Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy.
Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy.
Front Public Health. 2020 Apr 28;8:117. doi: 10.3389/fpubh.2020.00117. eCollection 2020.
In the near future, Artificial Intelligence (AI) is expected to participate more and more in decision making processes, in contexts ranging from healthcare to politics. For example, in the healthcare context, doctors will increasingly use AI and machine learning devices to improve precision in diagnosis and to identify therapy regimens. One hot topic regards the necessity for health professionals to adapt shared decision making with patients to include the contribution of AI into clinical practice, such as acting as mediators between the patient with his or her healthcare needs and the recommendations coming from artificial entities. In this scenario, a "third wheel" effect may intervene, potentially affecting the effectiveness of shared decision making in three different ways: first, clinical decisions could be delayed or paralyzed when AI recommendations are difficult to understand or to explain to patients; second, patients' symptomatology and medical diagnosis could be misinterpreted when adapting them to AI classifications; third, there may be confusion about the roles and responsibilities of the protagonists in the healthcare process (e.g., Who has authority?). This contribution delineates such effects and tries to identify the impact of AI technology on the healthcare process, with a focus on future medical practice.
在不久的将来，人工智能（AI）预计将越来越多地参与决策过程，其应用场景涵盖医疗保健到政治等诸多领域。例如，在医疗保健领域，医生将越来越多地使用人工智能和机器学习设备来提高诊断的精准度，并确定治疗方案。其中一个热门话题是，医疗保健专业人员是否有必要将与患者共同做出决策的方法进行调整，将人工智能的贡献纳入临床实践，例如充当患者及其医疗需求与来自人工智能实体的建议之间的调解人。在这种情况下，可能会出现“第三方”效应，从而以三种不同的方式潜在地影响共同决策的效果：首先，当人工智能的建议难以理解或难以向患者解释时，临床决策可能会被延迟或陷入僵局；其次，在将患者的症状和医学诊断适应于人工智能分类时，可能会产生误解；第三，在医疗保健过程中（例如，谁拥有权威？），可能会对主角的角色和责任感到困惑。本文阐述了这些影响，并试图确定人工智能技术对医疗保健过程的影响，重点关注未来的医疗实践。
