On the Ethical Limits of Natural Language Processing on Legal Text
It addresses ethical challenges for legal scholars and practitioners using NLP, but is incremental as it systematizes existing debates without introducing new methods or data.
The paper tackles the problem of identifying ethical limits in using NLP for legal text analysis, emphasizing three underestimated normative parameters—academic freedom, diversity of legal and ethical norms, and the threat of moralism—and provides specific recommendations for the legal NLP community.
Natural language processing (NLP) methods for analyzing legal text offer legal scholars and practitioners a range of tools allowing to empirically analyze law on a large scale. However, researchers seem to struggle when it comes to identifying ethical limits to using NLP systems for acquiring genuine insights both about the law and the systems' predictive capacity. In this paper we set out a number of ways in which to think systematically about such issues. We place emphasis on three crucial normative parameters which have, to the best of our knowledge, been underestimated by current debates: (a) the importance of academic freedom, (b) the existence of a wide diversity of legal and ethical norms domestically but even more so internationally and (c) the threat of moralism in research related to computational law. For each of these three parameters we provide specific recommendations for the legal NLP community. Our discussion is structured around the study of a real-life scenario that has prompted recent debate in the legal NLP research community.