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Issues of artificial intelligence application to the domestic high-tech industries (critical components of the Russian society)
V. B. Betelina, V. A. Galkinb, T. V. Gavrilenkob, A. K. Dibizhevc, O. V. Kovalenkod, N. F. Nikitinc, V. P. Solovyovd a Federal State Institution “Scientific Research Institute for System Analysis of the Russian Academy of Sciences”, Moscow, Russian Federation
b Surgut Branch of Federal State Institute “Scientific Research Institute for System Analysis of the Russian Academy of Sciences”, Surgut, Russian Federation
c United Aircraft Corporation, Moscow, Russian Federation
d Russian Federal Nuclear Center – Russian Research Institute of Experimental Physics, Sarov, Russian Federation
Abstract:
The authors discuss the issues of a large-scale AI adoption in the domestic high-tech industries. The paper presents the current legal framework and key AI implementation areas. It is shown that the capability of AI technologies available today is limited. There is no theoretical basis or required verification of artificial neural networks or other AI technologies. The paper also covers the issues with developing a digital twin of a human pilot, and the drastic differences between human and artificial intelligence applied to solve incorrect problems in aviation. One of the major conclusions is that a scientific, ideological, and political platform for the AI development and implementation in the mission-critical areas (education, high-tech industry, transportation) shall be prepared and adopted through public hearings and discussions hosted by the RAS, State Duma, with a subsequent review by the Russian Government.
Keywords:
artificial intelligence, high-tech industries, human pilot digital model, incorrect problems in aviation.
Citation:
V. B. Betelin, V. A. Galkin, T. V. Gavrilenko, A. K. Dibizhev, O. V. Kovalenko, N. F. Nikitin, V. P. Solovyov, “Issues of artificial intelligence application to the domestic high-tech industries (critical components of the Russian society)”, Russian Journal of Cybernetics, 2:3 (2021), 8–18
Linking options:
https://www.mathnet.ru/eng/uk78 https://www.mathnet.ru/eng/uk/v2/i3/p8
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Statistics & downloads: |
Abstract page: | 33 | Full-text PDF : | 8 |
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