How to Find the “Black Swans” of High-Technology Development: An Indicative Approach
Keywords:
Risks and security threats, principal component analysis, the corridor of acceptable risks, “black swans” of high-tech development, indicative evaluationAbstract
The article presents a mechanism for searching for unexpected, suddenly realized and unavoidable country risks of high-tech development (“black swans” of high-tech development) using an indicative approach to risk analysis; introduces the concept of stepped risk corridors of high-tech development as conventions that establish acceptable risk boundaries. An acceptable corridor of high-tech risks has also been built and its allocation as a test one has been justified. As a result, it is proved that risks become threats, turn into “black swans” for two groups of countries: the leading countries above the corridor, which are characterized by excessively rapid development of high technologies, and the outsider countries below the corridor, in which there is an excessively slow development of high technologies, which leads to vulnerability to external threats of high-tech development. The location of the Russian Federation in this corridor is considered as an example of assessing the country risks of high-tech development using the constructed risk corridor. It is shown that Russia developed in the field of ICT in 2014–2016 faster than average, but at the same time was within the risk corridor. For Russia, excessive acceleration of high-tech development will lead to going beyond the boundaries of the corridor and increasing risks. It would be more reasonable, as argued in the article, to adhere to a strategy of moderate development in order to maintain or somewhat increase the position in the ratings of the basic indices, accompanying technological innovations with a reasonable regulatory policy.
References
Барабашев А.Г., Макаров А.А., Макаров И.А. О совершенствовании индикативных оценок качества государственного управления // Вопросы государственного и муниципального управления. 2019. № 2. С. 7–38.
Зарочинцев С.В. «Упреждающее» государственное управление и оценка рисков национальной безопасности // Вопросы государственного и муниципального управления. 2021. № 3. С. 200–218.
Земцов С., Баринова В., Семёнова Р. Риски цифровизации и адаптация региональных рынков труда в России // Форсайт. 2019. Т. 13. № 2. С. 84–96. DOI: 10.17323/2500-2597.2019.2.84.96
Фомин М.В. Трансиндустриализм — предстоящая социальная реальность // Вопросы философии. 2018. № 1. С. 42–54.
Adams R., Kewell B., Parry G. Blockchain for Good? Digital Ledger Technology and Sustainable Development Goals // Handbook of Sustainability and Social Science Research / ed. by W. L. Filho, R. W. Marans, J. Callewaert. Cham: Springer, 2018. P. 127–140.
Berg J., Cazes S. The Doing Business Indicators: Measurement Issues and Political Implications. Geneva: ILO, 2007.
Besharov D.J., Call D.M. Modern Performance Measurement: Monitoring Program “Outcomes” Instead of “Impacts” // Improving Public Services: International Experiences in Using Evaluation Tools to Measure Program Performance / ed. by D.J. Besharov, K.J. Baehler, J.A. Klerman. Oxford: Oxford University Press, 2017. P. 19–38. DOI: 10.1093/acprof:oso/9780190646059.003.0002
Brockmann D., Helbing D. The Hidden Geometry of Complex, Network-Driven Contagion Phenomena // Science. 2013. Vol. 342. Is. 6164. P. 1337–1342. DOI: 10.1126/science.1245200
Cave J., Marsden C., Klautzer L., Levitt R., Oranje-Nassau C. van, Rabinovich L., Robinson N. Responsibility in the Global Information Society: Towards Multi-Stakeholder Governance. Santa Monica, CA: RAND Corporation, 2007.
