Challenges of the artificial intelligence economy to the traditional labor market

Capa

Citar

Texto integral

Acesso aberto Acesso aberto
Acesso é fechado Acesso está concedido
Acesso é fechado Acesso é pago ou somente para assinantes

Resumo

This article is devoted to the impact of artificial intelligence technology on the modern labor market. The authors focus on the economic consequences of the artificial intelligence application for enterprises, individual employees, and national economies. In the article, progress in the applying innovations in the national economy is associated with the growth of labor productivity and business profitability. The authors substantiate the necessity of Russiaʼs transition from the inertial path of development to the innovative one based on artificial intelligence and robotics. Catalysts for this transition are being identified. In the article, the impact of innovations and, above all, artificial intelligence technology on a modern worker is divided into innovations that replace a person and innovations that improve human capabilities. The formation of three fundamentally different groups of personnel is singled out in terms of the consequences of the impact of artificial intelligence technology. The authors analyze the results of the artificial intelligence application in the labor market according to the criteria of age, level of education, and the nature of the tasks they perform. The article identifies barriers, both economic and technological ones, for the optimal application of artificial intelligence in the labor market.

Sobre autores

Pavel Lukichyov

Baltic State Technical University «VOENMEH» named after D.F. Ustinov

Email: loukitchev20@mail.ru

Oleg Chekmarev

Saint-Petersburg State Agrarian University

Email: oleg1412@mail.ru

Bibliografia

  1. Мониторинг инновационной активности субъектов инновационного процесса. Исиэз ниу вшэ. [Электронный ресурс]. URL: https://issek.hse.ru/transfer_in_STI (дата обращения: 09.04.2023).
  2. Pew Research Center. AI in Hiring and Evaluating Workers: What Americans Think. - 2023
  3. Pan Y., Froese F.J. An interdisciplinary review of AI and HRM: Challenges and future directions // Human Resource Management Review. – 2022. – № 1. – p. 100924. – doi: 10.1016/j.hrmr.2022.100924.
  4. Tinbergen J. Substitution of Graduate Labor by Othe // Kyklos. – 1974. – № 2. – p. 217-226.
  5. Katz L.F., Murphy K.M. Changes in relative wages, 1963–1987: supply and demand factors // Quarterly Journal of Economics. – 1992. – № 1. – p. 35-78.
  6. Summers L.H. The age of secular stagnation: What it is and what to do about it // Foreign Affairs. – 2016. – № 2. – p. 2-9.
  7. Gordon R.J. The Rise and Fall of American Growth. - Princeton, NJ: Princeton University Press, 2016.
  8. Wike R., Stokes B. In advanced and emerging economies alike, worries about job automation. Pew Research Center, Global Attitudes Trends. [Электронный ресурс]. URL: https://www.pewresearch.org/global/2018/09/13/in-advanced-and-emerging-economies-alike-worries-about-job-automation/.
  9. Autor D. The labor market impacts of technological change: From unbridled enthusiasm to qualified optimism to vast uncertainty // National Bureau of Economic Research. – 2022. – doi: 10.3386/w30074.
  10. Graetz G., Restrepo P., Skans O.N. Technology and the labor market // Labour Economics. – 2022. – p. 102177. – doi: 10.1016/j.labeco.2022.102177.
  11. Watanabe C., Naveed K., Tou Y., Neittaanmäki P. Measuring GDP in the digital economy: Increasing dependence on uncaptured GDP // Technological Forecasting and Social Change. – 2018. – p. 226-240. – doi: 10.1016/j.techfore.2018.07.053.
  12. Караева Е. Н., Пьянова Н.В., Голоктионова Ю.Г. Производительность труда в российской экономике // Вестник ОрелГИЭТ. – 2020. – № 2(52). – c. 163-170. – doi: 10.36683/2076-5347-2020-2-52-163-170.
