Fine for others but not for me: The role of perspective in patients’ perception of artificial intelligence in online medical platforms

Matthias F.C. Hudecek , Eva Lermer , Susanne Gaube , Julia Cecil , Silke F. Heiss , Falk Batz
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Abstract

In the near future, online medical platforms enabled by artificial intelligence (AI) technology will become increasingly more prevalent, allowing patients to use them directly without having to consult a human doctor. However, there is still little research from the patient's perspective on such AI-enabled tools. We, therefore, conducted a preregistered 2x3 between-subjects experiment (N = 266) to examine the influence of perspective (oneself vs. average person) and source of advice (AI vs. male physician vs. female physician) on the perception of a medical diagnosis and corresponding treatment recommendations. Results of robust ANOVAs showed a statistically significant interaction between the source of advice and perspective for all three dependent variables (i.e., evaluation of the diagnosis, evaluation of the treatment recommendation, and risk perception). People prefer the advice of human doctors to an AI when it comes to their own situation. In contrast, the participants made no differences between the sources of medical advice when it comes to assessing the situation of an average person. Our study contributes to a better understanding of the patient's perspective of modern digital health technology. As our findings suggest the perception of AI-enabled diagnostic tools is more critical when it comes to oneself, future research should examine the relevant factors that influence this perception.

对别人很好,对我却不好视角在患者对在线医疗平台人工智能感知中的作用
在不久的将来,由人工智能(AI)技术驱动的在线医疗平台将变得越来越普遍,患者无需咨询人类医生即可直接使用这些平台。然而,从患者角度出发对这类人工智能工具的研究仍然很少。因此,我们进行了一项预先登记的 2x3 主体间实验(N = 266),以研究视角(自己与普通人)和建议来源(人工智能与男医生与女医生)对医疗诊断感知和相应治疗建议的影响。稳健方差分析的结果表明,在所有三个因变量(即对诊断的评价、对治疗建议的评价和风险认知)中,建议来源和视角之间存在统计学意义上的显著交互作用。在涉及自身情况时,人们更喜欢人类医生的建议,而不是人工智能。相比之下,在评估普通人的情况时,参与者对不同来源的医疗建议并无差异。我们的研究有助于更好地了解患者对现代数字医疗技术的看法。我们的研究结果表明,当涉及到自身时,对人工智能诊断工具的看法更为关键,因此未来的研究应探讨影响这种看法的相关因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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