The introduction of large public legal datasets has brought about a renaissance in legal NLP. Many of these datasets are comprised of legal judgements - the product of judges deciding cases. This fact, together with the way machine learning works, means that several legal NLP models are models of judges. While some have argued for the automation of judges, in this position piece, we argue that automating the role of the judge raises difficult ethical challenges, in particular for common law legal systems. Our argument follows from the social role of the judge in actively shaping the law, rather than merely applying it. Since current NLP models come nowhere close to having the facilities necessary for this task, they should not be used to automate judges. Furthermore, even in the case the models could achieve human-level capabilities, there would still be remaining ethical concerns inherent in the automation of the legal process.

翻译：大规模公开法律数据集的引入带来了法律自然语言处理领域的复兴。许多此类数据集由法律判决构成——即法官裁决案件的产物。这一事实与机器学习的工作方式相结合，导致若干法律NLP模型本质上是法官的模型。尽管有人主张实现法官的自动化，但在本文中，我们论证自动化法官角色会引发严峻的伦理挑战，尤其对普通法系国家而言。我们的论点基于法官在社会角色中主动塑造法律而非仅仅适用法律这一事实。由于当前NLP模型远不具备完成该任务所需的能力，它们不应被用于自动化法官。此外，即便模型能达到人类水平的能力，自动化法律程序本身仍存在固有的伦理隐忧。