DOI: 10.33917/mic-2.121.2025.47-56

The article examines the historical features of the development of censorship as a system of restrictions and an element of ensuring socio-economic security. The mechanisms of censorship in different epochs of the formation of the world are analyzed. The ways of solving problems in the information environment using technologies in the modern world are outlined.

References:

1. Censorship. The Great Russian Encyclopedia. URL: https://old.bigenc.ru/domestic_history/text/4674643

2. Markin A.N. Institute of Censorship in the Roman Republic. URL: https://cyberleninka.ru/article/n/institut-tsenzury-v-rimskoy-respublike/

3. Surovtseva E.V. Censorship in Ancient Rus’. URL: https://cyberleninka.ru/article/n/tsenzura-v-drevney-rusi/

4. Kulikova S.A. Formation of the constitutional principle of inadmissibility of censorship in the Russian Federation. URL: https://cyberleninka.ru/article/

5. Constitution of the Russian Federation: The Constitution was adopted by popular vote on 12.12.1993 with amendments approved during the all-Russian vote on 01.07.2020. Access from the reference and legal system «ConsultantPlus».

6. On the media: Law of the Russian Federation of 27.12.1991 No. 2124-1 (as amended on 11.03.2024). Access from the reference and legal system «ConsultantPlus».

7. VTsIOM. URL: https://wciom.ru/analytical-reviews/

8. Valkova Irina. Blocking of Internet services in Russia in 2024: trends and reasons. URL: https://pronedra.ru/blokirovki-internet-servisov-v-rossii-v-2024

9. Roskomnadzor announced the existence of tools for “motivating” YouTube. URL: https://www.rbc.ru/technology_and_media/26/07/2024/

10. Peskov spoke in favor of complete freedom of information, but not in wartime. URL: https://tass.ru/politika/

11. Wilson R. Gates proposes using AI to suppress freedom of speech; the UN seeks to control AI worldwide. URL: https://telegra.ph/Gejts-predlagaet-ispolzovat-II-dlya-podavleniya-svobody-slov

DOI: 10.33917/mic-6.119.2024.71-80

The article substantiates the necessity of introducing digital technologies based on artificial intelligence in the Arctic Zone of the Russian Federation. According to the methodology of the World Bank, the indicators of energy production and consumption per capita are important characteristics that reflect not only the dynamics of economic development of regions, but also the quality of life of the population. This study analyzes energy production and consumption in the period from 1990 to 2023, including four regions, the territories of which are fully included in the Arctic Zone of the Russian Federation. The article touches upon the impact of modern technologies based on artificial intelligence (AI) on energy consumption in the future, the use of predictive analytics for sustainable operation of energy systems in the Arctic. It also suggests the possibility of improving the energy efficiency of data centers in the Arctic zone, taking into account the use of natural cooling of servers.

References:

1. On the Strategy for the Development of the Arctic Zone of the Russian Federation and National Security for the Period until 2035: Presidential Decree of the Russian Federation of October 26, 2020. № 645. URL: https://www.garant.ru/products/ipo/prime/doc/74710556/?ysclid=m37uq9lmr885155307  

2. On the Fundamentals of State Policy of the Russian Federation in the Arctic for the period until 2035: Presidential Decree of the Russian Federation of March 5, 2020. № 164.

3. The Arctic Council. Russian Chairmanship. URL: https://as.arctic-russia.ru/useful/

4. EMISS. Government statistics. URL: https://www.fedstat.ru/indicator/55089

 5. What the Arctic will be like in 2035. URL: https://morvesti.ru/analitika/1692/87581/?ysclid=m38p5qacy4456766395. 

6. Babkinа L., Skotarenko, O., Kuznetsova E., Khatsenko E. Digitalization of Electrici-ty Suppliers’ Activities in the Arctic Zone. 5th International Scientific Conference on Digital Economy and Finances. St. Petersburg, Russian Federation, 2022. pp. 439–450.

