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Disentangling Human-AI Hybrids

Author

Listed:
  • Lukas Fabri

    (University of Applied Sciences Augsburg
    Branch Business and Information Systems Engineering of the Fraunhofer FIT)

  • Björn Häckel

    (University of Applied Sciences Augsburg
    Branch Business and Information Systems Engineering of the Fraunhofer FIT)

  • Anna Maria Oberländer

    (University of Bayreuth
    Branch Business and Information Systems Engineering of the Fraunhofer FIT)

  • Marius Rieg

    (University of Applied Sciences Augsburg
    Branch Business and Information Systems Engineering of the Fraunhofer FIT)

  • Alexander Stohr

    (Branch Business and Information Systems Engineering of the Fraunhofer FIT
    Kempten University of Applied Sciences)

Abstract

Artificial intelligence (AI) offers great potential in organizations. The path to achieving this potential will involve human-AI interworking, as has been confirmed by numerous studies. However, it remains to be explored which direction this interworking of human agents and AI-enabled systems ought to take. To date, research still lacks a holistic understanding of the entangled interworking that characterizes human-AI hybrids, so-called because they form when human agents and AI-enabled systems closely collaborate. To enhance such understanding, this paper presents a taxonomy of human-AI hybrids, developed by reviewing the current literature as well as a sample of 101 human-AI hybrids. Leveraging weak sociomateriality as justificatory knowledge, this study provides a deeper understanding of the entanglement between human agents and AI-enabled systems. Furthermore, a cluster analysis is performed to derive archetypes of human-AI hybrids, identifying ideal–typical occurrences of human-AI hybrids in practice. While the taxonomy creates a solid foundation for the understanding and analysis of human-AI hybrids, the archetypes illustrate the range of roles that AI-enabled systems can play in those interworking scenarios.

Suggested Citation

  • Lukas Fabri & Björn Häckel & Anna Maria Oberländer & Marius Rieg & Alexander Stohr, 2023. "Disentangling Human-AI Hybrids," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(6), pages 623-641, December.
    • Handle: RePEc:spr:binfse:v:65:y:2023:i:6:d:10.1007_s12599-023-00810-1
    DOI: 10.1007/s12599-023-00810-1
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