In Terms of Explainability: Refining Requirements for Self-Explainable Systems
Autonomous and software-intensive systems have been growing in occurrence, complexity, and assumed responsibility. Due to the high complexity of these systems, properties like transparency and explainability must be a focus of investigation. To date, no universally applicable definition and guide for the development of (self-)explainable systems exists. A need for explainability standards has already been recognized in the EU AI Act and the IEEE Transparency Standard 7001-2021. To address this need, we propose unified definitions in explainability based on an analysis and combination of existing definitions. Additionally, we present structured explainability requirements that are necessary to build (self-)explainable systems. By analysing the resulting taxonomy, we propose the incorporation of explanation goodness and thus correctness of explanations into the unified definitions. With our approach, we support the development of formal standards for (self-)explainable systems. Establishing such a uniform taxonomy also is a beneficial step towards certifying or auditing explainable systems.