THE LANGUAGE OF ARTIFICIAL INTELLIGENCE: LINGUISTIC AND SOCIOLINGUISTIC ANALYSIS OF AI-RELATED NEOLOGISMS (2016-2025)
DOI:
https://doi.org/10.24919/2522-4565.2025.61.20Keywords:
artificial intelligence, neologisms, linguistic innovation, sociolinguistic analysis, word formationAbstract
The study investigates the linguistic and sociolinguistic characteristics of neologisms related to artificial intelligence, which emerged between 2016 and 2025, focusing on their formation patterns, semantic fields, and sociocultural implications within the context of technological advancement.The research combines linguistic and sociolinguistic approaches to analyze over 30 AI-related neologisms collected from technical publications, academic journals, media articles, and tech blogs.The methodological framework includes morphological analysis of word-formation processes, semantic field categorization, and sociolinguistic examination of techno-social context, register variations, and discourse communities.The research presents the first systematic analysis of AI-related neologisms combining linguistic and sociolinguistic perspectives within 2016-2025. The study introduces an original analytical framework for examining how technological advancement influences language evolution, particularly in vocabulary formation and semantic expansion. It demonstrates the bidirectional relationship between linguistic innovation and societal attitudes towards AI technology.The study reveals various word-formation processes in AI-related neologisms, demonstrating language’s adaptability to emerging technological concepts. The findings show that these neologisms serve multiple functions beyond terminology, acting as indicators of societal attitudes and facilitating public discourse on AI technology. The research establishes the migration of technical terms into mainstream usage and highlights the role of metaphorical conceptualization in making complex AI concepts accessible. The evolution of AI-related vocabulary reflects societal debates about AI development and implementation, suggesting directions for future research.
References
De Cremer D., Kasparov G. AI should augment human intelligence, not replace it. Harvard Business Review. 2021. Vol. 18(1). URL: https://hbr.org/2021/03/ai-should-augment-human-intelligence-not-replace-it (дата звернення : 21.12.2024).
Hao Z., Fang F., Peng J.-E. The integration of AI technology and critical thinking in English major education in China : Opportunities, challenges, and future prospects. Digital Applied Linguistics. 2024. Vol. 1. P. 1–16. DOI : https://doi.org/10.29140/dal.v1.2256.
Jabłoński K., Gopalakrishnan S., Kun R. Decision Intelligence : The New Era of Data-Driven Decision- Making. URL: https://lingarogroup.com/blog/decision-intelligence-the-new-era-of-data-driven- decision-making (дата звернення : 21.12.2024).
Kelly-Holmes H. Artificial intelligence and the future of our sociolinguistic work. Journal of Sociolinguistics. 2024. Vol. 28. P. 3–10. DOI: https://doi.org/10.1111/josl.12678.
Maly I. AI, power and sociolinguistics. Journal of Sociolinguistics. 2024. Vol. 28. P. 11–15. DOI: https://doi. org/10.1111/josl.12681.
Prćić T. Exploring the English vocabulary, including neologisms, with resources of AI chatbots used as multitalented superdictionaries. Annual Review of the Faculty of Philosophy, Novi Sad. 2023. Vol. 48(3). P. 257–291. DOI: https://doi.org/10.19090/gff.v48i3.2436.
Toney A. A Large-Scale, Automated Study of Language Surrounding Artificial Intelligence. ArXiv. 2021. abs/2102.12516. DOI: 10.48550/arXiv.2102.12516 [in English].
Zheng J., Ritter A., Xu W. NEO-BENCH : Evaluating robustness of large language models with neologisms. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics. 2024. Vol. 1. P. 1–22. DOI: https://doi.org/10.18653/v1/2024.acl-long.749.