7. Regions of Russia. Socio-economic indicators – 2023. Official website of the Federal State Statistics Service. URL: https://rosstat.gov.ru/folder/210/document/13204

8. E²nergy. An industry media resource created to cover events and trends in the energy industry of Eurasia and the world. URL: https://eenergy.media/about 

9. On the development of artificial intelligence in the Russian Federation (together with the «National Strategy for the Development of Artificial Intelligence for the period up to 2030»): Decree of the President of the Russian Federation as amended on 02/15/2024 № 490. URL: https://www.consultant.ru/document/cons_doc_law_335184/

10. Ministry of Digital Development, Communications and Mass Media of the Russian Federation. URL: https://digital.gov.ru/

11. Roadmap for the development of «end-to-end» digital technology «Neurotechnology and artificial intelligence». URL: https://digital.gov.ru/uploaded/files/07102019ii.pdf 

DOI: 10.33917/es-5.197.2024.70-79

Currently, the topic of super-AI (Artificial General Intelligence or AGI) has captured the world’s press. Some are fascinated by the incredible possibilities, including the creation of a future global government, while others fear the arrival of an alien mind capable of displacing man. The authors show that, as usual, both positions miss the mark. There is no doubt that AI is a fundamentally new tool. Therefore, it can be both extremely useful and immensely dangerous, depending on its application. One thing is clear: innocence has been lost and it will not be possible to rewind it. The world is entering a new phase of development with the enormous potential. However, the transition period threatens with even greater dangers than the first half of the 20th century, when the advent of the internal combustion engine to replace the steam one has led to dramatic shifts in the economy and a change in political dominance against the backdrop of two world wars.

As industrial productivity growth decreases, financialization grows, oppressing the “real” sector, demographics is falling and the world is sliding into wars for dominance against the backdrop of the fading industrial society of the 20th century.

References:

1. Badalyan L.G., Krivorotov V.F. Industrial’nye Srednie veka, ili Est’ li zhizn’ posle industrial’nogo kapitalizma? Chast’ I [Industrial Middle Ages, or Is There Life After Industrial Capitalism? Part I]. Rossiyskiy ekonomicheskiy zhurnal, 2023, no 3, pp. 17–37.

2. Badalyan L.G., Krivorotov V.F. Industrial’nye Srednie veka, ili Est’ li zhizn’ posle industrial’nogo kapitalizma? Chast’ II [Industrial Middle Ages, or Is There Life After Industrial Capitalism? Part II]. Rossiyskiy ekonomicheskiy zhurnal, 2023, no 4, pp. 4–23.

3. Corsini R.J. The Dictionary of Psychology. London, Routledge, 2016. P. 494.

4. Davidson H. Alfarabi, Avicenna, and Averroes, on Intellect. Oxford University Press, 1992, p. 6.

5. Colman A.M. A Dictionary of Psychology. 3rd ed. Oxford [etc.]. Oxford University Press, 2008.

6. Sangha N. Instinct, Intellect, Intelligence, Intuition. Occult Mysteries, 2015, available at: https://occult-mysteries.org/intelligence.html

7. Kant I. Kritika sposobnosti suzhdeniya: Sobr. soch. [Critique of Judgment: Collected Works]. Vol. 5. Moscow, Mysl’, 1966.

8. Zhukovskiy V.A. Skazka o Ivane-tsareviche i Serom Volke [The Tale of Ivan Tsarevich and the Gray Wolf]. Moscow, Prospekt, 2013, 31 p.

9. De Gruyter. Kant and Artificial Intelligence. Edited by Hyeongjoo Kim and Dieter, 2022.

10. Asimov I.I, Robot. Garden City. N.Y., Doubleday, 1950.

11. Zhuravlev Yu.I. Ob algebraicheskom podkhode k resheniyu zadach raspoznavaniya ili klassifikatsii [On an Algebraic Approach to Solving Recognition or Classification Problems]. Problemy kibernetiki, vyp. 33. Moscow, Nauka, 1977.

12. Zhuravlev Yu.I. Korrektnye algebry nad mnozhestvami nekorrektnykh (evristicheskikh) algoritmov [Correct Algebras over sets of Incorrect (Heuristic) Algorithms]. Kibernetika, 1977, no 4; 1978, no 8.

