人工智能在医学中的 "神奇理论":专题叙事分析。

JMIR AI Pub Date : 2024-08-19 DOI:10.2196/49795
Giorgia Lorenzini, Laura Arbelaez Ossa, Stephen Milford, Bernice Simone Elger, David Martin Shaw, Eva De Clercq
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引用次数: 0

摘要

背景:围绕医学人工智能(AI)的讨论往往集中在对该技术潜力的炒作或对其未来的预言上。人工智能叙事对研究方向、资金和公众舆论具有重大影响,从而塑造了医学的未来:本文旨在对人工智能叙事进行批判性反思,特别关注医疗人工智能,并提高人们对从事医疗人工智能工作的人如何谈论人工智能以及如何履行其 "叙事责任 "的认识:对来自不同学科的 41 名参与者进行了定性半结构式访谈,他们在各自的职业中都接触过医疗人工智能。本研究采用专题叙事方法对数据进行了二次分析。分析得出 2 个主题,每个主题又有 2 个次主题:关于人工智能与医生互动的故事要么描述了一种竞争关系,要么描述了一种合作关系。一些参与者认为,人工智能可能会取代医生,因为它比医生表现得更好。但也有人认为,医生不应被取代,人工智能应该为医生提供帮助和支持。与会者讨论了过度技术推迟和自动化偏见的观点,强调了 "失去 "决策权的风险。还有人认为,人工智能可以减轻医生的职业倦怠,让他们有更多的时间与病人在一起。最后,少数与会者对医疗人工智能持极为乐观的态度,而大多数与会者则对这种说法提出了批评。后者对医疗人工智能 "神奇理论 "的存在表示遗憾,认为这是技术解决主义者的立场:大多数与会者对技术持细致入微的看法,既认识到技术的益处,也认识到技术的挑战,避免两极分化的叙述。不过,也有一些与会者助长了对医疗人工智能的炒作,将其与人类能力相提并论,并将其描绘得高人一等。总体而言,大多数人同意医疗人工智能应协助而非取代临床医生。研究得出结论,要充分发挥医疗人工智能的潜力,同时避免不切实际的期望和炒作,就必须进行平衡的叙述(侧重于技术的现有能力和局限性)。
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The "Magical Theory" of AI in Medicine: Thematic Narrative Analysis.

Background: The discourse surrounding medical artificial intelligence (AI) often focuses on narratives that either hype the technology's potential or predict dystopian futures. AI narratives have a significant influence on the direction of research, funding, and public opinion and thus shape the future of medicine.

Objective: The paper aims to offer critical reflections on AI narratives, with a specific focus on medical AI, and to raise awareness as to how people working with medical AI talk about AI and discharge their "narrative responsibility."

Methods: Qualitative semistructured interviews were conducted with 41 participants from different disciplines who were exposed to medical AI in their profession. The research represents a secondary analysis of data using a thematic narrative approach. The analysis resulted in 2 main themes, each with 2 other subthemes.

Results: Stories about the AI-physician interaction depicted either a competitive or collaborative relationship. Some participants argued that AI might replace physicians, as it performs better than physicians. However, others believed that physicians should not be replaced and that AI should rather assist and support physicians. The idea of excessive technological deferral and automation bias was discussed, highlighting the risk of "losing" decisional power. The possibility that AI could relieve physicians from burnout and allow them to spend more time with patients was also considered. Finally, a few participants reported an extremely optimistic account of medical AI, while the majority criticized this type of story. The latter lamented the existence of a "magical theory" of medical AI, identified with techno-solutionist positions.

Conclusions: Most of the participants reported a nuanced view of technology, recognizing both its benefits and challenges and avoiding polarized narratives. However, some participants did contribute to the hype surrounding medical AI, comparing it to human capabilities and depicting it as superior. Overall, the majority agreed that medical AI should assist rather than replace clinicians. The study concludes that a balanced narrative (that focuses on the technology's present capabilities and limitations) is necessary to fully realize the potential of medical AI while avoiding unrealistic expectations and hype.

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