DOI: 10.33917/es-2.188.2023.24–35

The article discusses the scheme of K. Marxian expanded reproduction through the prism of the capital accumulation analysis by R. Luxembourg taking into account of the infrastructure impact on the development of capitalism.

The author gives examples of the 21st century infrastructure, in par ticular he examines multilateral platforms — payment systems for cross-border payments, associated with broadband satellite Internet access and an ar tificial intelligence environment.

References:

1. Kuznetsova A.I. Infrastruktura: voprosy teorii, metodologii i prikladnye aspekty sovremennogo infrastrukturnogo obustroistva. Geoekonomicheskii podkhod [Infrastructure: Issues of Theory, Methodology and Applied Aspects of Modern Infrastructure Development. Geoeconomic Approach]. Moscow, KomKniga, 2006, 456 p.

2. Novoselov A.S. Regional’nye rynki [Regional Markets]. Moscow, TERRA, 1999, 476 p.

3. Samuel’son P., Nordkhaus V.M. Ekonomika [Economy]. Moscow, Vil’yams, 2001, 688 p.

4. Buzgalin A.V., Kolganov A.I. Global’nyi capital [Global Capital]. Moscow, Editorial URSS, 2004, 512 p.

5. Vazyulin V.A. Logika “Kapitala” K. Marksa [The Logic of K. Marx’s “Capital”]. 2-e izd. Moscow, Sovremennyi gumanitarnyi universitet, 2002, 392 p.

6. Gegel’ G.V.F. Nauka logiki [The Science of Logic]. Saint Petersburg, Nauka, 2005, 799 p.

7. Marks K. Kapital [Capital]. T. I–III. Moscow, Politizdat, 1978, 629 p.

8. Lyuksemburg R. Nakoplenie kapitala [The Accumulation of Capital]. 5-e izd. Moscow — Leningrad, Gos. Sotsial’no-ekonomicheskoe izdatel’stvo, 1934, 478 p.

9. Organizatsiya ekonomicheskogo sotrudnichestva i razvitiya, M3 dlya SShA [Organization for Economic Co-operation and Development, M3 for the United States]. FRED, Federal’nyi rezervnyi bank Sent-Luisa, available at: https://fred.stlouisfed.org/series/MABMM301USM189S.

10. Zaidenvarg V.E., Podolyak V.I., Saraev V.N. Osnovy upravleniya krizisami na rynkakh uglya, gaza i elektroenergii [Fundamentals of Crisis Management in the Coal, Gas and Electricity Markets]. Moscow, Institut ekonomicheskikh strategii, 2003, 192 p.

11. Malkov S.Yu. Sotsial’naya samoorganizatsiya i istoricheskii protsess: Vozmozhnosti matematicheskogo modelirovaniya [Social Self-Organization and the Historical Process: Possibilities of Mathematical Modeling]. Moscow, Knizhnyi dom “LIBROKOM”, 2009, 240 p.

12. Interlinking payment systems and the role of application programming interfaces: a framework for cross-border payments. Basel, Switzerland, Bank for International Settlements, Committee on Payments and Market Infrastructures (CPMI). Report to the G20, 2022, July, 53 p.

13. Exploring multilateral platforms for cross-border payments. Basel, Switzerland, Bank for International Settlements, 2023, January, 33 p.

DOI: https://doi.org/10.33917/es-6.186.2022.104-110

The paper discusses three key issues that play a special role in the development of strategies and policies for digital technologies: 1) particularities of digital technologies that greatly influence the principles and methodological approaches to the development of strategic documents, 2) drivers, main players and trends of global market, 3) trends in the accumulation of a technological knowledge base to provide competitive advantages to national companies in the short and medium term.

References:

1. Gaponenko N.V., Glenn J.C. Technology Industry 4.0: Problems of Labor, Employment and Unemployment. Studies on Russian Economic Development, 2020, vol. 31, no 3, pp. 271–276.

2. Gaponenko N.V. Teoreticheskie i metodologicheskie osnovy issledovaniya innovatsionnykh sistem i formirovaniya tekhnologicheskikh prioritetov ikh razvitiya v ekonomike, osnovannoi na znaniyakh [Theoretical and Methodological Foundations for Studying Innovative Systems and Forming Technological Priorities of their Development in the Knowledge-Based Economy]. Moscow, IPRAN RAN, 2020, 151 p.

3. Gaponenko N.V. Zakonomernosti i osobennosti evolyutsii sektoral’nykh innovatsionnykh sistem v ramkakh dolgosrochnogo tsikla [Regularities and Evolution Features of Sectoral Innovation Systems within the Long-Term Cycle]. Systems and Management, 2020, no 1, pp. 44–67.

