More Unique, More Accepting? Integrating Sense of Uniqueness, Perceived Knowledge, and Perceived Empathy with Acceptance of Medical Artificial Intelligence

Abstract

Artificial intelligence (AI) has had a profound impact on the medical industry. As the ultimate consumers, patients’ acceptance of medical AI plays an important role in realizing its widespread adoption in healthcare. However, previous studies have indicated that patients’ acceptance of medical AI is still inconsistent. This study considered the application of medical AI in different scenarios and divided them into medical AI for diagnosis and treatment (MAI-DT) and medical AI for non-diagnosis and non-treatment (MAI-NDT). Drawing on the theories of uniqueness and dehumanization, this study explored the impacts of patients’ sense of uniqueness (SOU) on their acceptance of medical AI under the two scenarios and the underlying mechanisms. Analysis of the data from 238 samples collected during the COVID-19 period in China showed that participants with a higher SOU had a lower acceptance of MAI-DT but a higher acceptance of MAI-NDT than participants with a lower SOU. In addition, perceived AI knowledge and perceived AI empathy mediated the relationship between the participants’ SOU and their acceptance of AI under the two scenarios. The theoretical and practical implications are discussed.

Keywords:

• Medical artificial intelligence
• acceptance of artificial intelligence
• sense of uniqueness
• perceived AI knowledge
• perceived AI empathy

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant Nos. 72072110;72102033]; the Shanghai Science and Technology Innovation Action Plan Soft Science Project [Grant No. 23692110000].

Notes on contributors

Zhenyao Cai

Zhenyao Cai is an associate professor in the SILC Business School, Shanghai University, Shanghai, China. His main research interests include knowledge management, leadership, as well as the impact of technological innovation on employee and organizational behavior.

Haoqing He

Haoqing He is a postgraduate student in the SILC Business School, Shanghai University, Shanghai, China. Her research focuses on the impact of technological innovation on employee and consumer behavior.

Weiwei Huo

Weiwei Huo is an associate professor in the SILC Business School, Shanghai University, China. Her research focuses on technology interference, telecommuting, and the impact of medical artificial intelligence on medical staff and patients.

Xinyu Xu

Xinyi Xu is a postgraduate student in the SILC Business School, Shanghai University, Shanghai, China. Her research focuses on the impact of technological innovation on employee and organizational behavior.