Search for Articles:
Journal:
Subject:
Open Access
Research Articles

How AI Will Affect Worker’s Earnings, Working Hours, and Employment Status


Xiaokang Zhou1,*

Business School, The University of Hong Kong, Hong Kong, China
Correspondence: Xiaokang Zhou, E-mail: xiaokangzhou21@gmail
 
J. Int. Eco. Glo. Gov., 2024, 1(6), 4-26; https://doi.org/10.12414/jiegg.240330
Received : 07 Sep 2024 / Revised : 13 Sep 2024 / Accepted : 13 Sep 2024 / Published : 30 Oct 2024
© The Author(s). Published by MOSP. This is an open access article under the CC BY-NC license.
Cite
Abstract
 
This paper investigates the impact of AI on the labor market. Three outcomes in the labor market, including employment status, earnings, and working hours, are considered. By closely analyzing the data on the labor market before and after an AI shock happened, it is found that the impact of AI tends to increase earnings and working hours in the short term. Additionally, more obvious findings may occur in the long term rather than the short term. It points out that the anxiety caused by the boomed technology may be mainly caused by the reform process instead of the direct impact. It suggests that people should focus on how to make adjustments to the education and training system to solve the problem.
 
Keywords: Labor Market, Technology, Difference in Difference, Artificial Intelligence
 
Download the full text PDF for viewing and using it according to the license of this paper.

Funding

    None.

Conflicts of Interest:

    The authors declare that they have no conflicts of interest to report regarding the present study.

References

  1. Acemoglu, D. and Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. In Handbook of labor economics, volume 4, pages 1043–1171. Elsevier.
  2. Acemoglu, D. and Restrepo, P. (2018a). Artificial intelligence, automation, and work. In The economics of artificial intelligence: An agenda, pages 197–236. University of Chicago Press.
  3. Acemoglu, D. and Restrepo, P. (2018b). The race between man and machine: Implications of technology for growth, factor shares, and employment. American economic review, 108(6):1488–1542.
  4. Agrawal, A., Gans, J., and Goldfarb, A. (2022). Chatgpt and how ai disrupts industries.
  5. Agrawal, A., Gans, J. S., and Goldfarb, A. (2019). Artificial intelligence: the ambiguous labor market impact of automating prediction. Journal of Economic Perspectives, 33(2):31–50.
  6. Bughin, J., Hazan, E., Sree Ramaswamy, P., DC, W., Chu, M., et al. (2017). Artificial intelligence the next digital frontier.
  7. Duarte, F. (2023). Number of chatgpt users (dec 2023).
  8. Felten, E., Raj, M., and Seamans, R. (2023). How will language modelers like chatgpt affect occupations and industries? arXiv preprint arXiv:2303.01157.
  9. Flood, S., King, M., Rodgers, R., Ruggles, S., Warren, J. R., Backman, D., Chen, A., Cooper, G., Richards, S., Schouweiler, M., and Westberry, M. (2023). IPUMS CPS: Version 11.0 [dataset]. https://doi.org/10.18128/D030.V11.0. Minneapolis, MN: IPUMS.
  10. Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., Feldman, M., Groh, M., Lobo, J., Moro, E., et al. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14):6531–6539.
  11. Graetz, G., Restrepo, P., and Skans, O. N. (2022). Technology and the labor market. Makridakis, S. (2017). The forthcoming artificial intelligence (ai) revolution: Its impact on society and firms. Futures, 90:46–60.
  12. Mutascu, M. (2021). Artificial intelligence and unemployment: New insights. Economic Analysis and Policy, 69:653–667.
  13. Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., et al. (2022). Artificial intelligence and life in 2030: the one hundred year study on artificial intelligence. arXiv preprint arXiv:2211.06318.
  14. Thormundsson, B. (2023). Artificial intelligence market size 2030.
  15. U.S. Bureau of Labor Statistics (2023). 2018 standard occupational classification system. Washington, DC: U.S. Bureau of Labor Statistics.
  16. Wang, F.-Y., Zhang, J. J., Zheng, X., Wang, X., Yuan, Y., Dai, X., Zhang, J., and Yang, L. (2016). Where does alphago go: From church-turing thesis to alphago thesis and beyond. IEEE/CAA Journal of Automatica Sinica, 3(2):113–120.
  17. Webb, M. (2019). The impact of artificial intelligence on the labor market. Available at SSRN 3482150.

© The Author(s). Published by MOSP
This is an open access article under the CC BY-NC license.

Zhou, X. How AI Will Affect Worker’s Earnings, Working Hours, and Employment Status. Journal of International Economy and Global Governance 2024, 1 (6), 4-23. https://doi.org/10.12414/jiegg.240330.

Subscribe Your Manuscript