Subject. This article discusses the use of intelligent decision support systems in BRICS countries public administration. Objectives. The article aims to identify the limiting factors and assess the prospects for the multilateral cooperation development of AI-based solutions in BRICS countries public administration. Methods. For the study, I used the methods of analysis, synthesis, classification, methods of comparative legal analysis and document analysis. Results. The article presents a classification of decision support systems, and defines the characteristics of the current stage of forming the international regime for managing the artificial intelligence development. Conclusions. BRICS countries are at different levels of maturity in their national regimes for managing artificial intelligence development. . Russia can strengthen its position by expanding the scale of supplying ready-made solutions for government administration.
Keywords: decision support systems, artificial intelligence, BRICS, public administration, data management
References:
Kovari A. AI for decision support: Balancing accuracy, transparency, and trust across sectors. Information, 2024, no. 15. DOI: 10.3390/info15110725
Bukht R., Heeks R. Defining, conceptualising and measuring the digital economy. International Organizations Research Journal, 2018, no. 2, pp. 143–172. DOI: 10.17323/1996-7845-2018-02-07
Zubarev S.M. [Legal risks of digitalization of public administration]. Aktual'nye problemy rossiiskogo prava, 2020, vol. 15, iss. 6, pp. 23–32. (In Russ.) DOI: 10.17803/1994-1471.2020.115.6.023-032
Grigalashvili V. E-government and E-governance: Various or multifarious concepts. International Journal of Scientific and Management Research, 2022, vol. 5, iss. 1, pp. 183–196. DOI: 10.37502/IJSMR.2022.5111
Grigalashvili V. Digital government and digital governance: Grand concept. International Journal of Scientific and Management Research, 2023, vol. 6, iss. 2, pp. 1–25. DOI: 10.37502/IJSMR.2023.6201
Sokolova M.E. [First successes of the new Pan-European general data protection regulation]. Sovremennaya Evropa, 2020, no. 2, pp. 56–66. (In Russ.) DOI: 10.15211/soveurope220205666 EDN: AALYIB
Keohane R.O. The demand for international regimes. International Organization, 1982, vol. 36, iss. 2, pp. 325–355.
Aroyo L.M., Lease M., Schaekermann M. et al. Data excellence for AI: Why should you care? Interactions, 2022, vol. 29, iss. 2, pp. 66–69. DOI: 10.1145/3517337
Denisov I.S., Akhmatova D.R., Kabakova V.M. [Comparative characteristics of the GDPR and Russian legislation on personal data]. Pravo. Obshchestvo, 2019, no. 1, pp. 21–27. (In Russ.) EDN: PPBJXF
Bykov I.A. [Public policy of the artificial intelligence development in the European Union]. Vestnik Moskovskogo universiteta. Seriya 12: Politicheskie nauki, 2024, no. 2, pp. 130–144. (In Russ.) DOI: 10.55959/MSU0868-4871-12-2024-2-2-130-144 EDN: JBVPUW
Kartskhiya A.A., Makarenko G.I. [Legal problems in using artificial intelligence in Russia]. Pravovaya informatika, 2024, no. 1, pp. 4–19. (In Russ.) DOI: 10.21681/1994-1404-2024-1-4-19 EDN: NONHLC
Kazakova M.P. [Artificial intelligence in tax law: Current problem of the 21st century]. Voprosy rossiiskoi yustitsii, 2020, no. 9, pp. 608–613. (In Russ.) EDN: AWJCJA
Kimathi E., Tonnang H.E.Z., Subramanian S. et al. Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa. Scientific Reports, 2020, no. 10. DOI: 10.1038/s41598-020-68895-2
Ignatov A.A. [The digital economy of BRICS: Prospects for multilateral cooperation]. Vestnik mezhdunarodnykh organizatsii: obrazovanie, nauka, novaya ekonomika, 2020, vol. 15, iss. 1, pp. 31–62. (In Russ.) DOI: 10.17323/19967845-2020-01-02 EDN: MEQIWM
