain robust to randomness and demographics but are sensitive to contextual framing. These findings highlight GPT’s decision-making potential and the need for further investigation of its limitations.In 2023, Nature’s 10 included a special non-human awardee – ChatGPT – on its annual list of ten influential ‘people’ in science, acknowledging the significant role this human-language-mimicking artificial intelligence has played in the advancement of science. Generative pre-trained transformer (GPT) – and large language models (LLMs) more broadly – have impressed the world with their fluency in various tasks, including writing, coding, solving mathematical problems, and acting like humans (Biancotti and Camassa 2023, Noy and Zhang 2023). There is an ongoing discussion about wider applications of this technology, particularly in supporting decision-making at both individual and collaborative levels (Ramge and Mayer-Schönberger 2023). In this context, the question arises: can GPT make high-quality decisions?
Rationality, a classic idea in economics, helps us understand this question by theoretically capturing the extent to which a decision-maker maximises some well-behaved utility functions under given budget constraints (Afriat 1967). In practice, rationality has been widely used to measure the quality of decision-making. It has been applied in human decisions in laboratory environments, surveys, and grocery stores and linked with occupation, income, and wealth differences across individuals as well as development gaps across countries (Choi et al. 2014, Cappelen et al. 2023). Rationality is used in various fields and has even been studied in other species, such as monkeys (Chen et al. 2006).
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ABOUT THE AUTHORS
Tracy Xiao Liu is an associate Professor in economics at School of Economics and Management, Tsinghua University. She received her B.E. from Renmin University of China in 2006, and Ph.D from University of Michigan in 2012. Her main research interests are experimental and behavioral economics, and Econ-CS. Currently she is an associate editor for Management Science, Journal of Economic Behaviour and Organisation and Journal of Behavioural and Experimental Economics.
Yiting Chen is an assistant professor in the Department of Economics, Lingnan University. She received her Bachelor's degree from Zhejiang University in 2017, and Ph.D. in Economics at the National University of Singapore in 2022. Her research interests are behavioural and experimental economics, with a focus on decision-making under uncertainty, moral behaviour, and their interaction with artificial intelligence.
