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Particles of a whole: design patterns for transparent and auditable AI-systems

Author: Fassbender, J.
Published in: Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings, 272-275
Year: 2021
Type: Academic articles
DOI: 10.1145/3460418.3479345

The integration of principles such as transparency and auditability in AI-systems is a challenging endeavour. The demand for guiding concepts is to be not too high-level and not too specific at the same time. In this paper, I will introduce design patterns as a promising method to meet this demand and as a guidance for the implementation of transparency and auditability in sociotechnical AI-systems. This will include the history of design patterns in urban planning and software engineering, as well as their distinguishing features. In extension to this, I outline a pattern approach for responsible AI-systems in a democratic society. This includes a sketch of possible design patterns for transparent and auditable AI-systems. Some early challenges and open questions are discussed at the end, together with the conclusion.

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Judith Faßbender

Researcher: AI & Society Lab

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