Developing Team Design Patterns for Hybrid Intelligence Systems

Emma Van Zoelen, Tina Mioch*, Mani Tajaddini, Christian Fleiner, Stefani Tsaneva, Pietro Camin, Thiago S. Gouvêa, Kim Baraka, Maaike H.T. De Boer, Mark A. Neerincx

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
24 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationHHAI 2023
Subtitle of host publicationAugmenting Human Intellect - Proceedings of the 2nd International Conference on Hybrid Human-Artificial Intelligence
EditorsPaul Lukowicz, Sven Mayer, Janin Koch, John Shawe-Taylor, Ilaria Tiddi
PublisherIOS Press
Number of pages14
ISBN (Electronic)9781643683942
Publication statusPublished - 2023
Event2nd International Conference on Hybrid Human-Artificial Intelligence, HHAI 2023 - Munich, Germany
Duration: 26 Jun 202330 Jun 2023

Publication series

NameFrontiers in Artificial Intelligence and Applications
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


Conference2nd International Conference on Hybrid Human-Artificial Intelligence, HHAI 2023


  • Co-evolution
  • Human-centered AI
  • Hybrid Intelligence
  • Interdependence
  • Team Design Patterns
  • Use-case based research


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