In response to the need to address the safety challenges in the use of artificial intelligence (AI), this research aimed to develop a framework for a safety controlling system (SCS) to address the AI black-box mystery in the healthcare industry. The main objective was to propose safety guidelines for implementing AI black-box models to reduce the risk of potential healthcare-related incidents and accidents. The system was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. On the basis of the MAVT approach, three layers of attributes were created. The first level contained six key dimensions, the second level included 14 attributes, and the third level comprised 78 attributes. The key first level dimensions of the SCS included safety policies, incentives for clinicians, clinician and patient training, communication and interaction, planning of actions, and control of such actions. The proposed system may provide a basis for detecting AI utilization risks, preventing incidents from occurring, and developing emergency plans for AI-related risks. This approach could also guide and control the implementation of AI systems in the healthcare industry.

中文翻译：

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控制医疗保健中基于人工智能的系统的安全性

为了应对使用人工智能（AI）的安全挑战的需要，本研究旨在开发一种安全控制系统（SCS）的框架，以解决医疗保健行业中的AI黑匣子之谜。主要目标是为实施AI黑匣子模型提出安全准则，以减少潜在的与医疗相关的事件和事故的风险。该系统是通过采用多属性值模型方法（MAVT）开发的，该方法包括四个对称部分：提取属性，为属性生成权重，制定评级量表并最终确定系统。在MAVT方法的基础上，创建了三层属性。第一层包含六个关键维度，第二层包含14个属性，第三层包含78个属性。SCS的关键一级维度包括安全政策，对临床医生，临床医生和患者进行培训的激励措施，沟通与互动，行动计划以及此类行动的控制。所提出的系统可以为检测AI使用风险，防止事件发生以及针对AI相关风险制定应急计划提供基础。这种方法还可以指导和控制医疗保健行业中AI系统的实施。