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Explainability Auditing for Intelligent Systems : A Rationale for Multi-Disciplinary Perspectives

Title data

Langer, Markus ; Baum, Kevin ; Hartmann, Kathrin ; Hessel, Stefan ; Speith, Timo ; Wahl, Jonas:
Explainability Auditing for Intelligent Systems : A Rationale for Multi-Disciplinary Perspectives.
In: Yue, Tao ; Mirakhorli, Mehdi (ed.): 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW). - Piscataway, NJ, USA : IEEE , 2021 . - pp. 164-168
ISBN 978-1-6654-1898-0

Project information

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

National and international guidelines for trustworthy artificial intelligence (AI) consider explainability to be a central facet of trustworthy systems. This paper outlines a multi-disciplinary rationale for explainability auditing. Specifically, we propose that explainability auditing can ensure the quality of explainability of systems in applied contexts and can be the basis for certification as a means to communicate whether systems meet certain explainability standards and requirements. Moreover, we emphasize that explainability auditing needs to take a multi-disciplinary perspective, and we provide an overview of four perspectives (technical, psychological, ethical, legal) and their respective benefits with respect to explainability auditing.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Auditing; Certification; Explainability; Explainable Artificial Intelligence; Requirements; Trustworthy AI
Institutions of the University: Faculties > Faculty of Cultural Studies > Department of Philosophy
Faculties > Faculty of Cultural Studies
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
100 Philosophy and psychology > 100 Philosophy
Date Deposited: 27 Feb 2023 09:06
Last Modified: 28 Feb 2023 06:25