Does AI explainability affect physicians’ intention to use AI?

前因(行为心理学) 情感(语言学) 概念模型 心理学 结构方程建模 医疗保健 考试(生物学) 知识管理 质量(理念) 卫生技术 实证研究 服务(商务) 应用心理学 计算机科学 社会心理学 营销 业务 机器学习 统计 古生物学 沟通 经济增长 数学 经济 数据库 哲学 认识论 生物
作者
Chung‐Feng Liu,Zhih‐Cherng Chen,Szu-Chen Kuo,Tzu-Chi Lin
出处
期刊:International Journal of Medical Informatics [Elsevier]
卷期号:168: 104884-104884 被引量:69
标识
DOI:10.1016/j.ijmedinf.2022.104884
摘要

Artificial Intelligence (AI) is increasingly being developed to support clinical decisions for better health service quality, but the adoption of AI in hospitals is not as popular as expected. A possible reason is that the unclear AI explainability (XAI) affects the physicians' consideration of adopting the model.To propose and validate an innovative conceptual model aimed at exploring physicians' intention to use AI with XAI as an antecedent variable of technology trust (TT) and perceived value (PV).A questionnaire survey was conducted to collect data from physicians of three hospitals in Taiwan. Structural equation modeling (SEM) was used to validate the proposed model and test the hypotheses.A total of 295 valid questionnaires were collected. The research results showed that physicians expressed a high intention to use AI. The XAI was found to be of great importance and had a significant impact both on AI TT and PV. We also observed that TT in AI had a significant impact on PV. Moreover, physicians' PV and TT in AI had a significant impact on their behavioral intention to use AI (BI). However, XAI's impact on BI cannot be proved.The conceptual model developed in this study provides empirical evidence that could be used as guidelines to effectively explore physicians' intention to use medical AI from the antecedent of XAI. Our findings contribute crucial AI-human interaction insights in health care studies.
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