What is it about?
We analyze the Terms and Conditions of online shopping websites to detect unfair or unfavorable financial terms. We built tools (TermMiner and TermLens) and a dataset (ShopTC-100K) to help identify and study these terms at scale using AI (Large Language Models).
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Why is it important?
Unfavorable financial terms—like hidden subscriptions or strict refund policies—can cause real financial harm to unsuspecting consumers. Our work enables the first large-scale analysis of such terms by developing a taxonomy and an automated detection system.
Perspectives
This paper is one of the first to systematically analyze unfavorable financial terms in e-commerce terms and conditions. By combining large-scale data collection, taxonomy development, and LLM-based detection, it bridges AI and consumer protection to expose financial risks hidden in the fine print.
Elisa Tsai
University of Michigan
Read the Original
This page is a summary of: Harmful Terms and Where to Find Them: Measuring and Modeling Unfavorable Financial Terms and Conditions in Shopping Websites at Scale, April 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3696410.3714573.
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