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为什么我们不应将医学人工智能的准确性误认为是效率。

Why we should not mistake accuracy of medical AI for efficiency.

作者信息

Jongsma Karin Rolanda, Sand Martin, Milota Megan

机构信息

Bioethics & Health Humanities, Julius Center, University Medical Center Utrecht, Utrecht University, PO Box 85500, 3508 CA, Utrecht, The Netherlands.

TU Delft, Department of Values, Technology and Innovation, Faculty of Technology, Policy and Management, Jaffalaan 5, 2628 BX, Delft, The Netherlands.

出版信息

NPJ Digit Med. 2024 Mar 4;7(1):57. doi: 10.1038/s41746-024-01047-2.

Abstract

In the medical literature, promising results regarding accuracy of medical AI are presented as claims for its potential to increase efficiency. This elision of concepts is misleading and incorrect. First, the promise that AI will reduce human workload rests on a too narrow assessment of what constitutes workload in the first place. Human operators need new skills and deal with new responsibilities, these systems need an elaborate infrastructure and support system that all contribute to an increased amount of human work and short-term efficiency wins may become sources of long-term inefficiency. Second, for the realization of increased efficiency, the human-side of technology implementation is determinate. Human knowledge, competencies and trust can foster or undermine efficiency. We conclude that is important to remain conscious and critical about how we talk about expected benefits of AI, especially when referring to systemic changes based on single studies.

摘要

在医学文献中,关于医学人工智能准确性的 promising 结果被表述为其提高效率的潜力主张。这种概念的省略具有误导性且不正确。首先,人工智能将减轻人类工作量的 promise 首先基于对工作量构成的过于狭隘的评估。人类操作员需要新技能并应对新责任,这些系统需要精心构建的基础设施和支持系统,所有这些都会导致人类工作量增加,短期的效率提升可能会成为长期低效率的根源。其次,为了实现效率提升,技术实施的人力方面是决定性的。人类的知识、能力和信任会促进或破坏效率。我们得出结论,重要的是要对我们如何谈论人工智能的预期好处保持清醒和批判性,尤其是在提及基于单一研究的系统性变化时。

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