The same model, different responsibilities: Responsible NLP under the EU AI Act

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

The European Union’s Artificial Intelligence Act changes the governance environment in which natural language processing (NLP) systems are developed and deployed. Its central lesson for Responsible NLP is that responsibility does not follow automatically from a model’s architecture or benchmark score. It is distributed across three layers: a general-purpose model, the task-specific system built around it, and the institution in which that system acts. This piece analyses those layers through recruitment, education, public-service chatbots, public-interest text generation, and general-purpose language models. It shows how the Act turns principles into duties concerning risk management, data governance, documentation, transparency, human oversight, and robustness, together with complaint, explanation, and procedural-accountability mechanisms, while also examining its interaction with data-protection law. The analysis reveals a deeper research challenge: compliance requires an evidence chain connecting intended purpose, affected people, evaluation, institutional workflow, and post-deployment monitoring. Regulation cannot create that evidence by itself. Multilingual fairness, construct validity, meaningful explanation, uncertainty communication, and effective contestability remain scientific and sociotechnical problems. The EU AI Act should therefore be understood as a legal floor for Responsible NLP, not its scientific ceiling.