DOI: 10.33917/mic-5.118.2024.14-25

Artificial intelligence and natural intelligence are two types of intelligence coexist in the world today. Despite the artificial intelligence is still little studied, it is changing all areas of human activity. It is a universal tool allows people to rethink how we integrate information, analyze data, and use insights to improve decision-making. The study analyzes areas where artificial intelligence and natural intelligence are unique. It also reveals the artificial intelligence positive value for natural intelligence. Artificial intelligence algorithms are not like passive machines capable of mechanical or predetermined responses. It combines information from different sources, instantly analyzes the material and displays information results obtained from the data. Data form can vary and may be as digital information, satellite imagery, visual information, text or unstructured data. Due to massive improvements in storage systems, processing speed, and analytical techniques, artificial intelligence is capable of incredibly complex analysis. The article identifies the main differences and similarities in the artificial and natural intelligence characteristics, as well as the exceptional capabilities of these concepts. Despite the natural intelligence is endowed with a creative component that nothing can supplant so far, artificial intelligence is already changing the world and raising important issues for the social, economic and political spheres. Artificial intelligence acts as an assistant to natural intelligence. Artificial intelligence is not a futuristic concept, but rather something that exists today, being integrated and implemented in various sectors. This includes areas such as finance, national security, healthcare, litigation, transportation, construction, and industry. There are many examples of how AI is already making an impact on the world and significantly expanding human capabilities.

References:

1. Kant I. Critique of Pure Reason / Translated from German by N. Lossky, verified and edited by Ts.G. Arzakanyan and M.I. Itkin, note by Ts.G. Arzakanyan. Moscow: Mysl, 1994. 591 p.

2. Osipov G.S., Velichkovsky B.M. Artificial Intelligence. The Great Russian Encyclopedia 2004–2017. URL: https://old.bigenc.ru/mathematics/text/2022537?ysclid=lxnb09fze448915724

3. Bridges A., Royka A., Wilson T. et al. Bumblebees Socially Learn Behavior Too Complex to Innovate Alone. Nature. URL: https://www.nature.com/articles/s41586-024-07126-4

4. Marx K., Engels F. Works. v. 46, part 2. 652 p.

5. Kozlowski P. Postmodern Culture: Social and Cultural Consequences of Technical Development: Transl. from Germ. 1997. 240 p.

6. Lepskiy V.E. Artificial Intelligence in Subjective Management Paradigms. Philosophical Sciences. 2021;64(1):88–101.

7. Glukhikh V.A., Eliseev S.M., Kirsanova N.P. Artificial Intelligence as a Problem of Modern Sociology. DISCOURSE. 2022;8(1):82–93.

8. Belikova E.K. Popov E.A. Modern problems of the relationship between natural and artificial intelligence in the paradigm of culture. Social problems of society development. Sociology of culture. 2023;11: 9–13.

DOI: 10.33917/es-4.196.2024.46-53

The purpose of this article is to identify criteria for the influence of artificial intelligence technologies in payment systems on the consciousness of the population as their main user. When reviewing technologies, methods of scientific analysis were applied: the method of analysis and synthesis, abstraction, generalization, description, induction, deduction.

The article dwells on assessment of the implementation and impact of technologies based on artificial intelligence. It is shown that at the moment a situation has arisen where artificial intelligence tools have the opportunity to manipulate human consciousness. Accelerated development of human interaction in the virtual space resulted in both positive and negative consequences of the use of artificial intelligence technologies in payment systems within the framework of the new social reality. Based on the identified advantages and disadvantages, criteria for the impact of artificial intelligence technologies on the consciousness of the population were discovered and identified.

References:

1. Velichkovskiy B.B. Soznanie [Conscience]. Bol’shaya rossiyskaya entsiklopediya, available at: https://bigenc.ru/c/soznanie-f1153b

2. Tekhnologii iskusstvennogo intellekta i mashinnogo obucheniya [Artificial Intelligence and Machine Learning Technologies]. NIU VShE, 2021, 5 marta, available at: https://hsbi.hse.ru/articles/tekhnologii-iskusstvennogo-intellekta-i-mashinnogo-obucheniya/

3. 12 variantov ispol’zovaniya II i mashinnogo obucheniya v finansakh [12 Ways to Use AI and Machine Learning in Finance]. Generativnyy analiz dannykh, 2020, 10 aprelya, available at: https://zephyrnet.com/ru/12-use-cases-of-ai-and-machine-learning-in-finance/

4. Fedorov D. Chto takoe NLP? [What is NLP?]. Renovatsio, 2023, available at: https://renovatsio.rf/media/natural-language-processing

