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Communications of the ACM

ACM Opinion

AI Model Transferability in Healthcare: A Sociotechnical Perspective

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Doctor using a tablet to examine patient records.

To deliver value in healthcare AI and ML models must be integrated not only into technology platforms but also into local human and organizational ecosystems and workflows.

Credit: Getty Images

Predictive model transferability is gaining more attention as healthcare organizations attempt to implement artificial intelligence (AI)-based prediction tools. Although some machine learning (ML)-based models fail when subjected to retrospective validation across institutions and patient populations, technical improvements show promise for addressing this model efficacy problem. To address the engineering challenges, a technical subfield labelled MLOps has emerged.

However, the focus of MLOps on technical transferability may be obscuring a larger set of obstacles to sociotechnical transferability: organizational, social, and individual challenges of deploying models at scale across contexts, whether institutions, teams or individual roles.

From Nature Machine Intelligence
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