Contestable Black Boxes
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Abstract (arXiv)
The right to contest a decision with consequences on individuals or the society is a well-established democratic right. Despite this right also being explicitly included in GDPR in reference to automated decision-making, its study seems to have received much less attention in the AI literature compared, for example, to the right for explanation. This paper investigates the type of assurances that are needed in the contesting process when algorithmic black-boxes are involved, opening new questions about the interplay of contestability and explainability. We argue that specialised complementary methodologies to evaluate automated decision-making in the case of a particular decision being contested need to be developed. Further, we propose a combination of well-established software engineering and rule-based approaches as a possible socio-technical solution to the issue of contestability, one of the new democratic challenges posed by the automation of decision making.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jun 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1; 2025: 0; 2026: 2.
6 papers.
- 2024Contestable AI needs Computational Argumentationcited by 12
- 2021Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutionscited by 7
- 2022Causal Discovery and Knowledge Injection for Contestable Neural Networks (with Appendices)cited by 6
- 2023Clash of the Explainers: Argumentation for Context-Appropriate Explanationscited by 0
- 2026Contesting Artificial Moral Agentscited by 0
- 2026Explainable AI Isn't Enough! Rethinking Algorithmic Contestabilitycited by 0
- 2026Explainable AI Isn't Enough! Rethinking Algorithmic Contestability15 May 2026
- 2026Contesting Artificial Moral Agents10 Feb 2026
- 2024Contestable AI needs Computational Argumentation17 May 2024
- 2023Clash of the Explainers: Argumentation for Context-Appropriate Explanations12 Dec 2023
- 2022Causal Discovery and Knowledge Injection for Contestable Neural Networks (with Appendices)19 May 2022
- 2021Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions20 Jul 2021