Problems and Prospects for the Use of Individual Artificial Intelligence Tools in Public Administration

The study is focused on the problems and challenges of applying specific tools of artificial intelligence in the public sector. The relevance of the topic is determined by the active growth of the presence of this technology in the society and the state, and the significant potential of its use to solve many problems of the public sector. The development of artificial intelligence is associated with hidden risks and threats to the security of citizens and the sovereignty of the state, therefore, a thorough study of the impact of this technology on society and public institutions is required. The aim of the study is to assess the impact of the Russian population's perception of artificial intelligence on the level of trust and willingness to adopt it and to identify management mechanisms for the introduction of artificial intelligence in the public sector in the Russian institutional environment. To achieve this goal, the study uses a combined approach, which consists of (1) conducting a survey of Russian citizens on the use of artificial intelligence tools in the public sector with further descriptive and comparative analysis and building a regression model to assess the impact of artificial intelligence on society, and (2) conducting semi-structured in-depth interviews with experts in the field of artificial intelligence and public administration to identify effective mechanisms for the implementation of artificial intelligence in the public sector in Russia. The analysis resulted in (1) classifying the areas of application of AI technologies in the public sector and the risks and limitations associated with this process, (2) revealing that the key factor of public perception of artificial intelligence in the public sector is the «real» knowledge about the technology, and (3) proposing specific recommendations for the public sector, based on the creation of a regulatory framework for the safe use of AI systems, the development of local technologies and improving the efficiency of data processing and management.