Human-Centric NLP or AI-Centric Illusion?: A Critical Investigation
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 24 references that are in the map. First posted on arXiv 14 Dec 2024.
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8 of 24 references.
References · 8
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2019Energy and Policy Considerations for Deep Learning in NLPcited by 1,242
- 2020Beyond Accuracy: Behavioral Testing of NLP models with CheckListcited by 979
- 2019A Just and Comprehensive Strategy for Using NLP to Address Online Abusecited by 49
- 2021Putting Humans in the Natural Language Processing Loop: A Surveycited by 40
- 2020Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gazecited by 16
- 2023NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMscited by 14
- 2022Human-Centric Research for NLP: Towards a Definition and Guiding Questionscited by 9
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