Implementation of Generative Artificial Intelligence in Sociological Research

Introduction. This article discusses the use of generative artificial intelligence (GAI) in sociological research. The relevance of the topic is determined by the increasing interest in applying new technologies to enhance the efficiency and accuracy of research in social sciences. GAI provides new opportunities for data collection, processing, and analysis, which can significantly change traditional approaches in sociology. Methodology and sources. The research is based on an analysis of available publications and experimental data obtained during discussions with sociologists using GAI in their projects. The paper examines methodologies for generating surveys, processing respondents' answers, and analyzing big data using machine learning algorithms. The focus is on specific cases of GAI applications in sociological research, as well as examples of successful projects. Results and discussion. The results of the study demonstrate that the use of GAI allows for significantly accelerating the data processing process and enhancing the quality of the data. New patterns and trends in sociological research have been identified, enabling researchers to draw more accurate and justified conclusions. Ethical aspects related to the use of GAI are also discussed, such as issues of confidentiality and algorithmic bias. Conclusion. Generative artificial intelligence represents a powerful tool capable of transforming sociological research. Despite existing challenges, it opens new horizons for data collection and analysis, fostering a deeper understanding of social processes and phenomena. It is important to continue exploring the possibilities and limitations of GAI for the advancement of sociological science.

Authors: Vladimir E. Drach, Yulia V. Torkunova

Direction: Sociology

Keywords: generative artificial intelligence, sociological research, surveys, machine learning, ethical aspects

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