Artificial intelligence as an effective tool for measuring and planning the quality of life of the Russian population

Russia’s accession to the UN International sustainable development program involves solving a number of social problems and, above all, combating poverty and smoothing out monetary (in terms of monetary income). Solution to these problems at the present stage of our country’s development is complicated by the military conflict in Ukraine. The collective West is exerting unprecedented sanctions pressure on the national economy. In this situation, the issue of improving the state’s social policy is becoming more relevant, which, in turn, also involves development of tools for monitoring the quality of life of the population of our country. This study is devoted to development and testing of the author’s approach for a comprehensive assessment of the quality of life of the Russian population at the meso-level of management using artificial intelligence. The rating of Russian regions, based on the quality of life of the population, was carried out using the index method. The rating for 2023 was headed by the Republic of Tatarstan, but not, as usual (according to the results presented in other thematic works), by Moscow. The capital of our country took second place in the rating in 2023 (in the previous year, it also practically shared second and third place with St. Petersburg). The relatively low place in the rating is explained by the fact that Moscow was only in 56th place in the third sub-rating, which characterizes the level of poverty and inequality of the population by income. Hence, the capital of the country at the current stage of development is, without exaggeration, a city of contrasts in terms of poverty and monetary inequality of the population. Artificial intelligence allows us to do a correct grouping of subjects of the Russian Federation by the quality of life of the population. With its help, factor analysis is also deepened, and, consequently, the mechanism for planning and forecasting the phenomenon under study is improved. Ultimately, the results of the thematic assessment using artificial intelligence can be taken into account when adjusting the state’s social policy.

quality of life, poverty, social inequality, regions of Russia, artificial intelligence, clustering, classification, forecasting