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poster voor de EuSoMII Annual Meeting in Pisa, Italië in oktober 2023.
PURPOSE & LEARNING OBJECTIVE
Artificial Intelligence (AI) technologies are gaining popularity for their ability to autonomously perform tasks and mimic human reasoning [1, 2]. Especially within the medical industry, the implementation of AI solutions
has seen an increasing pace [3]. However, the field of radiology is not yet transformed with the promised value of AI, as knowledge on the effective use and implementation of AI is falling behind due to a number
of causes:
1) Reactive/passive modes of learning are dominant
2) Existing developments are fragmented
3) Lack of expertise and differing perspectives
4) Lack of effective learning space
Learning communities can help overcome these problems and address the complexities that come with human-technology configurations [4]. As the impact of a technology is dependent on its social management
and implementation processes [5], our research question then becomes:
How do we design, configure, and manage a Learning Community to maximize the impact of AI solutions in medicine?