Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2023 12:00 AM
End Date
7-1-2023 12:00 AM
Description
This study emanates from work on human-centered AI and the claim of “keeping the organiza-tion in the loop”. A previous study suggests a sys-tematic 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 con-textual changes. Since we assume that these findings can be generalized for other kinds of applications of Machine Learning (ML), we contrast the manage-ment 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 holis-tic consideration of workflows or supervision and quality assurance.
Recommended Citation
Herrmann, Thomas and Pfeiffer, Sabine, "Keeping the Organization in the Loop as a General Concept for Human-Centered AI: The Example of Medical Imaging" (2023). Hawaii International Conference on System Sciences 2023 (HICSS-56). 5.
https://aisel.aisnet.org/hicss-56/os/ai_and_organizing/5
Keeping the Organization in the Loop as a General Concept for Human-Centered AI: The Example of Medical Imaging
Online
This study emanates from work on human-centered AI and the claim of “keeping the organiza-tion in the loop”. A previous study suggests a sys-tematic 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 con-textual changes. Since we assume that these findings can be generalized for other kinds of applications of Machine Learning (ML), we contrast the manage-ment 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 holis-tic consideration of workflows or supervision and quality assurance.
https://aisel.aisnet.org/hicss-56/os/ai_and_organizing/5