Sagit Bar-Gill: "LLMs and Consumer Bias: 'Paying Not to Go to the Gym' with an LLM Advisor?"

Large language model (LLM)–based advisors increasingly interact directly with consumers, raising the question of whether they mitigate or exacerbate well-documented consumer choice biases. We study this question in the context of gym membership purchases, where consumers are known to systematically overestimate future usage. We address three research questions: (1) Under what conditions do LLM advisors mitigate versus reinforce consumer choice bias; (2) What is the resulting consumer harm or benefit when biased consumers interact with LLM advisors; and (3) How can such harm be detected and mitigated through regulation and LLM design. To answer these questions, we conduct a field experiment in collaboration with NYU Athletics. In this experiment, prospective gym members are randomized to interact with one of two LLM advisor variants or assigned to one of three informational control conditions without LLM interaction, prior to choosing among gym membership plans. Preliminary results suggest that LLM advisors mitigate choice bias when consumers’ overestimation of future gym attendance is modest, but reinforce bias when overestimation is large. This work-in-progress will be extended to additional choice settings and aims to inform the design and regulation of consumer-facing LLM agents in markets characterized by asymmetric information, uncertainty, and systematic consumer biases.

About Sagit Bar-Gill

Sagit Bar-Gill is an assistant professor of Technology Management and Information Systems at the Coller School of Management in Tel Aviv University, and a visiting researcher at NYU’s Stern School of Business. Her research studies the economics of online markets, and the impacts of digitization on firms and consumers, using online experiments and causal inference methods. Her work has been published in top journals, including Management Science, Management of Information Systems Quarterly, and the Journal of the Association of Information Systems. Sagit holds a PhD and MA in economics, and a BSc in mathematics from Tel Aviv University.