Keeping the Organization in the Loop as a General Concept for Human-Centered AI: The Example of Medical Imaging - Herrmann, Thomas; Pfeiffer, Sabine (Proceedings of the Annual Hawaii International Conference on System Sciences, 2023)
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.
CRIS-Team Scopus Importer:2023-04-21