Human-centered LLMs for Inclusive Language Technology: The Need to Embrace Variation Holistically in NLP
Barbara Plank
DOI: http://dx.doi.org/10.15439/2025F4610
Citation: Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 43, pages 43–45 (2025)
Abstract. Large Language Models (LLMs) have advanced rapidly but often still cater primarily to a narrow set of users. This position paper advocates for a human-centered approach to NLP technology---one that embraces linguistic variation, improves reasoning and safety, and better serves diverse communities. We outline key challenges with current LLMs, highlight opportunities in modeling variation in both language and human annotation, and outline a path toward more inclusive and trustworthy language technologies.