van Voorst Roanne
Department of Anthropology, University of Amsterdam, Amsterdam, Netherlands.
AI Soc. 2025;40(5):3237-3248. doi: 10.1007/s00146-024-02177-7. Epub 2025 Jan 9.
This paper analyzes the collaboration between healthcare professionals and algorithms in making decisions within the realm of public healthcare. By extending the concept of 'tinkering' from previous research conducted by philosopher Mol (Care in practice. On tinkering in clinics, homes and farms Verlag, Amsterdam, 2010) and anthropologist Pols (Health Care Anal 18: 374-388, 2009), who highlighted the improvisational and adaptive practices of healthcare professionals, this paper reveals that in the context of digitalizing healthcare, both professionals and algorithms engage in what I call 'collaborative tinkering' as they navigate the intricate and unpredictable nature of healthcare situations together. The paper draws upon an idea that is increasingly common in academic literature, namely that healthcare professionals and the algorithms they use can form a hybrid decision-making entity, challenging the conventional notion of agency and intelligence as being exclusively confined to individual humans or machines. Drawing upon an international, ethnographic study conducted in different hospitals around the world, the paper describes empirically how humans and algorithms come to decisions together, making explicit how, in the practice of daily work, agency and intelligence are distributed among a range of actors, including humans, technologies, knowledge resources, and the spaces where they interact. The concept of collaborative tinkering helps to make explicit how both healthcare professionals and algorithms engage in adaptive improvisation. This exploration not only enriches the understanding of collaborative dynamics between humans and AI but also problematizes the individualistic conception of AI that still exists in regulatory frameworks. By introducing empirical specificity through ethnographic insights and employing an anthropological perspective, the paper calls for a critical reassessment of current ethical and policy frameworks governing human-AI collaboration in healthcare, thereby illuminating direct implications for the future of AI ethics in medical practice.
本文分析了医疗保健专业人员与算法在公共医疗保健领域决策过程中的协作。哲学家莫尔（《实践中的关怀：诊所、家庭和农场的修补》，阿姆斯特丹出版社，2010年）和人类学家波尔斯（《医疗保健分析》18：374 - 388，2009年）此前的研究强调了医疗保健专业人员的即兴和适应性实践，本文通过扩展他们提出的“修补”概念，揭示了在医疗保健数字化背景下，专业人员和算法在共同应对医疗保健情况的复杂和不可预测性时，都参与了我所称的“协作修补”。本文借鉴了学术文献中越来越常见的一种观点，即医疗保健专业人员及其使用的算法可以形成一个混合决策实体，挑战了将能动性和智能完全局限于个体人类或机器的传统观念。基于一项在世界各地不同医院进行的国际人种志研究，本文实证描述了人类和算法如何共同做出决策，明确了在日常工作实践中，能动性和智能是如何在包括人类、技术、知识资源以及它们相互作用的空间等一系列行为主体之间分布的。协作修补的概念有助于明确医疗保健专业人员和算法是如何进行适应性即兴创作的。这种探索不仅丰富了对人类与人工智能之间协作动态的理解，也对监管框架中仍然存在的人工智能个人主义概念提出了质疑。通过人种志见解引入实证细节并采用人类学视角，本文呼吁对当前医疗保健领域人类与人工智能协作的伦理和政策框架进行批判性重新评估，从而阐明对医疗实践中人工智能伦理未来的直接影响。