4. Gaponenko N.V. Sektoral’nye innovatsionnye sistemy v ekonomike, osnovannoi na znaniyakh [Sectoral Innovation Systems in the Knowledge-Based Economy]. Moscow, IPRAN RAN, 2021, 264 p.

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

6. IT Industry Outlook 2021. CompTIA, 2020.

7. Gaponenko N.V. Global’nye vyzovy v formirovanii politsentrichnogo mirovogo poryadka: traektorii retro i traektorii budushchego [Global Challenges in Formation of a Polycentric World Order: Retro Trajectories and Trajectories of the Future]. Ekonomicheskie strategii, 2020, vol. 22, no 1(167), pp. 28–35, DOI: https://doi.org/10.33917/es-1.167.2020.28-35/

8. Positive 5G Outlook Post COVID-19: What Does It Mean for Avid Gamers? Forest Interactive, 2020.

DOI: https://doi.org/10.33917/es-2.182.2022.20-31

Artificial intelligence systems (AI) are rapidly becoming a competitive tool, an important factor in improving the efficiency of socioeconomic reproduction, and even an attribute of the development of human civilization, the core of global and national development projects. Comparative assessments of the degree of development of AIS have also become a tool for influencing the economic strategies of states and companies and supporting their implementation. Determining a country’s place in the global “table of ranks” makes it possible not only to clarify its real status in global competition in AIS but also to identify unaccounted for elements to increase the effectiveness of government initiatives in the field of AIS development

Источники:

1. Glava VEF zayavil, chto kovid sleduet rassmatrivat’ kak dolgosrochnyi vyzov dlya chelovechestva [The Head of the WEF Said That Covid Should be Seen as a Long-Term Challenge for Humanity]. TASS, available at: https://tass.ru/obschestvo/13273357.

2. Krichevskii G.E. NBIKS-tekhnologii dlya Mira i Voiny [NBICS Technologies for Peace and War]. Saarbryukken, Germaniya, Lambert, 2017, 634 p.

3. Ovchinnikov V.V. Doroga v mir iskusstvennogo intellekta [Road to the World of Artificial Intelligence]. Moscow, Institut ekonomicheskikh strategii, RUBIN, 2017, 536 p. (Ceriya: Strategicheskaya analitika)

4. Gonka za tsifrovym prizrakom [Chasing the Digital Ghost]. Kommersant, 2019, June, 24, available at: https://www.kommersant.ru/doc/4003879.

5. Kalyaev I.A. Iskusstvennyi intellekt: kamo gryadeshi? [Artificial Intelligence: Whither Goest Thou?]. Ekonomicheskie strategii, 2019, no 5, pp. 6–15, available at: DOI: https://doi.org/10.33917/es-5.163.2019.6-15.

6. Markoff J. A learning advance in artificial intelligence rivals human abilities. The New York Times, 2015, available at: https://www.nytimes.com/2015/12/11/science/an-advance-in-artificial-intelligence-rivals-human-vision-abilities.html.

7. Ageev A.I., Loginov E.L., Shkuta A.A. Kitai kak neiroinformatsionnaya megamatritsa: tsifrovye tekhnologii strukturirovaniya kognitivnykh ansamblei poryadka [China as a Neural-Information Megamatrix: Digital Technologies for Structuring Cognitive Ensembles of Order]. Ekonomicheskie strategii, 2021, no 1, pp. 50–61, available at: DOI: https://doi.org/10.33917/es-1.175.2021.50-61.

8. European approach to artificial intelligence. European Commission, available at: https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificialintelligence.

9. Proposal for a Regulation of the European parliament and of the Council laying down harmonised rules on artificial intelligence (artificial intelligence act) and amending certain union legislative acts. EUR-lex, available at: https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1623335154975&uri=CELEX%3A52021PC0206.

10. Artificial Intelligence: A European Perspective. European Commission. URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC113826.

DOI: 10.33917/mic-5.100.2021.87-102

The article deals with a description and analysis of the policy of modernization of the healthcare sector implemented by the Japanese government on the basis of artificial technology, provides particular examples of some research projects and cases of practical application of the described technologies, identifies problem areas of the policy being implemented and projects being developed.

Modernization of the healthcare sector and medical services based on using of the latest digital technologies, in particular, artificial intelligence technology, is one of the key current global trends. In Russia, the digital transformation of healthcare is defined as one of the key tasks and is carried out within the framework of the National Project «Healthcare».

The study of successful examples of the introduction of artificial intelligence technology, as well as problems that hinder or slow down the integration of this technology and ways to overcome them, can be a valuable lesson for countries also involved in the development of national strategies for the development of artificial intelligence.

