While the increased use of AI in the manufacturing sector has been widely noted, there is little understanding on the risks that it may raise in a manufacturing organisation. Although various high level frameworks and definitions have been proposed to consolidate potential risks, practitioners struggle with understanding and implementing them. This lack of understanding exposes manufacturing to a multitude of risks, including the organisation, its workers, as well as suppliers and clients. In this paper, we explore and interpret the applicability of responsible, ethical, and trustworthy AI within the context of manufacturing. We then use a broadened adaptation of a machine learning lifecycle to discuss, through the use of illustrative examples, how each step may result in a given AI trustworthiness concern. We additionally propose a number of research questions to the manufacturing research community, in order to help guide future research so that the economic and societal benefits envisaged by AI in manufacturing are delivered safely and responsibly.

翻译：尽管制造业中人工智能的广泛应用已受到广泛关注，但关于其可能在制造组织中引发的风险，人们仍缺乏深入理解。尽管已有各种高级框架和定义被提出以整合潜在风险，但从业者在理解和落实这些框架时仍面临困难。这种认知缺失使制造业面临多重风险，涵盖组织本身、员工、供应商及客户。本文在制造业背景下探索并解读了负责任、伦理与可信人工智能的适用性，随后通过扩展机器学习生命周期，结合实例讨论每个环节如何引发特定的人工智能可信性问题。此外，我们为制造业研究界提出了一系列研究问题，旨在引导未来研究，确保人工智能在制造业中预期的经济与社会效益能够安全、负责任地实现。