mlsanityData to 7 Oct 2026

Contestable AI needs Computational Argumentation

arXiv 2405.10729 ↗First posted 17 May 2024cs.AIcited by 12

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Abstract (arXiv)

AI has become pervasive in recent years, but state-of-the-art approaches predominantly neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI guidelines (e.g. by the OECD) and regulation of automated decision-making (e.g. GDPR). In this position paper we explore how contestability can be achieved computationally in and for AI. We argue that contestable AI requires dynamic (human-machine and/or machine-machine) explainability and decision-making processes, whereby machines can (i) interact with humans and/or other machines to progressively explain their outputs and/or their reasoning as well as assess grounds for contestation provided by these humans and/or other machines, and (ii) revise their decision-making processes to redress any issues successfully raised during contestation. Given that much of the current AI landscape is tailored to static AIs, the need to accommodate contestability will require a radical rethinking, that, we argue, computational argumentation is ideally suited to support.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 36 of its 128 references that are in the map. First posted on arXiv 17 May 2024.

Builds on

36 of 128 references.

References · 36

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24 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 7; 2026: 5.

12 papers.