Interpretable ML [1] is a small online book on interpretable methods. Even if the content itself is rather shallow, it has links to a lot of more focused papers on the topic. Towards A Rigorous Science of Interpretable Machine Learning is one of the most thorough papers on interpretable ML that I have come across. The main author, Finale Doshi-Velez, has a done a lot of interesting work on interpretability [3].
[1] https://christophm.github.io/interpretable-ml-book/
[2] https://arxiv.org/abs/1702.08608
[3] https://finale.seas.harvard.edu/publications