5. Vot polozhenie NLP v finansakh. Ty dolzhen znat’ [Here is the Position of NLP in Finance. You Should Know]. Shaip, 2023, 26 oktyabrya, available at: https://ru.shaip.com/in-the-media/here-are-the-applications-of-nlp-in-finance-you-need-to-know/

6. Perspektivy razvitiya chat-botov v bankovskom sektore: golosovoy II, prognozirovanie povedeniya, analiz nastroeniya [Prospects for the Development of Chatbots in the Banking Sector: Voice AI, Behavior Forecasting, Mood Analysis]. TalkBank, 2022, 21 yanvarya, available at: https://business.talkbank.io/tpost/ lp3s2ai1c1-perspektivi-razvitiya-chat-botov-v-banko

7. Vershinin O. Neyronnye seti: printsip raboty, perspektivy i 159 sovremennykh neyronok [Neural Networks: the Principle of Operation, Prospects and 159 Modern Neurons]. Neiros, 2023, 17 noyabrya, available at: https://neiros.ru/blog/automation/neyronnye-seti-printsip-raboty-perspektivy-i-159-sovremennykhneyronok/

8. Kak rabotayut neyronnye seti? [How do Neural Networks Work?]. Productstar, 2023, 16 marta, available at: https://blog.productstar.ru/kak-rabotayutnejronnye-seti/

9. Prediktivnaya analitika: instruktsiya po primeneniyu II pri prognozirovanii [Predictive Analytics: Instructions for using AI in Forecasting]. SBER Pro, 2023, 23 avgusta, available at: https://sber.pro/publication/prediktivnaya-analitika-instrukcziya-po-primeneniyu-ii-pri-prognozirovanii/

DOI: 10.33917/es-3.195.2024.68-79

This work continues to examine the model-oriented system engineering [1–3] and at the same time presents an approach based on streamlining and sequentially complex complementing of MBSE formats according to the principle “from simpler to more complex” with the subsequent study of the possibility to include the considered modeling formats in tool platforms of digital engineering. The main focus is made on the systematic orderliness and logic of the approach presentation, with the understanding that in the subject area there is a wide range of divergent definitions (the well-known effect of the language of the Tower of Babel builders).

References:

1. Kondrat’ev V.V. Model’no-orientirovannyy sistemnyy inzhiniring 2.0 [Model-Based Systems Engineering 2.0]. Moscow, MF TI, 2021.

2. Garichev S.N., Gorbachev R.A., Davydenko E.V., Dzhaparov B.A., Kondrat’ev V.V. Model’no-orientirovannyy inzhiniring fiziko-tekhnicheskikh, informatsionnykh i intellektual’nykh system [Model-Based Engineering of Physical, Technical, Information and Intelligent Systems]. Trudy MFTI, 2022, vol.

14, no 2.

3. Kondrat’ev V.V., Tishchenko E.B. Arkhitekturnyy inzhiniring gibridnykh modeley, vklyuchayushchikh tsifrovye dvoyniki i mashinnoe obuchenie [Architectural Engineering of Hybrid Models Incorporating Digital Twins and Machine Learning]. Ekonomicheskie strategii, 2023, no 5(191), pp. 94–99, DOI:

10.33917/es-5.191.2023.94-99

4. Semin A.N., Tishchenko E.B., Kislitskiy M.M., Kurdyumov A.V. Razvitie metodologicheskikh polozheniy proektnogo upravleniya v sfere obespecheniya tekhnologicheskogo suvereniteta APK [Development of Methodological Provisions of Project Management in the Field of Ensuring Technological Sovereignty of the Agro-Industrial Complex]. Fundamental’nye i prikladnye issledovaniya kooperativnogo sektora ekonomiki, 2022, no 4, pp. 3–10.

5. Kondrat’ev V.V., Lorents V.Ya. Daesh’ inzhiniring! [Give me Engineering!]. Moscow, Eksmo, 2007 (Navigator dlya professionala).

6. Romanov A.A. Prikladnoy sistemnyy inzhiniring [Applied Systems Engineering]. Moscow, FIZMATLIT, 2015.

7. Borovkov A.I., Burdakov S.F., Klyavin O.I., Mel’nikova M.P., Mikhaylov A.A., Nemov A.S., Pal’mov V.A., Silina E.N. Komp’yuternyy inzhiniring [Computer Engineering]. Ucheb. posobie. Saint Petersburg, Izd-vo Politekhn. un-ta, 2012.

