医疗保健中人工智能驱动决策的公众认知：一种结构方程建模方法

中文摘要 AI 辅助

人工智能日益融入医疗保健以支持诊断、决策和行政流程。其成功实施不仅取决于技术性能，还取决于公众对其有用性、风险和公平性的认知。本研究通过对正在进行的纵向调查小组第一波数据（3915名受访者）进行结构方程建模，来考察公众对医疗保健中自动化决策的认知。将对医疗保健中自动化决策的有用性、风险性和公平性的认知作为因变量，把人工智能素养、对不同形式人工智能的熟悉程度等作为外生变量。结果显示，对不同形式人工智能更熟悉等与更高的感知有用性相关；使用对话代理与更低的感知风险相关等。公众对医疗保健中自动化决策的认知受技术熟悉程度、对话代理的使用和对人为监督的信心影响。总体而言，自动化决策的感知有用性和公平性更多地由对医疗专业人员的信任而非对技术本身的信任驱动。

英文摘要

Artificial intelligence (AI) is increasingly integrated into healthcare to support diagnostics, decision-making, and administrative processes. However, the successful implementation of AI depends not only on technical performance but also on public perceptions of its helpfulness, riskiness, and fairness. This study examines public perceptions of automated decision-making (ADM) in healthcare. Data were drawn from the first wave of an ongoing longitudinal survey panel. The final sample consisted of 3,915 respondents and was analyzed with structural equation modeling. Perceptions of ADM in healthcare as helpful, risky, and fair were treated as the dependent variables. AI literacy, familiarity with different forms of AI, confidence in clinicians' ability to distinguish AI- from human-generated content, use of conversational agents for health information, and use of traditional digital health information sources were included as exogenous. Greater familiarity with different forms of AI, higher confidence in the clinician's ability to recognize AI-generated content, and use of conversational agents for health information were associated with greater perceived helpfulness. Use of conversational agents was associated with lower perceived risk, whereas greater familiarity with AI and greater reliance on traditional health information sources were associated with higher perceived risk. Perceptions of ADM as fair were most strongly predicted by confidence in the clinician's ability, with additional small positive associations with AI familiarity, AI literacy, and use of conversational agents. Public perceptions of ADM in healthcare are shaped by technological familiarity, use of conversational agents, and confidence in human oversight. Overall, ADM's perceived helpfulness and fairness are driven more by trust in healthcare professionals than by trust in the technology itself.

发表机构

• Amsterdam School of Communication Research/ASCoR（阿姆斯特丹传播研究学院/ASCoR）
• University of Amsterdam（阿姆斯特丹大学）

机构由 AI 辅助整理，请以论文原文为准。