Towards an Argumentative Foundation for Evaluative AI
arXiv:2608.07473v1 Announce Type: new Abstract: Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting competing hypotheses together with evidence for and against each. In this position paper, we advocate (computational) argumentation as a particularly suitable paradigm to provide a formal, computable foundation for forms of EAI that are explainable and contestable, setting the ground for a long-term research agenda towards distributed and human-centred EAI systems.
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[Submitted on 25 Apr 2026]
Title:Towards an Argumentative Foundation for Evaluative AI
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Abstract:Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting competing hypotheses together with evidence for and against each. In this position paper, we advocate (computational) argumentation as a particularly suitable paradigm to provide a formal, computable foundation for forms of EAI that are explainable and contestable, setting the ground for a long-term research agenda towards distributed and human-centred EAI systems.
Subjects:
Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)
Cite as: arXiv:2608.07473 [cs.AI]
(or arXiv:2608.07473v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2608.07473
arXiv-issued DOI via DataCite
Submission history
From: Xiang Yin [view email] [v1] Sat, 25 Apr 2026 13:26:11 UTC (131 KB)
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