NLP Meets the World: Toward Improving Conversations With News Media About Natural Language Processing Research

Shomir Wilson


Abstract
Recent advances in large language models (LLMs) have rapidly increased the public’s interest in natural language processing (NLP). This attention is reflected by news outlets inviting NLP researchers to share their knowledge and views with public audiences. Recognizing the opportunities for the research field and for individual researchers, this paper shares recommendations for speaking with news media about NLP’s capabilities and limitations. Drawing on the topical structure of research communication frameworks published by the US National Academies of Sciences, Engineering, and Medicine and the European Union’s QUEST project, recommendations are provided for three field-appropriate communication challenges: cognitive terminology, unsustainable expectations, and ethical failures. Published NLP research and popular news coverage are cited to provide examples. The recommendations promote effective, transparent communication with the general public about NLP, in order to strengthen public understanding and encourage support for research.
Anthology ID:
2026.emnlp-main.1441
Volume:
Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
Month:
October
Year:
2026
Address:
Budapest, Hungary
Editors:
Hung-Yi Lee, Sunipa Dev, Jessy Li, Desmond Elliott
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
32910–32917
Language:
URL:
https://aclanthology.org/2026.emnlp-main.1441/
DOI:
10.18653/2026.emnlp-main.1441
Bibkey:
Cite (ACL):
Shomir Wilson. 2026. NLP Meets the World: Toward Improving Conversations With News Media About Natural Language Processing Research. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, pages 32910–32917, Budapest, Hungary. Association for Computational Linguistics.
Cite (Informal):
NLP Meets the World: Toward Improving Conversations With News Media About Natural Language Processing Research (Wilson, EMNLP 2026)
Copy Citation:
PDF:
https://aclanthology.org/2026.emnlp-main.1441.pdf