ARTIFICIAL INTELLIGENCE-BASED DECISION-MAKING IN PUBLIC ADMINISTRATION

Abstract

This article considers the possibilities and challenges of using artificial intelligence (AI) for decision-making in the public administration system. The aim of the study is to analyze the possibilities of using AI for decision-making in public administration. The research employs the following methods: correlation analysis, the least squares method, the White heteroscedasticity test, and the Chow test. The results of the study demonstrate the significant benefits of using AI technologies to increase the efficiency and transparency of public authorities and improve the quality of public services. Empirical research proves a positive correlation between the level of use of AI in public administration and the quality thereof. The model built demonstrates a significant correlation at the level of almost 60%. The least squares method establishes the main parameters of the model. The White heteroskedasticity test confirms the null hypothesis. The Chow test confirms the absence of structural shifts. The growing trend of using AI in the spheres of public services, social protection, economy and health care in Central and Eastern Europe is revealed. It is recommended to develop a comprehensive strategy in order to successfully realize the potential of AI as follows: create a favorable environment, ensure the transparency of AI systems, and develop the appropriate regulatory and legal framework. It is planned to study the results of using AI for decision-making in public administration in countries with different levels of economic development, which will contribute to the provision of more universal recommendations