DOI: 10.33917/es-7.173.2020.118-124

In the modern world, introduction of technologies with the elements of artificial intelligence into all spheres of life is developing rapidly, significantly ahead of the development of legislation. In this regard, the problem of determining liability for the harm caused by the use of such technologies arises. The problem can be solved by creating a comprehensive strategy for the development of the legal field in this area and bringing the current legislation to the level of information-oriented Society 5.0, the concept of which assumes technical breakthrough in the field of cyber technologies. The aim of this research is to analyze current situation in the field of legal regulation of liability for the harm caused by technologies with the elements of artificial intelligence and to determine the strategy for the formation of legal framework in this field. In the first part of the article the analysis of the current legal situation on the basis of scientific developments in this area is carried out, as well as the solutions proposed by the strategy for the development of artificial intelligence technologies as the basis for the formation of the legal framework are shown. The second part of the article is devoted to the strategy of a legal framework formation in the field of determining responsibility for the use of technologies with the elements of artificial intelligence. In conclusion it is said that the strategy under consideration can be realized by developing a set of measures aimed at implementing the provisions that define responsibility for the use of technologies with elements of artificial intelligence into current legislation.

DOI: 10.33917/es-6.172.2020.46-57

World achievements in the field of neuroscience have provided previously inaccessible opportunities for creating fundamentally new control systems based on neurointerfaces (brain — computer — brain). Hybridization of environments — gradual blurring of the boundaries between physical, cognitive and digital realities — is taking place. Descriptions of social and cognitive practices of real people are transformed into forming an artificial electronic subject, which becomes more real, replacing a biological object in society (a person is how he is represented in the electronic information environment). At the same time, development of the neurointerface perspectively leads to conversion of nervous tissue and changes biological substrate of the human brain and body in the vector of convergent collaboration of living and artificial nervous systems. Our American competing partners (the US Department of Defence represented by DARPA) carry out multidisciplinary comprehensive research in this area, leading in real results, the US leadership is increasing government funding. A qualitative change in technologies for managing people, society and the state is taking place. Russia’s objective in these conditions is to form its own segment of Neuronet, relying on domestic neurotechnologies, by analogy with the policy of import substitution in Russian nuclear energy.

DOI: 10.33917/es-6.172.2020.58-67

The article considers the classification of Artificial Intelligence (AI) systems. The role of AI has increased significantly recently in all areas of life. The use of AI in public administration, in production, in medicine, in the military, in the social sphere, etc., raised a number of questions related to the definition of AI and classification of AI systems. Classification of AI is necessary to understand the role of AI in the digital economy. Classification becomes important in the context of intensive development of international standards for AI systems and knowledge-based systems (expert, neural, multi-agent, cyber-physical systems and systems based on the industrial Internet)

DOI: 10.33917/es-3.169.2020.134-141

The article dwells on the topic of competition between coal and solar energy as types of fuel. The authors provide a comparison of the installed capacity of a virtual solar power station and an existing coal power station located within the land allotment of a coal mine. The development prospects of the coal industry in terms of thermal coal are shown.

DOI: 10.33917/es-7.165.2019.78-93

The key factor determining success of Trump’s election strategy was the use of cognitive neurophysiology methods — digital identification of a virtual doppelganger of a real voter in information and social networks. Semantization of the states of consciousness and psyche of individuals, being identified in the Global Network, on the basis of computational decisions allows to encapsulate (grab) an integral position that suits most people available for monitoring in order to set the vector of stable convergence of Trump’s election platform and the views of a particular American voter described and analyzed. Identification allows to influence the dominant focus of the emotional-imagination block for remote cognitive correction of the people’s political position in conditions of strategic bifurcation (elections). Russian developments in the field of personality neuro-management are also of great scientific and practical importance

DOI: 10.33917/es-7.165.2019.94-104

The article examines two approaches to formation of a national data management system (NDMS). The first approach is based on applying statistical data for predictive analytics to forecast the future. However, to ensure social progress, a proactive approach is required, aimed at creation of such a NDMS, which can be used to build the future implementing moral values. The authors substantiate that a proactive approach should be based on the principles of economic cybernetics, which allow to develop and introduce proactive artificial intelligence (AI) for improving the economic management efficiency. Its core is a Dynamic Model of Interbranch-Intersectoral Balance (MIIB), representing a system of algorithms for matching end consumers’ orders and manufacturers’ capabilities. The MIIB table, which presents all the relationships of economic agents, defines the architecture of the National Data Management System (NDMS) for the proactive AI functioning