PAIS, University of Warwick, Coventry, UK
Computer Science, University of Warwick, Coventry, UK.
J Med Ethics. 2022 Apr;48(4):278-284. doi: 10.1136/medethics-2020-107024. Epub 2021 Mar 3.
This paper explores ethical issues raised by whole slide image-based computational pathology. After briefly giving examples drawn from some recent literature of advances in this field, we consider some ethical problems it might be thought to pose. These arise from (1) the tension between artificial intelligence (AI) research-with its hunger for more and more data-and the default preference in data ethics and data protection law for the minimisation of personal data collection and processing; (2) the fact that computational pathology lends itself to kinds of data fusion that go against data ethics norms and some norms of biobanking; (3) the fact that AI methods are esoteric and produce results that are sometimes unexplainable (the so-called 'black box'problem) and (4) the fact that computational pathology is particularly dependent on scanning technology manufacturers with interests of their own in profit-making from data collection. We shall suggest that most of these issues are resolvable.
本文探讨了基于全玻片图像的计算病理学所引发的伦理问题。在简要举例说明该领域的一些最新进展后,我们考虑了它可能引发的一些伦理问题。这些问题源于:(1) 人工智能 (AI) 研究的需求与数据伦理和数据保护法对个人数据收集和处理最小化的默认偏好之间的紧张关系;(2) 计算病理学易于进行违反数据伦理规范和一些生物库规范的数据融合;(3) AI 方法的深奥性以及产生的结果有时无法解释(即所谓的“黑箱”问题);(4) 计算病理学特别依赖于扫描技术制造商,他们自身在从数据收集中获利方面存在利益。我们将表明,这些问题大多是可以解决的。