Institute for Occupational Safety and Health of the German Social Accident Health Insurance (IFA), 53757 Sankt Augustin, Germany.
Int J Environ Res Public Health. 2022 Mar 18;19(6):3641. doi: 10.3390/ijerph19063641.
Artificial intelligence can be used to realise new types of protective devices and assistance systems, so their importance for occupational safety and health is continuously increasing. However, established risk mitigation measures in software development are only partially suitable for applications in AI systems, which only create new sources of risk. Risk management for systems that for systems using AI must therefore be adapted to the new problems. This work objects to contribute hereto by identifying relevant sources of risk for AI systems. For this purpose, the differences between AI systems, especially those based on modern machine learning methods, and classical software were analysed, and the current research fields of trustworthy AI were evaluated. On this basis, a taxonomy could be created that provides an overview of various AI-specific sources of risk. These new sources of risk should be taken into account in the overall risk assessment of a system based on AI technologies, examined for their criticality and managed accordingly at an early stage to prevent a later system failure.
人工智能可用于实现新型防护设备和辅助系统，因此其对职业安全与健康的重要性正不断增加。然而，软件开发中既定的风险缓解措施仅部分适用于人工智能系统应用，这只会产生新的风险源。因此，必须针对使用人工智能的系统来调整针对系统的风险管理。为此，本研究旨在通过确定人工智能系统的相关风险源来为此做出贡献。为此，分析了人工智能系统（特别是基于现代机器学习方法的系统）与经典软件之间的差异，并评估了可信人工智能的当前研究领域。在此基础上，创建了一个分类法，提供了各种人工智能特定风险源的概述。在基于人工智能技术的系统的整体风险评估中应考虑这些新的风险源，评估其关键性，并在早期进行相应管理，以防止系统后期失效。
