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May 8, 20260 citationsOpen Access

The Role of Artificial Intelligence in Philological Research

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BSBahor Boltayevna ShukurovaArctic State Agrotechnological University

Key Points

  • This article aims to explore how artificial intelligence influences modern philological research methodologies.
  • Examined existing AI technologies relevant to philological research, including natural language processing and machine translation.
  • Discussed the impact of AI on traditional philological methods, such as textual analysis and linguistic description.
  • Highlighted the need for critical assessment of AI-generated findings in philological contexts.
  • AI allows for the analysis of extensive textual data, enabling the identification of linguistic patterns and stylistic features.
  • The integration of digital technologies fosters new research methodologies in philology, enhancing understanding across languages.
  • Caution is urged regarding the inherent risks of AI's inaccuracies and cultural biases in philological applications.

Abstract

This article examines the role of artificial intelligence in modern philological research. In recent years, artificial intelligence technologies, especially natural language processing, machine translation systems, corpus linguistics tools and large language models, have become increasingly important in the study of language, literature, text, discourse and cultural communication. Philology, as a field that traditionally relies on textual analysis, historical-comparative methods, interpretation and linguistic description, is now entering a new methodological stage under the influence of digital technologies. Artificial intelligence enables researchers to process large volumes of textual data, identify lexical and semantic patterns, compare linguistic units across languages, analyze stylistic features and create digital corpora for further investigation. At the same time, the use of artificial intelligence in philology requires critical thinking, methodological caution and ethical responsibility, because machine-generated results may contain inaccuracies, cultural bias or contextual limitations.

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Bahor Boltayevna Shukurova (2026) studied this question.

synapsesocial.com/papers/69fd7ec6bfa21ec5bbf0714dhttps://doi.org/10.5281/zenodo.20054670
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