In this work, I discuss how Large Language Models can be applied in the legal domain, circumventing their current drawbacks. Despite their large success and acceptance, their lack of explainability hinders legal experts to trust in their output, and this happens rightfully so. However, in this paper, I argue in favor of a new view, Justifiable Artificial Intelligence, instead of focusing on Explainable Artificial Intelligence. I discuss in this paper how gaining evidence for and against a Large Language Model's output may make their generated texts more trustworthy - or hold them accountable for misinformation.

翻译：本文探讨如何将大语言模型应用于法律领域，同时规避其现有缺陷。尽管大语言模型取得了巨大成功并得到广泛认可，但其缺乏可解释性导致法律专家难以信任其输出结果——这种质疑实属合理。然而，本文提出了一种新视角：与聚焦可解释人工智能不同，应倡导"可论证人工智能"。本文阐释了通过收集支持或反驳大语言模型输出的证据，能够使其生成的文本更可信——或明确追究其传播错误信息的责任。