8. Potyupkin A.Yu., Chechkin A.V. Iskusstvennyy intellekt. Na baze informatsionno-sistemnoy izbytochnosti [Artificial Intelligence. Based on Information System Redundancy]. Moscow, Kurs, 2022.

9. Organizatsionnyy dizayn. Resheniya dlya korporatsiy, kompaniy, predpriyatiy: Mul’timediynoe uchebnoe posobie + Praktikum na CD-R [Organizational Design. Solutions for Corporations, Companies, Enterprises: Multimedia Textbook + Workshop on CD-R]. Pod red. V.V. Kondrat’eva. Moscow, INFRA-M, 2018 (Upravlenie proizvodstvom).

10. ArchiMate. Vikipediya, available at: https://ru.wikipedia.org/

11. Generativnyy iskusstvennyy intellekt [Generative Artificial Intelligence]. Vikipediya. URL: https://ru.wikipedia.org/

DOI: 10.33917/es-3.195.2024.50-59

Innovation is a key factor in the modern economy development. At the same time, strategic planning in the context of innovation development is a primary step towards scientific and technological leadership and sovereignt y. In the modern world, key powers are investing enormous amounts of money in the race for leadership in the field of ar tificial intelligence, defining innovation for the coming years and decades. At the moment most countries, including Russia, have already formed their strategic vision for this sphere’s development. If we consider ar tificial intelligence technologies not just as a way to automate production processes, but as a tool to transform the entire economy due to the synergistic ef fect from introducing these technologies, then the question of the current role of AI in strategizing innovation becomes paramount. Analysis of the relationship between strategic planning documents and the National AI Development Strategy will mak e it possible to identify its place in the existing hierarchy of strategic documents and, as a result, to determine the strategy’s potential in stimulating Russia’s innovation development and economic transformation.

References:

1. Ukaz Prezidenta RF ot 10 oktyabrya 2019 g. N 490 “O razvitii iskusstvennogo intellekta v Rossiyskoy Federatsii” [Decree of the President of the Russian Federation dated October 10, 2019 No. 490 “On the Development of Artificial Intelligence in the Russian Federation”]. Garant, available at: https://base.garant.ru/72838946

2. Porter M. Konkurentnaya strategiya. Metodika analiza otrasley konkurentov [Competitive Strategy. Methodology for Analyzing Competitors’ Industries]. Moscow, Al’pina Pablisher, 2015, 435 p.

3. Khamel G., Prakhalad K.K. Konkuriruya za budushchee. Sozdanie rynkov zavtrashnego dnya [Competing for the Future. Creating Tomorrow’s Markets]. Moscow, Olimp-Biznes, 2014, 288 p.

4. Kvint V.L. Kontseptsiya strategirovaniya [Concept of Strategizing]. Kemerovo, Kemerovskiy gosudarstvennyy universitet, 2022, 170 p., DOI: 10.21603/978-5-8353-2562-7

5. Artificial Intelligence Index Report, 2023. Stanford University, available at: https://aiindex.stanford.edu/report/

6. Pasport FP “Iskusstvennyy intellect” [FP Passport of “Artificial Intelligence”]. Konsul’tantPlyus. Sudebnye i normativnye akty RF, available at: https://sudact.

ru/law/pasport-federalnogo-proekta-iskusstvennyi-intellekt-natsionalnoi-programmy

7. Indeks gotovnosti prioritetnykh otrasley ekonomiki Rossiyskoy Federatsii k vnedreniyu iskusstvennogo intellekta: Analiticheskiy otchet [Index of Readiness of Priority Sectors of the Russian Economy for Implementing Artificial Intelligence: Analytical Report]. Analiticheskiy tsentr pri Pravitel’stve RF; MGU imeni

M.V. Lomonosova, 2021, 159 p.

8. Kolin K.K. Novyy etap razvitiya iskusstvennogo intellekta: natsional’nye strategii, tendentsii i prognozy [New Stage of Artificial Intelligence Development: National Strategies, Trends and Forecasts]. Strategicheskie prioritety, 2019, no 2(22), pp. 4–12.

