Exploring Explainability : A Definition, a Model, and a Knowledge Catalogue

Title data

Chazette, Larissa ; Brunotte, Wasja ; Speith, Timo:
Exploring Explainability : A Definition, a Model, and a Knowledge Catalogue.
In: Moreira, Ana ; Schneider, Kurt ; Vierhauser, Michael ; Cleland-Huang, Jane (ed.): 2021 IEEE 29th International Requirements Engineering Conference (RE). - Piscataway, NJ, USA : IEEE , 2021 . - pp. 197-208
ISBN 978-1-6654-2856-9
DOI: https://doi.org/10.1109/RE51729.2021.00025

Project information

Abstract in another language

The growing complexity of software systems and the influence of software-supported decisions in our society awoke the need for software that is transparent, accountable, and trust-worthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. However, in order to incorporate this NFR into systems, we need to understand what explainability means from a software engineering perspective and how it impacts other quality aspects in a system. This allows for an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. Nevertheless, explainability is currently under-researched in the domain of requirements engineering and there is a lack of conceptual models and knowledge catalogues that support the requirements engineering process and system design. In this work, we bridge this gap by proposing a definition, a model, and a catalogue for explainability. They illustrate how explainability interacts with other quality aspects and how it may impact various quality dimensions of a system. To this end, we conducted an interdisciplinary Systematic Literature Review and validated our findings with experts in workshops.