Keeping the Organization in the Loop as a General Concept for Human-Centered AI: The Example of Medical Imaging
Herrmann T, Pfeiffer S (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: IEEE Computer Society
Book Volume: 2023-January
Pages Range: 5272-5281
Conference Proceedings Title: Proceedings of the Annual Hawaii International Conference on System Sciences
Event location: Online
ISBN: 9780998133164
Abstract
This study emanates from work on human-centered AI and the claim of “keeping the organization in the loop”. A previous study suggests a systematic framework of organizational practices in the context of predictive maintenance, and identified four cycles: using AI, customizing AI, original task handling with support of AI, and dealing with contextual changes. Since we assume that these findings can be generalized for other kinds of applications of Machine Learning (ML), we contrast the management activities that support the four cycles and their interplay with a widely different domain: the usage of AI for radiology. Our literature analysis reveals a series of overlaps with the existing framework, but also results in the need for extensions, such as holistic consideration of workflows or supervision and quality assurance.
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Germany (DE)How to cite
APA:
Herrmann, T., & Pfeiffer, S. (2023). Keeping the Organization in the Loop as a General Concept for Human-Centered AI: The Example of Medical Imaging. In Tung X. Bui (Eds.), Proceedings of the Annual Hawaii International Conference on System Sciences (pp. 5272-5281). Online: IEEE Computer Society.
MLA:
Herrmann, Thomas, and Sabine Pfeiffer. "Keeping the Organization in the Loop as a General Concept for Human-Centered AI: The Example of Medical Imaging." Proceedings of the 56th Annual Hawaii International Conference on System Sciences, HICSS 2023, Online Ed. Tung X. Bui, IEEE Computer Society, 2023. 5272-5281.
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