Helbing D. Societal, Economic, Ethical and Legal Challenges of the Digital Revolution: From Big Data to Deep Learning, Artificial Intelligence, and Manipulative Technologies // SSRN. 2015. DOI: 10.2139/ssrn.2594352
Helbing D., Bishop S., Conte R., Lukowicz P., McCarthy J.B. FuturICT: Participatory Computing to Understand and Manage Our Complex World in a More Sustainable and Resilient Way // The European Physical Journal Special Topics. 2012. Vol. 214. P. 11–39. DOI: 10.1140/epjst/e2012-01686-y
Henman P. Improving Public Services Using Artificial Intelligence: Possibilities, Pitfalls, Governance // Asia Pacific Journal of Public Administration. 2020. Vol. 42. Is. 4. P. 209–221. DOI: 10.1080/23276665.2020.1816188
Iphofen R., Kritikos M. Regulating Artificial Intelligence and Robotics: Ethics by Design in a Digital Society // Contemporary Social Science. 2021. Vol. 16. Is. 2. P. 170–184. DOI: 10.1080/21582041.2018.1563803
Kaufmann D., Kraay A., Mastruzzi M. The Worldwide Governance Indicators: Methodology and Analytical Issues // Hague Journal on the Rule of Law. 2011. Vol. 3. P. 220–246. DOI: 10.1017/S1876404511200046
Kwet M. Digital Colonialism: US Empire and the New Imperialism in the Global South // Race & Class. 2019. Vol. 60. Is. 4. P. 3–26.
DOI: 10.1177/0306396818823172
Maiti D., Awasthi A. ICT Exposure and the Level of Wellbeing and Progress: A Cross Country Analysis // Social Indicators Research. 2020. Vol. 147. Is. 1. P. 311–343.
Matthess M., Kunkel S. Structural Change and Digitalization in Developing Countries: Conceptually Linking the Two Transformations // Technology in Society. 2020. Vol. 63. DOI: 10.1016/j.techsoc.2020.101428
Mazarr M.J., Bauer R.M., Casey A., Heintz S.A., Matthews L.J. The Emerging Risk of Virtual Societal Warfare: Social Manipulation in a Changing Information Environment. Santa Monica, CA: RAND Corporation, 2019.
Nardo M., Saisana M., Saltelli A., Tarantola S., Hoffman A., Giovanni E. Handbook on Constructing Composite Indicators: Methodology and User Guide. Paris: OECD publishing, 2008.
Nyagadza B., Pashapa R., Chare A., Mazuruse G., Hove P.K. Digital Technologies, Fourth Industrial Revolution (4IR) & Global Value Chains (GVCs) Nexus with Emerging Economies’ Future Industrial Innovation Dynamics // Cogent Economics & Finance. 2022. Vol. 10. Is. 1.
DOI: 10.1080/23322039.2021.2014654
Pagallo U. Cracking Down on Autonomy: Three Challenges to Design in IT Law // Ethics and Information Technology. 2012. Vol. 14. P. 319–328. DOI: 10.1007/s10676-012-9295-9
Paul R. Varieties of Risk Analysis in Public Administrations: Problem-solving and Polity Policies in Europe. London: Routledge, 2021.
DOI: 10.4324/9780429030543
Pollitzer E. Creating a Better Future: Four Scenarios for How Digital Technologies Could Change the World // Journal of International Affairs. 2018. Vol. 72. Is. 1. P. 75–90.
Sahbaz U. Artificial Intelligence and the Risk of New Colonialism // Horizons: Journal of International Relations and Sustainable Development. 2019. Is. 14. P. 58–71.
Skorodumova О.B., Matronina L.F., Koval T.I. Anthropological Risks of the Information Society // Mediterranean Journal of Social Sciences. 2015. Vol. 6. Is. 3, S 3. DOI: 10.5901/mjss.2015.v6n3s3p295
Smith K.P., Christakis N.A. Social Networks and Health // Annual Review of Sociology. 2008. Vol. 34. P. 405–429.
DOI: 10.1146/annurev.soc.34.040507.134601
Southwick L., Guntuku S.C., Klinger E.V., Pelullo A., McCalpin H., Merchant R.M. The Role of Digital Health Technologies in COVID-19 Surveillance and Recovery: A Specific Case of Long Haulers // International Review of Psychiatry. 2021. Vol. 33. Is. 4. P. 412–423.
DOI: 10.1080/09540261.2020.1854195
Zemtsov S. New Technologies, Potential Unemployment and ‘Nescience Economy’ During and after the 2020 Economic Crisis // Regional Science Policy & Practice. 2020. Vol. 12. Is. 4. P.723–743. DOI: 10.1111/rsp3.12286