DOI: 10.33917/es-6.204.2025.16-25

In the present work the authors practically present a requiem for cybernetics — a classical management science that has fulfilled its historical role, but is now giving way to new approaches emerging at the junction of the philosophy of knowledge, complexity theory, the cognitive and social sciences. The article gives a historical and philosophical overview of cybernetics — from Plato, Ampere and Wiener to the present day. It is demonstrated that classical cybernetic paradigm — a mechanistic control model with feedback loops and representation of the world as a set of “finite state machines” — has proven insufficient in the era of dynamically changing, weakly deterministic, self-organizing living systems. Analysis of the causes of the methodological crisis in cybernetics at the turn of the 20th and 21st centuries is provided and it is argued that its resources are exhausted — further progress requires transition to new conceptual ideas. The authors propose a new engineering approach to understanding the World (K3-Engineering) and an original concept for Genesis of the digital — “Digital Genesis” — as a promising replacement.

References:

1. Wiener N. Cybernetics: or Control and Communication in the Animal and the Machine. 1948.

2. Beer S. Brain of the Firm. London, Allen Lane, 1972. 320 p.

3. Sobolev S.L., Kitov A.I., Lyapunov A.A. Osnovnye cherty kibernetiki [The Main Features of Cybernetics]. Voprosy filosofii, 1955, no 4, pp. 136–148.

4. Thiel P., Douthat R. Peter Thiel and the Antichrist. The New York Times, June 26, 2025.

5. Karp A., Zamiska N. The technological republic: hard power, soft belief, and the future of the West. Crown Publishing Group, 2025.

6. Budanov V.G. Metodologiya sinergetiki v postneklassicheskoy nauke i v obrazovanii [Methodology of Synergetics in Post-Non-Classical Science and Education]. Izd. 4-e dop. Moscow, Lenand, 2017, 272 p.

7. Budanov V.G., Kutin V.N., Khokhlova M.N. Kognitivnyy kollektivnyy konvergentnyy inzhiniring. Chast’ I [Cognitive Collective Convergent Engineering. Part I]. Ekonomicheskie strategii, 2023, no 5, pp. 100–109, DOI: https://doi.org/10.33917/es-5.191.2023.100-109

8. Budanov V.G., Kutin V.N., Khokhlova M.N. Kognitivnyy kollektivnyy konvergentnyy inzhiniring. Chast’ II [Cognitive Collective Convergent Engineering. Part II]. Ekonomicheskie strategii, 2023, no 6, pp. 52–61, DOI: https://doi.org/10.33917/es-6.192.2023.52-61

9. Kutin V.N., Khokhlova M.N. Kak aytishniki “obuvayut” promyshlennikov. A u vas kakaya kollektsiya PPO? O problemakh tsifrovoy transformatsii na primere sistem upravleniya proizvodstvom i promyshlennogo programmnogo obespecheniya (PPO) [How IT Professionals “Shoe” Industrialists. What’s Your Software Collection Like? On the Challenges of Digital Transformation Using Production Management Systems and Industrial Software (IS) as Examples]. OOO “GiperGrafGrupp”, 2022, available at: https://www.gipergraf.ru/kak-ajtishniki-obuvayut-promyshlenniko

DOI: 10.33917/es-6.204.2025.26-33

Conceptual approaches to modeling trends in information technology are discussed. It is shown that modeling IT trends solely based on technology interest data, such as Gartner’s Hype Cycle, is insufficient to predict the emergence of new technologies. Various IT examples demonstrate the need to analyze the connections between technologies, as success in some areas of economic digitalization creates the conditions for technological development in others. Furthermore, due to the high knowledge intensity of information technology, the depth of fundamental and applied scientific research must be taken into account. When modeling trends, the demand for technologies in specific economic sectors must also be considered. Simulations based on empirical data must identify simple and explainable relationships, and high-quality predictions must be achieved by synthesizing all the relationships of the technology under study. The proposed conceptual approach can also be applied to modeling other socioeconomic processes based on the synthesis of empirical data.

References:

1. Almalawi A., Soh B., Li A., Samra H. Predictive Models for Educational Purposes. A Systematic Review. Big Data Cogn. Comput., 2024, no 8, pp. 187, DOI: https://doi.org/10.3390/ bdcc8120187

2. Hassan M., Awan F.M., Naz A., Andrés-Galiana, de E.J., Alvarez O., Cernea A.; Fernández-Brillet L., Fernández-Martínez J.L., Kloczkowski A. Innovations in Genomics and Big Data Analytics for Personalized Medicine and Health Care. A Review. Int. J. Mol. Sci., 2022, no 23, 4645, DOI: https://doi.org/10.3390/ ijms23094645

3. Ribeiro F.L., Rybski D. Mathematical models to explain the origin of urban scaling laws. Physics Reports, 2023, vol. 1012, 23 April, pp. 1–39.

