Interpretability

The ability to explain or to present an ML model’s reasoning in understandable terms to a human

The ability to understand the value and accuracy of system output. Interpretability refers to the extent to which a cause and effect can be observed within a system or to which what is going to happen given a change in input or algorithmic parameters can be predicted.