New Framework Automates How AI Systems Handle Legal Burden of Proof
Researchers have developed a formal system for encoding burden-of-persuasion rules into AI reasoning engines, enabling machines to model legal arguments with multiple levels of proof requirements. The approach could automate legal decision-making in contract disputes, regulatory compliance, and courtroom support tools—reducing inconsistency in how different parties' claims are weighted.
Originaltitel: A comprehensive account of the burden of persuasion in abstract argumentation
<p>In this paper, we provide a formal framework for modeling the burden of persuasion in legal reasoning. The framework is based on abstract argumentation, a frequently studied method of non-monotonic reasoning, and can be applied to different argumentation semantics; it supports burdens of persuasion with arbitrary many levels, and allows for the placement of a burden of persuasion on any subset of an argumentation framework’s arguments. Our framework can be considered an extension of related works that raise questions on how burdens of persuasion should be handled in some conflict scenarios that can be modeled with abstract argumentation. An open source software implementation of the introduced formal notions is available as an extension of an argumentation reasoning library. A theoretical analysis shows that our approach can be generalized to a novel method for the preference-based selection of extensions from argumentation frameworks.</p>