Affiliation:
1. Business School, Shandong University, Weihai 264209, China
2. HSBC Business School, Peking University, Shenzhen 518055, China
3. School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China
Abstract
This paper examines how AI at work impacts on-the-job learning, shedding light on workers’ reactions to the groundbreaking AI technology. Based on theoretical analysis, six hypotheses are proposed regarding three aspects of AI’s influence on on-the-job learning. Empirical results demonstrate that AI significantly inhibits people’s on-the-job learning and this conclusion holds true in a series of robustness and endogeneity checks. The impact mechanism is that AI makes workers more pessimistic about the future, leading to burnout and less motivation for on-the-job learning. In addition, AI’s replacement, mismatch, and deskilling effects decrease people’s income while extending working hours, reducing their available financial resources and disposable time for further learning. Moreover, it has been found that AI’s impact on on-the-job learning is more prominent for older, female and less-educated employees, as well as those without labor contracts and with less job autonomy and work experience. In regions with more intense human–AI competition, more labor-management conflicts, and poorer labor protection, the inhibitory effect of AI on further learning is more pronounced. In the context of the fourth technological revolution driving forward the intelligent transformation, findings of this paper have important implications for enterprises to better understand employee behaviors and to promote them to acquire new skills to achieve better human–AI teaming.
Funder
Humanities and Social Science Research Project of the Ministry of Education of China
Project of the Natural Science Foundation of China
Project of the Natural Science Foundation of Shandong Province, China
Project of the Social Science Foundation of Shandong Province, China
Subject
Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software
Reference79 articles.
1. Agrawal, A., Gans, J., and Goldfarb, A. (2019). The Economics of Artificial Intelligence: An Agenda, University of Chicago Press. Available online: https://ideas.repec.org/b/nbr/nberbk/agra-1.html.
2. The impact of artificial intelligence on labor productivity;Damioli;Eurasian Bus. Rev.,2021
3. Robots are not always bad for employment and wages;Sequeira;Int. Econ.,2021
4. Cobots in knowledge work;Sowa;J. Bus. Res.,2021
5. Design principles for a hybrid intelligence decision support system for business model validation;Dellermann;Electron. Mark.,2018
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献