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Developing Team Design Patterns for Hybrid Intelligence Systems

Emma van Zoelen; Tina Mioch; Mani Tajaddini; Christian Fleiner; Stefani Tsaneva; Pietro Camin; Thiago Gouvea; Kim Baraka; Maaike H.T. de Boer; Mark A. Neerincx
In: Frontiers in Artificial Intelligence and Applications. International Conference on Hybrid Human-Artificial Intelligence (HHAI-2023), June 26-30, Munich, Germany, IOS Press, 2023.


With artificial intelligence (AI) systems entering our working and leisure environments with increasing adaptation and learning capabilities, new opportunities arise for developing hybrid (human-AI) intelligence (HI) systems, comprising new ways of collaboration. However, there is not yet a structured way of specifying design solutions of collaboration for hybrid intelligence (HI) systems and there is a lack of best practices shared across application domains. We address this gap by investigating the generalization of specific design solutions into design patterns that can be shared and applied in different contexts. We present a human-centered bottom-up approach for the specification of design solutions and their abstraction into team design patterns. We apply the proposed approach for 4 concrete HI use cases and show the successful extraction of team design patterns that are generalizable, providing re-usable design components across various domains. This work advances previous research on team design patterns and designing applications of HI systems.