TAI-PRM: trustworthy AI—project risk management framework towards Industry 5.0

Eduardo Vyhmeister, Gabriel G. Castane
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Abstract

Artificial Intelligence (AI) is increasingly being used in manufacturing to automate tasks and process data, leading to what has been termed Industry. 4.0. However, as we move towards Industry 5.0, there is a need to incorporate societal and human-centric dimensions into the development and deployment of AI software artefacts. This requires blending ethical considerations with existing practices and standards. To address this need, the TAI-PRM framework has been developed. It builds upon established methods, such as Failure Mode and Effect Analysis (FMEA) and the Industrial ISO 31000, to manage risks associated with AI artefacts in the manufacturing sector. The framework identifies ethical considerations as hazards that can impact system processes and sustainability and provides tools and metrics to manage these risks. To validate the framework, it was applied in an EU project for Digital Twins on AI for manufacturing. The results showed that TAI-PRM can effectively identify and track different failure modes associated with AI artefacts and help users to manage ethical risks associated with their deployment. By incorporating ethical considerations into risk management processes, the framework enables the developing and deploying trustworthy AI in the manufacturing sector.

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TAI-PRM:面向工业 5.0 的可信人工智能项目风险管理框架
人工智能(AI)越来越多地用于制造业,以实现任务自动化和数据处理,从而产生了所谓的工业4.0。然而,随着我们向工业5.0迈进,有必要将社会和以人为中心的维度纳入人工智能软件工件的开发和部署中。这需要将道德考虑与现有的实践和标准结合起来。为了满足这一需求,已经开发了TAI-PRM框架。它建立在既定方法的基础上,如失效模式和影响分析(FMEA)和工业ISO 31000,以管理制造业中与人工智能制品相关的风险。该框架将道德因素识别为可能影响系统过程和可持续性的危害,并提供管理这些风险的工具和度量标准。为了验证该框架,它被应用于欧盟关于人工智能制造业的数字双胞胎项目。结果表明,TAI-PRM可以有效地识别和跟踪与人工智能制品相关的不同故障模式,并帮助用户管理与其部署相关的道德风险。通过将道德考虑纳入风险管理流程,该框架能够在制造业开发和部署值得信赖的人工智能。
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