Work

Privacy disclosure to large language models: A large-scale study on awareness, benefits, and concerns in health contexts across three countries

Year: 2025

Type: article

Abstract: Privacy has emerged as a critical societal concern in large language models (LLMs). Designing an effective and usable privacy experience for end-users requires more than technical mitigation; it necessitates a careful understanding and balancing of the risks and benefits perceived by the public. To identify public perceptions toward LLMs, we surveyed 1,073 individuals from the United States, the United Kingdom, and South Korea across three healthcare settings. The findings revealed that privacy concerns related to data leaks and disclosure without consent are major issues for end-users. However, the potential for personalization and public benefits outweighed these concerns and positively contributed to the willingness to disclose personal data. We examined the consistency of privacy perception across three countries and highlighted the need for culturally tailored approaches to privacy design. Finally, we discuss the legal implications of our research and the opportunities to deploy responsible and privacy-preserving systems.

Source: Computers in Human Behavior Reports

DOI: 10.1016/j.chbr.2025.100841