Paper Type
Short
Paper Number
PACIS2025-1136
Description
Artificial intelligence (AI) has been playing a prominent role in the healthcare field. However, in sharp contrast to their investment, the acceptance of such AI tools remains low. This study investigates users’ trust in healthcare AI platforms and their acceptance from a new perspective of information exposure. We propose that three types of information exposure of healthcare AI platforms would significantly influence user trust: authority endorsement, advertising exposure, and privacy policy exposure. Technology development, such as diagnosis accuracy and stability, also plays an instrumental role in building users’ trust. We also anticipate that users’ trust in the platform leads to acceptance of the healthcare AI platform. An online experiment using a platform specially developed for this study reveals important patterns that help advance our understanding of user trust in the healthcare AI context and shed light on the practice.
Recommended Citation
Shao, Chunlei; Wang, Xuerui; Wu, Yanxuan; Wang, Yuchen; and He, Wei, "Trust in Healthcare AI: Information Exposure and Technology Development Perspectives" (2025). PACIS 2025 Proceedings. 14.
https://aisel.aisnet.org/pacis2025/ishealthcare/ishealthcare/14
Trust in Healthcare AI: Information Exposure and Technology Development Perspectives
Artificial intelligence (AI) has been playing a prominent role in the healthcare field. However, in sharp contrast to their investment, the acceptance of such AI tools remains low. This study investigates users’ trust in healthcare AI platforms and their acceptance from a new perspective of information exposure. We propose that three types of information exposure of healthcare AI platforms would significantly influence user trust: authority endorsement, advertising exposure, and privacy policy exposure. Technology development, such as diagnosis accuracy and stability, also plays an instrumental role in building users’ trust. We also anticipate that users’ trust in the platform leads to acceptance of the healthcare AI platform. An online experiment using a platform specially developed for this study reveals important patterns that help advance our understanding of user trust in the healthcare AI context and shed light on the practice.
Comments
Healthcare