Missing values are everywhere, and I’ve been dealing with them one way or another for many years. Recently I’ve been doing research in interpretable machine learning. To my surprise, interpretable machine learning has completely changed how I work with missing values. Interpretable learning provides new methods for detecting, understanding, and modeling missing values. In the presentation I’ll show a few surprises where interpretability makes it clear the impact missing values have been having on our machine learning models all along, but which are only visible now thanks to interpretable methods.