Specifics and Adaptation of Machine Learning in Modern Humanities Amid Turbulence, Uncertainty and Systemic Risks: Evidence from Modern Linguistics

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Published: 06.09.2026

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Svitlana Krasniuk
Kyiv National University of Technologies and Design

Abstract

The article explores the specifics, features and directions of adapting machine learning technologies in modern humanities using the example of linguistics. The possibilities of ML for analyzing linguistic data are considered, as well as the problems of uncertainty, turbulence, systemic risks, algorithmic bias and interpretation of results. The need to transition to adaptive machine learning models that combine technological capabilities, expert humanitarian interpretation and a risk-oriented approach is substantiated.

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Data Availability Statement

All data supporting the findings of this study are presented in the text of the scientific work.

Issue

No. 308 (2026): 8th ISPC «Progressive Science and Achievements» (September 6-8, 2026; Dallas, USA).

Section

Philology and Linguistics
Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Biography

Svitlana Krasniuk, Kyiv National University of Technologies and Design

Senior Lecturer, Department of philology and translation

How to Cite

Krasniuk, S. (2026). Specifics and Adaptation of Machine Learning in Modern Humanities Amid Turbulence, Uncertainty and Systemic Risks: Evidence from Modern Linguistics. Scientific Collection «InterConf», 308, 32–38. https://interconf.openpubarchive.com/index.php/proceeding/article/view/75

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