Abstract
As the use of AI systems continues to increase, so do concerns over their lack of fairness, legitimacy and accountability. Such harmful automated decision-making can be guarded against by ensuring AI systems are contestable by design: responsive to human intervention throughout the system lifecycle. Contestable AI by design is a small but growing field of research. However, most available knowledge requires a significant amount of translation to be applicable in practice. A proven way of conveying intermediate-level, generative design knowledge is in the form of frameworks. In this article we use qualitative-interpretative methods and visual mapping techniques to extract from the literature sociotechnical features and practices that contribute to contestable AI, and synthesize these into a design framework
Original language | English |
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Pages (from-to) | 613-639 |
Number of pages | 27 |
Journal | Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences |
Volume | 33 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- Artificial intelligence
- Automated decision-making
- Contestability
- Design
- Human–computer interaction
- Machine learning
- Sociotechnical systems
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Data Underlying the Publication: Contestable AI by Design: Towards a Framework
Alfrink, C. P. (Creator), Keller, A. I. (Creator), Kortuem, G. W. (Creator) & Doorn, N. (Creator), TU Delft - 4TU.ResearchData, 16 Aug 2022
DOI: 10.4121/15350118
Dataset/Software: Dataset