Abstract
AI-based services are becoming more and more common in manufacturing; however, the development, implementation, and operation of these services are associated with challenges. The design of Human-Centered AI (HCAI) is one approach to address these challenges. Design guidelines and principles are provided to assist AI developers in the design of HCAI. However, these principles are currently defined for AI in general and not for specific application contexts. The aim of this work is to analyze whether existing design principles for HCAI are transferable to IAI-based services in manufacturing and how they can be integrated into the development process. In an explorative-qualitative research design, the design pattern of the People + AI Guidebook by the PAIR from Google were analyzed regarding their applicability in manufacturing environments. The finding show that a transfer of the design principles is generally possible. According to the experts, 15 of the design patterns have a direct influence on the perception of Industrial AI-based services by end-users or management and can thus increase the acceptance of them. Finally, the design patterns were assessed in terms of their application relevance and complexity in manufacturing.
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Appendix
Appendix
The experts assessed the patterns according to their application relevance and application complexity in the manufacturing environment (Figs. 3 and 4).
Workshop 1: Assessment of the relevance and complexity of the application of end-user-centered design patterns of the People + AI Guidebook [10].
Workshop 2: Assessment of the relevance and complexity of the application of end-user-centered design patterns of the People + AI Guidebook [10].
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Kutz, J., Neuhüttler, J., Bienzeisler, B., Spilski, J., Lachmann, T. (2023). Human-Centered AI for Manufacturing – Design Principles for Industrial AI-Based Services. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2023. Lecture Notes in Computer Science(), vol 14050. Springer, Cham. https://doi.org/10.1007/978-3-031-35891-3_8
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