LLMs driven products were increasingly prevalent in our daily lives, With a natural language based interaction style, people may potentially leak their personal private information. Thus, privacy policy and user agreement played an important role in regulating and alerting people. However, there lacked the work examining the reading of LLM's privacy policy. Thus, we conducted the first user study to let participants read the privacy policy and user agreement with two different styles (a cursory and detailed style). We found users lack important information upon cursory reading and even detailed reading. Besides, their privacy concerns was not solved even upon detailed reading. We provided four design implications based on the findings.
@article{arxiv.2406.18100,
title = {Natural Language but Omitted? On the Ineffectiveness of Large Language Models' privacy policy from End-users' Perspective},
author = {Shuning Zhang and Haobin Xing and Xin Yi and Hewu Li},
journal= {arXiv preprint arXiv:2406.18100},
year = {2024}
}