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@PHDTHESIS{Meyer:1005412,
      author       = {Meyer, Lea Mareen},
      othercontributors = {Salge, Torsten-Oliver and Paluch, Stefanie},
      title        = {{E}ssays on human-{AI} collaboration : insights from
                      healthcare},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      reportid     = {RWTH-2025-01746},
      pages        = {xvi, 182 Seiten : Illustrationen},
      year         = {2025},
      note         = {Dissertation, Rheinisch-Westfälische Technische Hochschule
                      Aachen, 2025},
      abstract     = {Collaboration between individuals and artificial
                      intelligence (AI) in healthcare has become a central topic
                      in both information system (IS) research and broader
                      societal discussions on leveraging human skills with AI
                      capabilities. As AI applications advance and get more
                      involved in healthcare processes, exploring how individuals
                      (i.e., medical staff such as physicians and nurses) and AI
                      can collaborate most effectively is essential. This
                      collaboration integrates human expertise and contextual
                      understanding with AI’s precision and data processing
                      capabilities. Combining these expertise offers the
                      possibility to improve patient outcomes, relieve medical
                      staff, and increase their decision-making. Despite the
                      growing interest in human-AI collaboration, existing
                      research mainly focuses on theoretical advancements and
                      AI’s potential and neglects practical field tests,
                      deployment, and interaction between individuals and AI.
                      Consequently, AI’s potential is not sufficiently realized,
                      and developed AI applications mismatch with practical needs,
                      resulting in no or fragmented deployment in practice. To
                      overcome this research gap, this thesis adopts an engaged
                      scholarship approach. It is a promising research methodology
                      that focuses on a participative form incorporating
                      practitioners in the research process. Engaged scholarship
                      is instrumental in generating a sustained and in-depth
                      understanding of human-AI collaboration. The thesis
                      comprises three research essays on human-AI collaboration,
                      each offering a different perspective on the collaboration
                      process. To ensure an ongoing knowledge transfer from
                      research to practice and vice versa, all three research
                      essays are informed by one AI research project deeply
                      embedded in clinical practices to develop and implement an
                      AI application in a hospital. In summary, this thesis
                      contributes to existing research on human-AI collaboration
                      by analyzing the collaboration process from multiple
                      perspectives. This research sheds light on the dynamics and
                      the interplay between individuals and AI, offering guidance
                      to ensure AI’s practical relevance and deployment for
                      healthcare practices. In doing so, this thesis provides a
                      nuanced understanding of human-AI collaboration at the
                      intersection between research and practice.},
      cin          = {816410},
      ddc          = {330},
      cid          = {$I:(DE-82)816410_20140620$},
      typ          = {PUB:(DE-HGF)11},
      url          = {https://publications.rwth-aachen.de/record/1005412},
}