4. Mokhov V., Aliukov S., Alabugin A., Osintsev K. A Review of Mathematical Models of Macroeconomics, Microeconomics, and Government Regulation of the Economy. Mathematics, 2023, no 11, 3246, DOI: https://doi.org/10.3390/ math11143246

5. Helbing D. Pluralistic Modeling of Complex System. Science and Culture, 2010, vol. 76, no 9/10, pp. 399–417.

6. Zhu Z., Xie H., Chen L. ICT industry innovation: Knowledge structure and research agenda. Technological Forecasting and Social Change, 2023, vol. 189, 122361.

7. Kleyner G.B. Dokazatel’noe modelirovanie kak perspektivnyy instrument nauchnogo issledovaniya sotsial’no-ekonomicheskikh protsessov [Evidence-based Modeling as a Promising Tool for Scientific Research of Socio-economic Processes]. Ekonomika i upravlenie: problemy, resheniya, 2023, no 6, vol. 2, pp. 5–16, DOI: https://doi.org/10.36871/ek.up.p.r.2023.06.02.001

8. O’Leary D.E. Gartner’s hype cycle and information system research issues. International Journal of Accounting Information Systems, 2008, no 9, pp. 240–252.

9. Chen X., Han T. Disruptive Technology Forecasting based on Gartner Hype Cycle. 2019 IEEE Technology & Engineering Management Conference (TEMSCON), Atlanta, GA, USA, 2019, pp. 1–6, DOI: 10.1109/TEMSCON.2019.8813649.

DOI: 10.33917/es-6.204.2025.134-143

The article proposes to examine a preliminary version of a program for improving methodological tools for increasing the level of objectivity when making decisions on classifying or declassifying information. The program consists of several stages, which include: conducting preliminary work, including collecting information and solving specially formulated problems, solution of which would facilitate the implementation of these stages; collecting additional information and solving the assigned problems; analyzing the information received and solving the problems that arise; ensuring ongoing monitoring of the implementation effectiveness of the proposed program. A total of 32 such problems are formulated. Furthermore, the authors discuss ways to improve methodological principles and methodological tools in this area. In conclusion, the authors present a plan for future research in the above area.

References:

1. Sagan C. The Demon-Haunted World: Science as a Candle in the Dark. Ballantine Book. New York, 1996, 457 p.

2. Zakon Rossiyskoy Federatsii ot 21.07.93 N 5485-1 “O gosudarstvennoy tayne” (v red. federal’nykh zakonov ot 06.10.97 N 131-FZ, ot 30.06.2003 N 86-FZ, ot 11.11.2003 N 153-FZ, ot 29.06.2004 N 58-FZ, ot 22.08.2004 N 122-FZ, ot 01.12.2007 N 294-FZ, ot 01.12.2007 N 318-FZ, ot 18.07.2009 N 180-FZ, ot 15.11.2010 N 299-FZ, ot 18.07.2011 N 242-FZ, ot 19.07.2011 N 248-FZ, ot 08.11.2011 N 309-FZ, ot 21.12.2013 N 377-FZ, ot 08.03.2015 N 23-FZ, ot 26.07.2017 N 193-FZ, ot 29.07.2018 N 256-FZ, ot 30.12.2020 N 481-FZ, ot 09.03.2021 N 39-FZ, ot 11.06.2021 N 170-FZ, ot 14.07.2022 N 292-FZ, ot 04.08.2022 N 359-FZ, ot 05.12.2022 N 498-FZ, ot 04.08.2023 N 432-FZ, ot 08.08.2024 N 249-FZ) [Law of the Russian Federation of 21.07.93 No. 5485-1 “On State Secrets” (as amended by federal laws of 06.10.97 No. 131-FZ, of 30.06.2003 No. 86-FZ, of 11.11.2003 No. 153-FZ, of 29.06.2004 No. 58-FZ, of 22.08.2004 No. 122-FZ, of 01.12.2007 No. 294-FZ, of 01.12.2007 No. 318-FZ, of 18.07.2009 No. 180-FZ, of 15.11.2010 No. 299-FZ, dated 18.07.2011 No. 242-FZ, dated 19.07.2011 No. 248-FZ, of 08.11.2011 No. 309-FZ, of 21.12.2013 No. 377-FZ, of 08.03.2015 No. 23-FZ, of 26.07.2017 No. 193-FZ, of 29.07.2018 No. 256-FZ, of 30.12.2020 No. 481-FZ, of 09.03.2021 No. 39-FZ, of 11.06.2021 No. 170-FZ, of 14.07.2022 No. 292-FZ, of 04.08.2022 No. 359-FZ, of 05.12.2022 No. 498-FZ, dated 04.08.2023 No. 432-FZ, dated 08.08.2024 No. 249-FZ)]. Konsul’tantPlyus, available at: https://www.consultant.ru/document/cons_doc_LAW_2481/