  13. Инвестиции в науку повышают экономическую эффективность бизнеса. Исиэп ниу вшэ. [Электронный ресурс]. URL: https://issek.hse.ru/news/828948590.html?ysclid=lhyu2y7ugb991665715 (дата обращения: 21.04.2023).
  14. Лукичев П.М. Позиция России в новом международном разделении труда // Вестник Удмуртского университета. Серия Экономика и право. – 2022. – № 5. – c. 817-828. – doi: 10.35634/2412-9593-2022-32-5-817-828.
  15. The Global Human Capital Report 2017. World Economic Forum. [Электронный ресурс]. URL: https://www.weforum.org/reports/the-global-human-capital-report-2017 (дата обращения: 09.04.2023).
  16. Eloundou T., Manning S., Mishkin P., Rock D. Gpts are gpts: An early look at the labor market impact potential of large language models. Arxiv.org. [Электронный ресурс]. URL: https://arxiv.org/pdf/2303.10130.pdf.
  17. Trajtenberg M. Artificial intelligence as the next GPT: A political-economy perspective. / The economics of artificial intelligence: An agenda., 2018. – 175-186 p.
  18. Jesuthasan R., Boudreau J.W. Work without Jobs. How to Reboot Your Organization’s Work Operating System. - Cambridge, MA: The MIT Press, 2023. – 232 p.
  19. Alekseeva L., Azar J., Gine M., Samila S., Taska B. The demand for AI skills in the labor market // Labour Economics. – 20021. – p. 102002. – doi: 10.1016/j.labeco.2021.102002.
  20. Beane M., Brynjolfsson E. Working with Robots in a Post-Pandemic World // MIT Sloan Management Review. – 2020. – № 1. – p. 1-5.
  21. Bresnahan T., Gordon R. J. “Introduction,” The Economics of New Goods. - Chicago: University of Chicago Press, 1996.
  22. Autor D., Chin C., Salomons A.M., Seegmiller B. New Frontiers: The Origins and Content of New Work, 1940–2018 // National Bureau of Economic Research. – 2022. – doi: 10.3386/w30389.
  23. Brynjolfsson E. The Turing Trap: The Promise Peril of Human-Like Artificial Intelligence // Daedalus. – 2022. – № 2. – p. 272-287. – doi: 10.1162/daed_a_01915.
  24. Goldfarb A., Taska B., Teodoridis F. Could machine learning be a general purpose technology? a comparison of emerging technologies using data from online job postings // Research Policy. – 2023. – № 1. – p. 104653. – doi: 10.1016 /j.respol.2022.104653.
  25. Moulaï K., Islam G., Manning S., Terlinden L. «All too human» or the emergence of a techno-induced feeling of being less-able: identity work, ableism and new service technologies // International Journal of Human Resource Management. – 2022. – № 22. – p. 4499-4531. – doi: 10.1080/09585192.2022.2066982.
  26. Blien U., Dauth W., Roth D.H. Occupational routine intensity and the costs of job loss: evidence from mass layoffs // Labour Economics. – 2021. – p. 101953. – doi: 10.1016/j.labeco.2020.101953.
  27. Brynjolfsson E., Frank M. R., Mitchell T., Rahwan I., Rock D. Quantifying the Distribution of Machine Learning’s Impact on Work. Forthcoming. - 2023
  28. Pritchett L. The Global Economy Needs Immigration Before Automation // Foreign Affairs. – 2023.
  29. Rust R.T., Huang M.H. The feeling economy: How artificial intelligence is creating the era of empathy. - Cham, Switzerland: Palgrave Macmillan, 2021. – 179 p.
  30. Webb M. The impact of artificial intelligence on the labor market // Ssrn. – 2019. – p. 61. – doi: 10.2139/ssrn.3482150.
  31. Where are all the robots? The Economist. - 2023
  32. Artificial Intelligence (AI) Market. Nextmsc.com. [Электронный ресурс]. URL: https://www.nextmsc.com/report/artificial-intelligence-market (дата обращения: 15.04.2023).
  33. Лукичёв П.М., Чекмарев О.П. Применение искусственного интеллекта в системе высшего образования // Вопросы инновационной экономики. – 2023. – № 1. – c. 485-502. – doi: 10.18334/vinec.13.1.117223.

Arquivos suplementares

Arquivos suplementares
Ação
1. JATS XML

Declaração de direitos autorais © Lukichyov P.M., Chekmarev O.P., 2023

Este site utiliza cookies

Ao continuar usando nosso site, você concorda com o procedimento de cookies que mantêm o site funcionando normalmente.

Informação sobre cookies