SOME ISSUES OF THE METHODOLOGY OF USING ARTIFICIAL INTELLIGENCE IN ETHNOLOGICAL RESEARCH: OPPORTUNITIES AND CHALLENGES

Abstract

The article explores the application of artificial intelligence (AI) in ethnological research, showcasing its potential in analyzing cultural data. It highlights methods for processing texts, images, and videos using deep learning and natural language processing (NLP). These approaches enable automation, structuring large datasets, and identifying cultural patterns such as symbolism, folklore narratives, and traditional practices. Examples of successful AI applications include analyzing ornaments, mythological texts, and social media data to track shifts in public opinion. However, the authors emphasize challenges like interpreting cultural context, risks of bias, and ethical issues, including data privacy concerns. Addressing these challenges requires interdisciplinary collaboration between ethnologists and AI specialists and the development of tailored algorithms. The author concludes that integrating AI can make ethnological research more precise, efficient, and scalable while respecting cultural nuances. AI is presented as a complementary tool to traditional research methods, opening new opportunities to study cultural heritage in a globalized context.