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Dynamics of labor and capital in AI vs. non-AI industries: A two-industry model analysis

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  • Xu Huang

Abstract

There is an imbalance in the development of artificial intelligence between industries. Compared to non-AI enterprise, AI- enterprise will save labor, enhance innovation capabilities, and improve production efficiency. By constructing a two-industry model of AI and non-AI enterprise, this paper finds that with the development of artificial intelligence in the same industry, the AI enterprise will occupy a dominant position, attracting labor and capital from the non-AI enterprise into the AI enterprise. In different industries, the development of artificial intelligence improves the production efficiency of the enterprise. However, due to the price effect, non-AI enterprise benefits more. Labor and capital flow from AI enterprise to non-AI enterprise. In order to promote the improvement of production efficiency in the whole society, the government can tax non-AI enterprise and subsidize them to AI enterprise. Taxation promotes the degree of automation and the improvement of production efficiency, but it has only a short-term effect on the development of AI. At the same time, taxation inhibits the development of non-AI enterprise, and there is a high risk of unemployment. When both industries use artificial intelligence for production, the labor share and the capital share of the two industries will tend to the same value. The convergence of technology measures is conducive to increasing labor income share and reducing income inequality, but it is not conducive to innovation.

Suggested Citation

  • Xu Huang, 2024. "Dynamics of labor and capital in AI vs. non-AI industries: A two-industry model analysis," PLOS ONE, Public Library of Science, vol. 19(1), pages 1-31, January.
    • Handle: RePEc:plo:pone00:0295150
    DOI: 10.1371/journal.pone.0295150
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    References listed on IDEAS

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    1. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    2. Duch-Brown, Néstor & Gomez-Herrera, Estrella & Mueller-Langer, Frank & Tolan, Songül, 2022. "Market power and artificial intelligence work on online labour markets," Research Policy, Elsevier, vol. 51(3).
    3. David Autor, 2022. "The Labor Market Impacts of Technological Change: From Unbridled Enthusiasm to Qualified Optimism to Vast Uncertainty," NBER Working Papers 30074, National Bureau of Economic Research, Inc.
    4. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    6. Daron Acemoglu & Veronica Guerrieri, 2008. "Capital Deepening and Nonbalanced Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 116(3), pages 467-498, June.
    7. Lankisch, Clemens & Prettner, Klaus & Prskawetz, Alexia, 2019. "How can robots affect wage inequality?," Economic Modelling, Elsevier, vol. 81(C), pages 161-169.
    8. Gasteiger, Emanuel & Prettner, Klaus, 2022. "Automation, Stagnation, And The Implications Of A Robot Tax," Macroeconomic Dynamics, Cambridge University Press, vol. 26(1), pages 218-249, January.
    9. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    10. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    11. Seth G. Benzell & Laurence J. Kotlikoff & Guillermo LaGarda & Jeffrey D. Sachs, 2015. "Robots Are Us: Some Economics of Human Replacement," NBER Working Papers 20941, National Bureau of Economic Research, Inc.
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    1. Shi, Yu & Wu, Tong & Qin, Chuan & Liu, Bailu, 2025. "The value-creating potential of AI: A multi-dimensional analysis of effects and mechanisms," International Review of Financial Analysis, Elsevier, vol. 108(PB).

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