Abstract: Deep learning systems are complex and often viewed as opaque---but is this opacity necessary?
To answer this, we first study deep learning as a tool for creating explanations. We show that deep learning models can construct accurate natural language explanations of how two large datasets differ. This can be used to diagnose data issues such as spurious cues and distribution shift, as...