3. Veryutin V.N. Otdel’nye aspekty zashchity gosudarstvennoy tayny v Rossiyskoy Federatsii [Certain Aspects of the Protection of State Secrets in the Russian Federation]. Vestnik Voronezhskogo instituta MVD Rossii, 2009, no 2, pp. 17–22.

4. Kotov M.A., Kravchenko A.Yu., Chervonenko V.Yu. Ob opredelenii ekonomicheskogo ushcherba bezopasnosti gosudarstva vsledstvie nesanktsionirovannogo raskrytiya svedeniy, sostavlyayushchikh gosudarstvennuyu taynu v VS RF [On the Determination of Economic Damage to State Security Due to the Unauthorized Disclosure of Information Constituting a State Secret in the RF Armed Forces]. Voennaya mysl’, 2009, no 6, pp. 21–26.

DOI: 10.33917/es-6.204.2025.34-41

The article focuses on three key issues that play a special role in studying and regulating the development of the “big data” digital technology: 1) the content and characteristics of big data as a digital technology both as large volumes of information, which predetermine methodological approaches to studying the trajectories of their development, as well as their legal basis, 2) global trends and challenges of transitioning to a data-driven economy; 3) analysis and assessment of Russian trends in the global landscape.

References:

1. Big Data. Definition. Gartner, available at https://www.gartner.com/en/information-technology/glossary/big-data

2. Gaponenko N.V. Tsifrovye tekhnologii za granitsami khaypa: global’nyy landshaft [Digital Technologies Beyond Hype: The Global Landscape]. Ekonomicheskie strategii, 2022, no 6, pp. 104–110, DOI: https://doi.org/10.33917/es-6.186.2022.104-110

3. Going Digital: Shaping Policies, Improving Lives. Paris: OECD Publishing, 2019.

4. Navin Kumar. Statistika bol’shikh dannykh za 2025 god (dannye o roste i rynke) [Big Data Statistics 2025 (Growth and Market Data)]. DemandSage, 2025, 24 iyunya, available at: https://www.demandsage.com/big-data-statistics/

5. Data and AI Leadership Executive Survey. Wavestone, 2024.

6. Data, BI and Analytics Trend. BARC, 2025.

7. Bol’shie dannye: vygodnoe prilozhenie ili dorogostoyashchiy eksperiment? [Big Data: Profitable Application or Expensive Experiment?]. K2 Cloud i Arenadata, 2025.

8. Gotovnost’ rossiyskogo biznesa k ekonomike dannykh: Monitoring tsifrovoy transformatsii biznesa [Readiness of Russian Business for the Data Economy: Monitoring Digital Transformation of Business]. Vyp. 2. Moscow, NIU VShE, 2023.

DOI: 10.33917/es-6.204.2025.42-49

The objective criterion of management are not ratings and assessments, but results. Since “any modeling is carried out by humans and for humans” [1], we are talking about increasing the quality of people’s life in the relevant public legal entity (hereinafter PLE), including their safety, and about profits of the relevant corporations. For this, an information model of power is important, and it is important for managers to move from thinking in words to thinking in equations [1]. “Less pompous phrases, more simple everyday work and concern for a pood of bread and a pood of coal” [2].

References:

1. Glushkov V.M. Kibernetika. Voprosy truda i praktika [Cybernetics: Issues of Work and Practice]. Moscow, Nauka, 1986. 488 s.

2. Lenin V.I. Polnoe sobranie sochineniy [Complete works]. Vol. 39. Moscow, Izd-vo politicheskoy literatury, 1972, p. 23.

3. Shumpeter Y. Teoriya ekonomicheskogo razvitiya: Issledovanie predprinimatel’skoy pribyli, kapitala, kredita, protsenta i tsikla kon”yunktury [Theory of Economic Development: An Investigation of Entrepreneurial Profit, Capital, Credit, Interest, and the Business Cycle]. Moscow, URSS, 2024, 400 p.

