Contestable AI by Design: Towards a Framework. Alfrink, K., Keller, I., Kortuem, G., & Doorn, N. Minds and Machines, 33(4):613–639, December, 2023. ![Contestable AI by Design: Towards a Framework [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{alfrink_contestable_2023,
title = {Contestable {AI} by {Design}: {Towards} a {Framework}},
volume = {33},
issn = {1572-8641},
shorttitle = {Contestable {AI} by {Design}},
url = {https://doi.org/10.1007/s11023-022-09611-z},
doi = {10.1007/s11023-022-09611-z},
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.},
language = {en},
number = {4},
urldate = {2024-05-06},
journal = {Minds and Machines},
author = {Alfrink, Kars and Keller, Ianus and Kortuem, Gerd and Doorn, Neelke},
month = dec,
year = {2023},
keywords = {Artificial intelligence, Automated decision-making, Contestability, Design, Human–computer interaction, Machine learning, Sociotechnical systems},
pages = {613--639},
}
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