Scruitability is the potential for an algorithm or model to be understood and interpretted by a human. Some representations, such as decision trees, are more naturally scrutible, at least by experts. Other, such as neural networks, are opaque and hence there is a need for techniques in explainable AI to expose aspects of these black-box models. Scrutability is important to ensure legal compliance and expose potential bias in the model.
Used in Chap. 18: page 283
Used in glossary entries: bias, decision tree, explainable AI, neural network