Introduction. There are currently many different methods in the field of artificial intelligence research. Methods of mathematical, cognitive and philosophical sciences are dominant among them. All research approaches are united by the hypothesis that natural and artificial intelligence are fundamentally comparable. The sociality formed as a result of these changes attracts increasing attention from both foreign and Russian researchers. The purpose of this article is to clarify the theoretical and methodological approaches in the study of artificial intelligence in the social sciences, especially in sociology.Methodology and sources. The article is based on an interdisciplinary approach, which allows outlining the scale of the research problem, coordinating the methodological approach to the organization of research, smoothing the contradictions of ideas and categories, which are operated by different sciences in the study of artificial intelligence.Results and discussion. According to the authors, the widely used concept of Artificial Intelligence is more a scientific metaphor than a proven empirical fact. Currently there is no such thing as artificial intelligence. There are neural networks, machine learning, which can solve certain problems in the real world. Artificial intelligence is a metaphor that captures a certain level of human knowledge about the introduction of information technology, based on computer hardware and specialized software. To treat artificial intelligence as an empirical fact is a fallacy that is not appropriate in science.Conclusion. Sociology is only taking its first steps in the field of artificial intelligence research. It does not have its own methodological tools for analyzing artificial intelligence and the social reality that arises from its introduction into the everyday life of society. Artificial Intelligence changes people's daily lives, embedding itself in everyday social practices, and forming a hybrid social world for the social sciences to study. Today there is a debate about the place of artificial intelligence in sociology. According to the authors, sociological fantasies and speculations are not appropriate here. In order to correctly and accurately define the problem of artificial intelligence in the social sciences, it is necessary to carefully analyze the opinions of the experts in the exact sciences, in which artificial intelligence is understood as algorithms or models created by human, and which perform certain tasks and help them manage specific processes in various spheres of society.
The relevance of the study is determined by the growth of international terrorism and extremism in recent decades. With the growing dynamics of social change, it is important to quickly respond to both positive and negative changes. In a postindustrial society, the most important issue is the speed of decision making. Monitoring of important changes in society can partially solve this problem. Monitoring of social attitudes allows to identify risk groups by identifying extremist attitudes to prevent the further spread of extremist ideology among young people in the early stages of its development. In the course of the project implementation, the approved scientific and methodological support and tools for sociological monitoring of extremist attitudes and identification of extremist behavior risk groups among young people will be obtained. This scientific and methodological support and tools will be used for early diagnosis and prevention of extremism. The scientific novelty of the project is to develop a new approach to the prevention of extremism among young people, which, unlike the existing approaches, emphasizes the prevention of the spread of extremism at the early stages of its development. The study has a high scientific and practical significance, as it allows to get ready-to-use scientific and methodological support for the sociological monitoring of extremist attitudes among young people for political decision-making processes in the field of improving youth and anti-extremist policies. The paper describes the result of developing a conceptual model of digital monitoring of extremist attitudes and identifying risk groups in the youth environment. A conceptual model can be represented in the form of a scheme that includes four interconnected modules: a theoretical and methodological module, a methodical module, an empirical module, and an analytical module. Four stages of monitoring are described, and the main activities at each stage and their main results are highlighted. The basic elements that constitute the scientific and methodological support of sociological monitoring of extremist attitudes and the identification of risk groups in the youth environment are described. Expected results of the study are formulated and substantiation of their scientific significance in theoretical and applied terms is given.
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