China waged a campaign of harassment and intimidation directed at a UK university to get it to shut down sensitive research into alleged human rights abuses, documents seen by the BBC show. Sheffield Hallam University staff in China were threatened by individuals described by them as being from China's National Security Service who demanded the research being done in Sheffield be halted. And access to the university's websites from China was blocked, impeding its ability to recruit Chinese students, in a campaign of threats and intimidation lasting more than two years. In an internal email from July 2024, university officials said attempting to retain the business in China and publication of the research are now untenable bedfellows. When the UK government learned of the case, the then Foreign Secretary David Lammy issued a warning to his Chinese counterpart that it would not tolerate attempts to suppress academic freedoms at UK universities, the BBC understands.

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 natural language processing (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.