What is Interpretable Machine Learning?

Should we always trust a model that performs well? A model could reject your application for a mortgage or diagnose you with cancer. Even if they are correct, we would expect an explanation. A human could give one. A human would be able to tell you that your income is too low or that a cluster of cells is malignant. To get similar explanations from a model we look to the field of interpretable machine learning. We explore this field and understand what it aims to achieve.