On the overlooked issue of defining explanation objectives for local-surrogate explainers

Several methods exist that Yet, we argue that the current literature on model surrogates fit this description and share this goal. However, to explain a prediction lacks the clarity needed for a practitioner despite their shared overall procedure, they set out to make an informed choice on which method to use, different objectives, extract different information given explanation needs. Existing approaches usually lack from the black-box, and consequently produce transparency with regards to the explanation needs they propose diverse explanations, that are -in general-incomparable. to solve, on their specifications and ultimately on their In this work we review the similarities formal objectives. This situation (1) fuels a disseminated research and differences amongst multiple methods, with with propositions that are difficult to compare and (2) a particular focus on what information they extract prevents a sound development of the explainability practice.