Alec Thompson


pdf bib
The Ethics of Automating Legal Actors
Josef Valvoda | Alec Thompson | Ryan Cotterell | Simone Teufel
Transactions of the Association for Computational Linguistics, Volume 12

The introduction of large public legal datasets has brought about a renaissance in legal NLP. Many of these datasets are composed of legal judgments—the product of judges deciding cases. Since ML algorithms learn to model the data they are trained on, 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 are too far away from having the facilities necessary for this task, they should not be used to automate judges. Furthermore, even in the case that the models could achieve human-level capabilities, there would still be remaining ethical concerns inherent in the automation of the legal process.