Trust in AI: why we should be designing for APPROPRIATE reliance
Trust in AI: why we should be designing for APPROPRIATE reliance
复制标题
信任人工智能：为什么我们应该设计适当的依赖
DOI：
10.1093/jamia/ocab238
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发表时间：
2021-11-02
影响因子：
6.4
通讯作者：
Ancker, Jessica S.
中科院分区：
文献类型：
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作者：
Benda, Natalie C.;Novak, Laurie L.;Ancker, Jessica S.
在医疗保健中使用人工智能，例如基于机器学习的预测算法，有望提高结果，但很少有系统用于常规临床实践。信任被认为是在临床实践中有意义地使用人工智能的一个重要挑战。人工智能系统通常涉及自动化具有认知挑战性的任务。因此，以前关于自动化信任的文献可能为人工智能在医疗保健中的应用提供了重要的经验教训。从这个角度来看，我们认为，信息学应该从自动化的信任文献中吸取教训，目标应该是根据工具的目的，提出建议的过程及其在给定环境中的表现，培养对人工智能的适当信任。我们适应的概念模型来支持这一论点，并提出建议，为今后的工作。
Use of artificial intelligence in healthcare, such as machine learning-based predictive algorithms, holds promise for advancing outcomes, but few systems are used in routine clinical practice. Trust has been cited as an important challenge to meaningful use of artificial intelligence in clinical practice. Artificial intelligence systems often involve automating cognitively challenging tasks. Therefore, previous literature on trust in automation may hold important lessons for artificial intelligence applications in healthcare. In this perspective, we argue that informatics should take lessons from literature on trust in automation such that the goal should be to foster appropriate trust in artificial intelligence based on the purpose of the tool, its process for making recommendations, and its performance in the given context. We adapt a conceptual model to support this argument and present recommendations for future work.