4. Lange O. Vvedenie v ekonomicheskuyu kibernetiku [Introduction to Economic Cybernetics]. Moscow, Progress, 1968, 207 p.

5. Vanchurin V., Wolf Yu.I., Katsnelson M.I., Kooni E.V. Toward a theory of evolution as multilevel learning. PNAS, February 4, 2022, DOI: https://doi.org/10.1073/pnas.2120037119

6. Bychkova N.Yu., Kiselev V.G. Ustoychivoe razvitie upravlyaemoy sistemy kak rezul’tat evolyutsii upravlencheskogo kapitala [Sustainable Development of a Managed System as a Result of the Evolution of Management Capital]. Innovatsii i investitsii, 2025, no 7, pp. 180–184, DOI: 10.24412/2307-180X-2025-7-180-184

7. Glaz’ev S.Yu. Za gorizontom kontsa istorii [Beyond the Horizon of the End of History]. Moscow, Prospekt, 2021, 416 p.

8. Gusakov V.G. Doklad na Mezhdunarodnoy nauchno-prakticheskoy konferentsii “Strategiya razvitiya ekonomiki Belarusi: vyzovy, instrumenty realizatsii i perspektivy”, 16 noyabrya 2023 g. [Presentation at the International Scientific and Practical Conference «Strategy for the Development of the Belarusian Economy: Challenges, Implementation Tools, and Prospects,» November 16, 2023], available at: https://youtu.be/tDQ5x6v1t-0

9. Bychkova N.Yu. Soznanie kak ekonomicheskaya kategoriya [Consciousness as an Economic Category]. Innovatsii i investitsii, 2022, no 12, pp. 22–29, DOI: 10.24412/2307-180X-2022-12-22-29

10. Zhukov N.I. Filosofskie osnovy kibernetiki [Philosophical Foundations of Cybernetics]. Minsk, Izd-vo BGU, 1976, 224 p.

11. Druker P.F. Effektivnyy rukovoditel’ [Effective Leader]. Moscow, Mann, Ivanov i Ferber (MIF), 2012, 240 p.

12. Bychkova N.Yu. Samodostatochnost’ cheloveka kak osnova samodostatochnosti sotsial’no-ekonomicheskikh sistem i mnogopolyarnogo mira [Human Self-Sufficiency as the Basis for Self-Sufficiency of Socio-Economic Systems and a Multipolar World]. Ekonomicheskie strategii, 2024, no 1(193), pp. 93–99, DOI: 10.33917/es-1.193.2024.93-99

DOI: 10.33917/es-6.204.2025.50-55

The article examines the role of digital factors in enhancing labor productivity as one of the key elements of technological and economic development. Using the example of the Kyrgyz Republic, it demonstrates that the implementation of digital technologies and the development of digital infrastructure contribute to improving efficiency; however, without the simultaneous modernization of fixed assets and the training of qualified personnel, the effect of digitalization remains limited. The article also proposes the creation of an integrated model of digital factors influencing labor productivity at the macro, meso, and micro levels, which would enable a more comprehensive assessment and management of digital transformation processes.

References:

1. Telyatnikova T.V., Kipervar E.A., Trunkina L.V. Vyyavlenie faktorov, vliyayushchikh na uroven’ proizvoditel’nosti truda, kak osnova formirovaniya ustoychivogo razvitiya predpriyatiya [Identifying Factors Influencing Labor Productivity as a Basis for the Formation of Sustainable Enterprise Development]. Ekonomika truda, 2024, vol. 11, no 3, pp. 361–374, DOI 10.18334/et.11.3.120672

2. Mkrtychan Z.V. Klassifikatsiya faktorov, okazyvayushchikh vliyanie na proizvoditel’nost’ truda [Classification of Factors Influencing Labor Productivity]. Sibirskaya finansovaya shkola, 2020, no 3(139), pp. 23–30.

3. Kontseptsiya tsifrovoy transformatsii Kyrgyzskoy Respubliki na 2024–2028 gody [Concept of Digital Transformation of the Kyrgyz Republic for 2024– 2028]. Ministerstvo yustitsii KR, available at: https://cbd.minjust.gov.kg/30-164/edition/6414/ru?ysclid=mgi8iwipwl116850581

4. Tsifrovoy kodeks Kyrgyzskoy Respubliki ot 31 iyulya 2025 g. N 178 [Digital Code of the Kyrgyz Republic of July 31, 2025, No. 178]. Ministerstvo yustitsii KR, available at: https://cbd.minjust.gov.kg/3-48/edition/35412/ru

