Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modelling

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A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems (2011, unknown): “In [168], Zhou and Gan introduced a global framework distinguishing two different levels for fuzzy system interpretability, high-level and low-level interpretability.”
Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures (2011, background): “Different works [10,54,75] have proposed interesting taxonomies as a way to study interpretability aspects within the more general area of fuzzy systems:”
Explainable Artificial Intelligence: a Systematic Review (2020, unknown): “Interactivity The capacity of an explanation system to reason about previous utterances both to interpret and answer users’ follow-up questions [80, 81] Interestingness The capacity of a method for explainability to facilitate the discovery of novel knowledge and to engage user’s attention [64, 82, ”