How Artificial Intelligence Challenges Tailorable Technology Design : Insights from a Design Study on Individualized Bladder Monitoring

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00007997
URN to cite this document: urn:nbn:de:bvb:703-epub-7997-4

Title data

Fechner, Pascal ; König, Fabian ; Lockl, Jannik ; Röglinger, Maximilian:
How Artificial Intelligence Challenges Tailorable Technology Design : Insights from a Design Study on Individualized Bladder Monitoring.
In: Business & Information Systems Engineering. Vol. 66 (2024) Issue 3 . - pp. 357-376.
ISSN 1867-0202
DOI der Verlagsversion: https://doi.org/10.1007/s12599-024-00872-9

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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 on 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 bladder monitoring domain 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.

Further data

Item Type:	Article in a journal
Keywords:	Theory of Tailorable Technology Design; Individualization; Smart wearables; Neurogenic lower urinary tract dysfunction; Bladder monitoring; Deep transfer learning
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Business Administration Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management - Univ.-Prof. Dr. Maximilian Röglinger Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT Research Institutions > Affiliated Institutes > FIM Research Center for Information Management Faculties Faculties > Faculty of Law, Business and Economics
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-7997-4
Date Deposited:	14 Oct 2024 08:42
Last Modified:	14 Oct 2024 08:42
URI:	https://epub.uni-bayreuth.de/id/eprint/7997

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