Limits of trust in medical AI
Limits of trust in medical AI
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DOI：
10.1136/medethics-2019-105935
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发表时间：
2020-07-01
影响因子：
4.1
通讯作者：
Hatherley, Joshua James
中科院分区：
文献类型：
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作者：
Hatherley, Joshua James
人工智能（AI）有望彻底改变医学实践。深度学习领域的最新进展已经在各种临床任务中取得了成功：从图像中检测糖尿病视网膜病变，预测再入院，帮助发现新药等。在本文中，我将认为这些担忧是有道理的，因为人工智能系统可以依赖，并且能够可靠，但不能被信任，并且不具有可信度。由于患者需要依赖人工智能系统进行医疗决策，因此这有可能在临床实践中产生信任赤字。
Artificial intelligence (AI) is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI's progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since AI systems can be relied on, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely on AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice.