Document Type

Conference Proceeding

Publication Title

ICAIL '25: Proceedings of the Twentieth International Conference on Artificial Intelligence and Law

Editors

Juliano Maranhão

Abstract

Argumentation frameworks (AFs) provide formal approaches for legal reasoning, but identifying sources of ambiguity and explaining argument acceptance remains challenging for non-experts. We present AF-XRAY, an open-source toolkit for exploring, analyzing, and visualizing abstract AFs in legal reasoning. AF-XRAY introduces: (i) layered visualizations based on game-theoretic argument length revealing well-founded derivation structures; (ii) classification of attack edges by semantic roles (primary, secondary, blunders); (iii) overlay visualizations of alternative 2-valued solutions on ambiguous 3-valued grounded semantics; and (iv) identification of critical attack sets whose suspension resolves undecided arguments. Through systematic generation of critical attack sets, AF-XRAY transforms ambiguous scenarios into grounded solutions, enabling users to pinpoint specific causes of ambiguity and explore alternative resolutions. We use real-world legal cases (e.g., Wild Animals as modeled by Bench-Capon) to show that our tool supports teleological legal reasoning by revealing how different assumptions lead to different justified conclusions.

Pages

495-497

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DOI

https://doi.org/10.1145/3769126.3769246

Publisher

Association for Computing Machinery

Publication Date

1-2026

Keywords

argumentation frameworks, legal reasoning, interactive visualization, explainable AI

Disciplines

Artificial Intelligence and Robotics | Computer Law | Computer Sciences

Comments

This content was originally presented at the Twentieth International Conference on Artificial Intelligence and Law, held from June 16-20, 2025, in Chicago, IL. 

ISBN

979-8400719394

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