背景:围绕医疗人工智能(AI)的论述通常集中在炒作技术潜力或预测反乌托邦未来的叙述上。人工智能叙事对研究方向有重大影响,资金,和公众舆论,从而塑造医学的未来。
目标: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,并提高人们对使用医疗人工智能的人如何谈论人工智能并履行他们的“叙事责任”的认识。“
方法:对来自不同学科的41名参与者进行了定性半结构化访谈,这些参与者在其职业中接触过医学AI。该研究代表了使用主题叙事方法对数据的二次分析。分析得出了两个主要主题,每个都有2个其他子主题。
结果:关于AI-医师互动的故事描述了竞争或合作的关系。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。然而,其他人认为,医生不应该被取代,人工智能应该帮助和支持医生。讨论了过度技术推迟和自动化偏差的想法,强调“失去”决策权的风险。人工智能可以减轻医生的倦怠,并允许他们花更多的时间与病人在一起。最后,一些参与者报告了对医学人工智能的极其乐观的描述,大多数人批评这种类型的故事。后者感叹医学AI的“神奇理论”的存在,确定了技术解决方案的立场。
结论:大多数参与者报告了对技术的细微看法,认识到它的好处和挑战,避免两极分化的叙述。然而,一些参与者确实助长了围绕医疗人工智能的炒作,将其与人类能力进行比较,并将其描述为卓越。总的来说,大多数人同意医疗人工智能应该帮助而不是取代临床医生。该研究得出的结论是,平衡的叙述(侧重于技术的现有能力和局限性)对于充分实现医疗AI的潜力是必要的,同时避免不切实际的期望和炒作。
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.