Artificial Intelligence as a New Lens on Linguistics
DOI:
https://doi.org/10.69760/portuni.0110003Keywords:
artificial intelligence, linguistics, natural language processing, language models, computational linguistics, corpus linguisticsAbstract
This article explores how recent advances in artificial intelligence (AI) are reshaping linguistics by providing new tools, perspectives, and research paradigms. We review the deepening correlation between AI and linguistic science, from historical roots in early computational linguistics to modern neural models. Key methods such as natural language processing (NLP), machine learning, and deep learning have revolutionized corpus analysis, language acquisition studies, and semantic modeling (Groenewald et al., 2024; Incelli, 2025). Researchers have demonstrated that AI can induce human-interpretable grammatical rules from data (Zewe, 2022; Stanford University, 2024). This synergy is bidirectional: linguistic theory offers formal foundations for AI models, while AI opens new horizons for linguistic inquiry (Portelance & Jasbi, 2025; Shormani, 2025). We discuss applications (e.g., corpus exploration, language learning, large language models) and challenges (data bias, ethical concerns) of this AI-driven lens on language (Anthony, 2024; Incelli, 2025). Overall, AI is seen not as replacing human insight but as a “completely new lens” for understanding language structures and use (Shormani, 2025; Portelance & Jasbi, 2025).
References
Anthony, L. (2024, October 28). Breaking new ground: AI-enhanced concordance analysis. Reading Concordances in the 21st Century. Retrieved from https://blog.bham.ac.uk/rc21/2024/10/28/laurence-anthony-breaking-new-ground-ai-enhanced-concordance-analysis/
Groenewald, E. S., Pallavi, S., Rani, S., Singla, P., Howard, E., & Groenewald, C. A. (2024). Artificial Intelligence in linguistics research: Applications in language acquisition and analysis. Naturalista Campano, 28(1), 1253–1262.
Incelli, E. (2025). Exploring the future of corpus linguistics: Innovations in AI and social impact. International Journal of Mass Communication, 3, 3–10.
Portelance, E., & Jasbi, M. (2025). On the compatibility of generative AI and generative linguistics. arXiv. https://arxiv.org/abs/2411.10533v2
Shormani, M. Q. (2025). What fifty-one years of linguistics and artificial intelligence research tell us about their correlation: A scientometric analysis. Artificial Intelligence Review, 58, 379. https://doi.org/10.1007/s10462-025-11332-5
Stanford University. (2024, April 18). The linguist who lay the foundation for generative AI. Stanford News. Retrieved from https://news.stanford.edu/2024/04/18/laying-foundation-todays-generative-ai/
Zewe, A. (2022, August 30). AI that can learn the patterns of human language. MIT News. Retrieved from https://bcs.mit.edu/news/ai-can-learn-patterns-human-language/
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Porta Universorum
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
License Terms
All articles published in Porta Universorum are licensed under the Creative Commons Attribution–NonCommercial 4.0 International License (CC BY-NC 4.0). This license permits:
-
Sharing (copying and redistributing the material in any medium or format),
-
Adapting (remixing, transforming, and building upon the material),
-
for non-commercial purposes only,
-
with proper attribution to the original author(s) and source.
Commercial use of the material is not permitted without prior written permission from the publisher.
