From Publishing to Practice: Bringing AI Model Monitoring to a Healthcare Setting
In this tutorial, we focus on translation of general AI governance techniques to “boots on the ground” healthcare settings. That translation comes with terminology and vocabulary challenges, data quality and paucity issues, and legal and ethical barriers. Indeed, an ad hoc feedback loop is beginning to form between practitioners in healthcare and “traditional” AI/ML researchers, wherein the preferences and needs of practitioners are fed back into AI/ML research communities, who then adjust and build new tools that translate back into practice. This tutorial adds to that nascent movement, focusing on translational issues that arise between these two communities.