What is critical for human-centered AI at work? - Toward an interdisciplinary theory.

Journal: Frontiers in artificial intelligence
Published Date:

Abstract

Human-centered artificial intelligence (HCAI) has gained momentum in the scientific discourse but still lacks clarity. In particular, disciplinary differences regarding the scope of HCAI have become apparent and were criticized, calling for a systematic mapping of conceptualizations-especially with regard to the work context. This article compares how human factors and ergonomics (HFE), psychology, human-computer interaction (HCI), information science, and adult education view HCAI and discusses their normative, theoretical, and methodological approaches toward HCAI, as well as the implications for research and practice. It will be argued that an interdisciplinary approach is critical for developing, transferring, and implementing HCAI at work. Additionally, it will be shown that the presented disciplines are well-suited for conceptualizing HCAI and bringing it into practice since they are united in one aspect: they all place the human being in the center of their theory and research. Many critical aspects for successful HCAI, as well as minimum fields of action, were further identified, such as human capability and controllability (HFE perspective), autonomy and trust (psychology and HCI perspective), learning and teaching designs across target groups (adult education perspective), as much as information behavior and information literacy (information science perspective). As such, the article lays the ground for a theory of human-centered interdisciplinary AI, i.e., the Synergistic Human-AI Symbiosis Theory (SHAST), whose conceptual framework and founding pillars will be introduced.

Authors

  • Athanasios Mazarakis
    ZBW - Leibniz Information Centre for Economics, Web Science, Kiel, Germany.
  • Christian Bernhard-Skala
    Department of Organisation and Program Planning, German Institute for Adult Education - Leibniz Centre for Lifelong Learning, Bonn, Germany.
  • Martin Braun
    Fraunhofer Institute for Industrial Engineering, User Experience, Stuttgart, Germany.
  • Isabella Peters
    ZBW - Leibniz Information Centre for Economics, Web Science, Kiel, Germany.

Keywords

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