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How Artificial Intelligence Challenges Tailorable Technology Design

Author

Listed:
  • Pascal Fechner

    (University of Bayreuth
    University of Bayreuth)

  • Fabian König

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

  • Jannik Lockl

    (University of Bayreuth
    University College London)

  • Maximilian Röglinger

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

Abstract

Artificial intelligence (AI) has significantly advanced healthcare and created unprecedented opportunities to enhance patient-centeredness and empowerment. This progress promotes individualized medicine, where treatment and care are tailored to each patient’s unique needs and characteristics. The Theory of Tailorable Technology Design has considerable potential to contribute to individualized medicine as it focuses on information systems (IS) that users can modify and redesign in the context of use. While the theory accounts for both the designer and user perspectives in the lifecycle of an IS, it does not reflect the inductive learning and autonomy of AI throughout the tailoring process. Therefore, this study posits the conjecture that current knowledge about tailorable technology design does not effectively account for IS that incorporate AI. To investigate this conjecture and challenge the Theory of Tailorable Technology Design, a revelatory design study of an AI-enabled individual IS in the domain of bladder monitoring is conducted. Based on the empirical evidence from the design study, the primary contribution of this work lies in three propositions for the design of tailorable technology, culminating in a Revised Theory of Tailorable Technology Design. As the outcome of the design study, the secondary contribution of this work is concrete design knowledge for AI-enabled individualized bladder monitoring systems that empower patients with neurogenic lower urinary tract dysfunction (NLUTD). Overall, this study highlights the value of AI for patient-centeredness in IS design.

Suggested Citation

  • Pascal Fechner & Fabian König & Jannik Lockl & Maximilian Röglinger, 2024. "How Artificial Intelligence Challenges Tailorable Technology Design," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(3), pages 357-376, June.
    • Handle: RePEc:spr:binfse:v:66:y:2024:i:3:d:10.1007_s12599-024-00872-9
    DOI: 10.1007/s12599-024-00872-9
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    References listed on IDEAS

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