Responsible NLP: Why performance is no longer enough

Abstract

Natural language processing (NLP) has moved from a specialized research field into the everyday infrastructure of writing, search, translation, education, journalism, public administration, and scientific work. This transition changes what counts as progress. Accuracy, fluency, and benchmark performance remain important, but they are no longer sufficient when language technologies shape knowledge, decisions, identities, and public trust. This column introduces Responsible NLP as a research orientation that integrates fairness, transparency, privacy, safety, cultural diversity, environmental awareness, and human agency across the full life cycle of language technologies. It argues that responsibility is not an external constraint on innovation, but a condition for meaningful and trustworthy innovation. Future research must therefore ask not only whether an NLP system works but also for whom it works, under which assumptions, with what risks, and with what forms of accountability.