Borycki Elizabeth M, Peute Linda W P, van Sinderen Femke, Kaufman David, Kushniruk Andre W
School of Health Information Science, University of Victoria, Victoria, British Columbia, Canada.
Department of Medical Informatics, Amsterdam UMC Location, University of Amsterdam Amsterdam, The Netherlands.
Yearb Med Inform. 2024 Aug;33(1):18-24. doi: 10.1055/s-0044-1800714. Epub 2025 Apr 8.
Artificial intelligence (AI) promises to revolutionize healthcare. Currently there is a proliferation of new AI applications that are being developed and beginning to be deployed across many areas in healthcare to streamline and make healthcare processes more efficient. In addition, AI has the potential to support personalized and customized precision healthcare by providing intelligent interaction with end users. However, to achieve the goal of precision AI issues and concerns related to the safety of AI, as with any new technology, must be addressed. In this article we first describe the link between AI and safety and then describe the relation of AI to the emerging study of technology-induced error. An overview of published safety issues that have been associated with introduction of AI are described and categorized. These include potential for error to arise from varied sources, including the data used to drive AI applications, and the design process of AI applications itself. In addition, lack of appropriate and rigorous testing and limited analysis of AI applications during procurement processes has also been reported. Recommendations for ensuring the safe adoption of AI technology in healthcare are discussed, focusing on the need for more rigorous testing and evaluation of AI applications, ranging from laboratory testing through to naturalistic evaluation. The application of such approaches will support safety and precision AI for a modern digital health system.
人工智能有望给医疗保健带来变革。目前,大量新的人工智能应用正在开发中,并开始在医疗保健的许多领域部署,以简化流程并提高医疗保健效率。此外,人工智能有潜力通过与终端用户进行智能交互来支持个性化和定制化的精准医疗。然而,要实现精准人工智能的目标,与人工智能安全性相关的问题和担忧,如同任何新技术一样,必须得到解决。在本文中,我们首先描述人工智能与安全性之间的联系,然后阐述人工智能与新兴的技术诱发错误研究之间的关系。对已发表的与人工智能引入相关的安全问题进行了概述和分类。这些问题包括可能从各种来源产生错误,包括用于驱动人工智能应用的数据,以及人工智能应用本身的设计过程。此外,也有报告称在采购过程中缺乏对人工智能应用的适当严格测试和有限分析。讨论了确保在医疗保健中安全采用人工智能技术的建议,重点是需要对人工智能应用进行更严格的测试和评估,从实验室测试到自然主义评估。应用这些方法将支持现代数字健康系统的安全和精准人工智能。