5. Rasporyazhenie Kabineta ministrov KR ot 23 iyulya 2024 g. N 4 [Order of the Cabinet of Ministers of the Kyrgyz Republic dated July 23, 2024 No. 4]. Ministerstvo yustitsii KR, available at: https://cbd.minjust.gov.kg/57-19271/edition/14721/ru?ysclid=mgjn8uo4yg604258729

6. Indeks razvitiya elektronnogo pravitel’stva (srednevzveshennyy): Kirgiziya: Po dannym OON [E-Government Development Index (weighted average): Kyrgyzstan: According to UN data]. Statbase, available at: https://statbase.ru/data/kgz-e-government-development-index/

7. Tsifrovizatsiya v Kyrgyzstane: byudzhet v 600 mln somov na 2024 god [Digitalization in Kyrgyzstan: A 600 Million Som Budget for 2024]. News KG, available at: https://news.kg/2024/04/03/cifrovizacija-v-kyrgyzstane-bjudzhet-v-600/

8. Kyrgyzstan v tsifrakh — 2025: Natsional’nyy statisticheskiy komitet [Kyrgyzstan in Figures — 2025: National Statistical Committee], available at: https:// stat.gov.kg/media/publicationarchive/4943edd9-da6d-4075-88f9-8b667e64c8cb.pdf

9. Brovko N.A., Borisenko N.A. Ekonomicheskiy rost v Kyrgyzskoy Respublike cherez prizmu proizvoditel’nosti truda [Economic Growth in the Kyrgyz Republic through the Prism of Labor Productivity]. Ufimskiy gumanitarnyy nauchnyy forum, 2023, no 4(16), pp. 40–55.

DOI: 10.33917/es-6.204.2025.56-63

The article presents the author’s approach to technological sovereignty based on data from the international assessment, conducted by the UN. The author proposes a concept for representing technological sovereignty in the form of three components (structural elements): information and communication security (digital security), infrastructural (logistics) security and scientific-technological security. To assess each component of technological sovereignty it is proposed to use the corresponding indicators, grouped in accordance with the author’s approach. In addition, the article provides the author’s analysis of countries that have achieved Goal 9 of the Sustainable Development based on statistical data, provided by the UN, and the corresponding threshold values for each indicator of the countries under consideration.

References:

1. Potaptseva E.V., Akberdina V.V. Tekhnologicheskiy suverenitet: ponyatie, soderzhanie i formy realizatsii [Technological Sovereignty: Concept, Content and Forms of Implementation]. Vestnik Volgogradskogo gosudarstvennogo universiteta. Ekonomika, 2023, vol. 25, no 3, pp. 5–16.

2. Strategiya nauchno-tekhnologicheskogo razvitiya Soyuznogo gosudarstva na period do 2035 goda [Strategy for Scientific and Technological Development of the Union State for the Period up to 2035]. Informatsionno-analiticheskiy portal Soyuznogo gosudarstva. 2024. 31 yanvarya, available at: https://soyuz.by/projects/dekrety-vysshego-gosudarstvennogo-soveta-soyuznogo-gosudarstva/postanovlenie-ot-29-yanvarya-2024-g-2-o-strategii-nauchno-tehnologicheskogo-razvitiya-soyuznogo-gosudarstva-na-period-do-2035-goda

3. Tseli v oblasti ustoychivogo razvitiya [Sustainable Development Goals]. OON. Tseli v oblasti ustoychivogo razvitiya, available at: https://www.un.org/ sustainabledevelopment/ru/infrastructure-industrialization/#tab-a971aadac89bd5b8b3a

4. The SDGS in action. UNDP, available at: https://www.undp.org/sustainable-development-goals

5. Sustainable development report 2019, available at: https://s3.amazonaws.com/sustainabledevelopment.report/2019/2019_sustainable_development_ report.pdf

6. Sustainable development report 2020, available at: https://s3.amazonaws.com/sustainabledevelopment.report/2020/2020_sustainable_development_ report.pdf

7. Sustainable development report 2021, available at: https://s3.amazonaws.com/sustainabledevelopment.report/2021/2021-sustainable-development-report.pdf

8. Sustainable development report 2022, available at: https://s3.amazonaws.com/sustainabledevelopment.report/2022/2022-sustainable-development-report.pdf

9. Sustainable development report 2023, available at: https://s3.amazonaws.com/sustainabledevelopment.report/2023/sustainable-development-report-2023.pdf

10. Sustainable development report 2024, available at: https://s3.amazonaws.com/sustainabledevelopment.report/2024/sustainable-development-report-2024.pdf