Machine Learning in Medicine: To Explain, or Not to Explain, That Is the Question

Abstract

In 2022, the Medical Informatics Europe conference created a special topic called 'Challenges of trustable AI and added-value on health' which was centered around the theme of eXplainable Artificial Intelligence. Unfortunately, two opposite views remain for biomedical applications of machine learning: accepting to use reliable but opaque models, vs. enforce models to be explainable. In this contribution we discuss these two opposite approaches and illustrate with examples the differences between them.