The SAGE Framework for Explaining Context in Explainable Artificial Intelligence

Abstract

Scholars often recommend incorporating context into the design of an explainable artificial intelligence (XAI) model in order to ensure successful real-world adoption. However, contemporary literature has so far failed to delve into the detail of what constitutes context. This paper addresses that gap by firstly providing normative and XAI-specific definitions of key concepts, thereby establishing common ground upon which further discourse can be built. Second, far from pulling apart the body of literature to argue that one element of context is more important than another, this paper advocates a more holistic perspective which unites the recent discourse. Using a thematic review, this paper establishes that the four concepts of setting, audience, goals and ethics (SAGE) are widely recognized as key tools in the design of operational XAI solutions. Moreover, when brought together they can be employed as a scaffold to create a user-centric XAI real-world solution.

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