Abstract

The article discusses the possibilities of applying a behavioral approach when creating machine learning models of artificial intelligence mechanisms, taking into account the possibilities of tracking the behavioral reactions of users of digital tools, collecting and analyzing the information received and identifying hidden dependencies, and, as a result, developing management decisions based on the correct interpretation of the data obtained by AI algorithms based on the results of the above analysis. It has been established that when building machine learning models, it is advisable to track the behavioral reactions of users of digital tools, collect and analyze the information received, in order to identify hidden dependencies, since this contributes to increasing the efficiency of prediction and modeling by artificial intelligence of various scenarios of behavior of social groups and ensures an increase in the level of personalization of administrative services. Specific examples of the application of the behavioral approach in fields other than public administration, including economics, mass communications, sociology, and others, are presented. The author analyzes the experience of popular social networks in the current conditions of digital development, which use artificial intelligence tools to adjust the behavior of social groups. It is determined that artificial intelligence is able to quickly process large amounts of data and build certain predictive models on their basis and correct the behavior of controlled systems. However, the correctness of the interpretation of the obtained data by artificial intelligence algorithms depends on the conceptual framework used by the developer in the process of machine learning. It is emphasized that the study of the possibilities of applying artificial intelligence mechanisms based on the use of behavioral approaches is already being actively carried out by leading innovative companies, in particular Netflix, Meta, Google and others, to ensure internal management and other business processes. It has been proven that the use of behavioral approaches to machine learning, which focus on the study of behavioral patterns, can provide more effective methods for predicting and modeling user reactions to various scenarios in the field of public administration and contribute to the development of the most effective solutions without the use of coercion and administrative levers

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