DOI: 10.33917/es-2.194.2024.42-53

While the physical basis of natural intelligence is the human brain, the physical basis of artificial intelligence (AI) is constituted by computers. Currently, the processes of creating AI based on computer technology are developing in two main directions — logical direction and neuromorphic one. The logical approach is aimed at creating computer systems designed to solve one or a limited set of “intelligent” problems (that is, problems whose solution would require intelligence if they were solved by a person). The neuromorphic approach aims to create computer systems that imitate the human brain functioning, and ultimately to create its artificial analogue.

References:

1. Yangging Jia. Technical Report. No. VCB/EECS 2014-93, Berkley.

2. Kalyaev I.A., Levin I.I., Semernikov E.A., Shmoilov V.I. Reconfigurable Multipipeline Computing Structures. Nova Science Publishers, Inc. USA. 2012. 340 p.

3. Guzik V.F., Kalyaev I.A., Levin I.I. Rekonfiguriruemye vychislitel’nye sistemy [Reconfigurable Computing Systems]. Rostov n/D, Izd-vo YuFU, 2016, 472 p.

4. Kalyaev I.A., Levin I.I. Rekonfiguriruemye vychislitel’nye sistemy na osnove PLIS [Reconfigurable Сomputing Systems Based on FPGAs]. Rostov n/D, Izd-vo YuNTs RAN, 2022, 475 p.

5. Spall J., Guo X., Barrett T.D., Lvovsky A.I. Fully reconfigurable coherent optical vector-matrix multiplication. Optics Letters, 45, 5752–5755 (2020).

6. Tait A.N., de Lima T.F., et al. Neuromorphic photonic networks using silicon photonic weight banks. Scientific Reports, 7, 7430 (2017).

7. Shen Y., Harris N.C., et al. Deep learning with coherent nanophotonic circuits. Nature Photon, 11(7), pp. 441–446 (2017).

8. Golovastikov N.V., Dorozhkin P.S., Soyfer V.A. Intellektual’nye tekhnicheskie sistemy na osnove fotoniki [Intelligent Technical Systems Based on Photonics]. Ontology of Designing, 2021, vol. 11, pp. 422–436.

9. Mikhaylov A.N., Gryaznov E.G., Lukoyanov V.I., Koryazhkina M.N., Bordanov I.A., Shchanikov S.A., Tel’minov O.A., Ivanchenko M.V., Kazantsev V.B. Na puti k realizatsii vysokoproizvoditel’nykh vychisleniy v pamyati na osnove memristornoy elektronnoy komponentnoy bazy [Towards the Implementation of High-performance Computing in Memory Based on Memristor Electronic Components]. Fizmat, 2023, vol. 1, no 1, pp. 42–64, DOI: 10.56304/S0000000023010021

10. Mikhaylov A.N., Gryaznov E.G., Koryazhkina M.N., Bordanov I.A., Shchanikov S.A., Telminov O.A., Kazantsev V.B. Neuromorphic computing based on CMOS-integrated memristive arrays: current state and perspectives. Supercomputing Frontiers and Innovations, 2023, vol. 10, no 2, pp. 77–103, DOI: 10.14529/jsfi230206

11. Dongarra J. Less Moor, more Brain. Moskovskiy superkomp’yuternyy forum, MGU, 2019.

12. Iskusstvennyy intellekt uvelichil moshchnost’ Superkomp’yuternogo tsentra “Politekhnicheskiy”. Saint Petersburg, SPbPU Petra Velikogo, Nauka i innovatsii, 22 dekabrya 2023 g. [Artificial Intelligence Has Increased the Capacity of the Polytechnic Supercomputer Center. St. Petersburg, Peter the Great St. Petersburg Polytechnic University. Science and Innovation, December 22, 2023], available at: https://www.spbstu.ru/media/news/nauka_i_innovatsii/
iskusstvennyy-intellekt-uvelichil-moshchnost-superkompyuternogo-tsentra-politekhnicheskiy/

DOI: 10.33917/es-1.193.2024.84-85

DOI: 10.33917/es-6.192.2023.134-135

Review of the textbook “Scientific and technological progress and modern international relations”, published by the Moscow State Institute of International Relations (MGIMO) of the Russian Ministry of Foreign Affairs on the initiative of the Centre for International Information Security, Science and Technology Policy.

The textbook provides up-to-date and structured information and analysis on certain types of technologies with an emphasis on their importance for global politics.