Human-Centric NLP or AI-Centric Illusion?: A Critical Investigation

TL;DR

The paper investigates whether Human-Centric NLP truly centers human needs or is an AI-centric illusion. It critically analyzes trends in data practices, evaluation, and three illustrative case studies to reveal misalignment between proclaimed human-centric aims and actual research priorities. The authors argue for redefining Human-Centric NLP around true human-centered design, holistic evaluation, and consideration of broader societal impacts, supported by interdisciplinary collaboration and ethical grounding. If adopted, this reframing could steer NLP research toward real-world utility and responsible, user-empowering technologies.

Abstract

Human-Centric NLP often claims to prioritise human needs and values, yet many implementations reveal an underlying AI-centric focus. Through an analysis of case studies in language modelling, behavioural testing, and multi-modal alignment, this study identifies a significant gap between the ideas of human-centricity and actual practices. Key issues include misalignment with human-centred design principles, the reduction of human factors to mere benchmarks, and insufficient consideration of real-world impacts. The discussion explores whether Human-Centric NLP embodies true human-centred design, emphasising the need for interdisciplinary collaboration and ethical considerations. The paper advocates for a redefinition of Human-Centric NLP, urging a broader focus on real-world utility and societal implications to ensure that language technologies genuinely serve and empower users.