A Bibliometric Analysis of Artificial Intelligence and the Workforce: an Assessment of Trends, Patterns, and Future Directions

Öz

When the literature on artificial intelligence and the workforce is examined, it is seen that the impact of artificial intelligence on the workforce is addressed in a historical perspective and examined in different frameworks. Our study is about a bibliometric analysis using the keywords “artificial intelligence” and “workforce” in the Web of Science (WOS) database in order to examine academic studies in this field. Thus, it aims to understand the relationship, trends, patterns, and future expectations between artificial intelligence and the workforce. In this context, 130 studies published between 2003 and 2024 in the WOS database were examined. Accordingly, it was seen that the relationship between artificial intelligence and the workforce has been investigated with increasing interest in recent years; the interaction between artificial intelligence and the workforce is a multifaceted subject and requires perspectives from different disciplines; the United States of America and the People's Republic of China are leading artificial intelligence research and applications; concepts such as “technology”, “automation”, “employment” and “work” are prominent. Therefore, it has emerged that the potential effects of artificial intelligence on the workforce, especially concerns about automation and job loss, have been intensively addressed by researchers. Furthermore, relevant studies reveal that the relationship in question is complex and multifaceted and contains both opportunities and challenges. In this context, it has been determined that artificial intelligence affects labour markets, an important issue that requires further research and policy discussion in the future.

Anahtar Kelimeler

• Artificial Intelligence
• Workforce
• Bibliometric analysis
• WOSviewer

Kaynakça

1. Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technoLogical change: An empiricaL exploration. Quarterly Journal of Economics, 118 (4), 1279-1333. google scholar
2. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company. google scholar
3. CherrY, M. A. (2016). Beyond miscLassification: The digitaL transformation of work. Comparative Labor Law & Policy Journal (Forthcoming), Saint Louis U. Legal Studies Research Paper No. 2016-2. google scholar
4. ÇaLışır, Y. C. (2024). Uzun dönemLi bakım sigortasının Literatürdeki izLeri: BibLiYometrik bir inceLeme. Journal of Social Policy Conferences, 86, 42-54. google scholar
5. Davenport, T. H., & KirbY, J. (2016). Only humans need apply: Winners and losers in the age of smart machines. HarperBusiness. google scholar
6. DeLipetrev, B., Tsinaraki, C., & Kostic, U. (2020). AI Watch historical evolution of artificial intelligence. European Commission, Joint Research Centre. google scholar
7. Donthu, N., Kumar, S., Mukherjee, D., PandeY, N., & Lim, W. M. (2021). How to conduct a bibLiometric anaLYsis: An overview and guideLines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070 google scholar
8. Drucker, P. F. (1999). Management challenges for the 21st century. HarperCoLLins. google scholar

9. Dusyant, D. (2024). The impact of artificiaL intelligence on workforce dYnamics: Opportunities and challenges. Scholars Digest, 1(1). google scholar
10. Ensruld, K. (2024, January 17). Navigating the new normal: Adapting in the age of AI and hybrid work models. Chief Learning Offi-cer. https://www.chieflearningofhcer.com/2024/01/17/navigating-the-new-normaL-adapting-in-the-age-of-ai-and-hYbrid-work-models/ (Erişim tarihi: 16.10.2024). google scholar
11. FreY, C., & Osborne, M. (2016). The future of empLoyment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change. google scholar
12. Haenlein, M., & Kaplan, A. (2019). A brief history of artificiaL intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5-14. google scholar
13. Haustein, S., & Lariviere, V. (2015). The use of bibliometrics for assessing research: PossibiLities, Limitations and adverse effects. İn I. M. WeLpe, J. WoLLersheim, S. RingeLhan, & M. OsterLoh (Eds.), Incentives and performance: Governance of research organizations (pp. 121-139). Springer InternationaL PubLishing. google scholar
14. Judijanto, L., Asfahani, A., & Vandika, Y. (2022). 21st century economic transformation: The impact of artificiaL inteLLigence on markets and empLoYment. Journal of Artificial Intelligence and Development, 1(1). google scholar
15. Liao, H., Tang, M., Luo, L., Li, C., ChicLana, F., & Zeng, X. J. (2018). A bibLiometric anaLYsis and visuaLization of medicaL big data research. Sustainability, 10(1), 166. google scholar
16. MasLow, A. H. (1943). A theorY of human motivation. Psychological Review, 50, 370-396. google scholar
17. NicuLescu, V. (2020). On the impact of high performance computing in big data anaLYtics for medicine. Applied Medical Informatics, 42(1), 9-18. google scholar
18. Pereira, V., HadjieLias, E., Christofi, M., & Vrontis, D. (2023). A systematic Literature review on the impact of artificiaL intelligence on workplace outeomes: A multi-process perspeetive. Human Resource Management Review, 33(i). google scholar
19. Pettinger, T. (2022, October 17). The Luddite fallacy. Economics Help. https://www.economicshelp.org/bLog/6717/economics/the-Luddite-fallacy/ (Erişim tarihi: 17.10.2024). google scholar
20. Pritchard, A. (1969). StatisticaL bibLiography or bibLiometrics? Journal of Documentation, 25(4), 348-349. google scholar
21. PwC. (2024). PwCs2024 Al jobs barometer. https://www.pwc.com/gx/en/issues/artificiaL-intelligence/job-barometer/report.pdf (Erişim tarihi: 01.11.2024). google scholar
22. RiedL, M. O. (2019). Human-centered artificiaL inteLLigence and machine Learning. Human Behavior and Emerging Technologies. google scholar
23. RusseLL, S., & Norvig, P. (2022). Artificial intelligence: A modern approach (4th ed.). Pearson Education Limited. google scholar
24. Scerbo, M. W. (1996). Theoretical perspectives on adaptive automation. In R. Parasuraman & M. Mouloua (Eds.), Automation and human performance: Theory and Applications (pp. 201-223). CRC Press. google scholar
25. SodaLes. (2024). The role of Al in creating a more inclusive and supportive work environment. https://www.sodalessolutions.com/the-roLe-of-ai-in-creating-a-more-incLusive-and-supportive-work-environment/ (Erişim tarihi: 17.10.2024). google scholar
26. Spector, P. E. (1997). Job satisfaction: Application, assessment, causes, and consequences. Sage Academic Books. google scholar
27. Wang, Q., Su, M., & Li, R. (2020). Is China the world’s blockchain leader? Evidence, evolution and outlook of China’s blockchain research. Journal of Cleaner Production, 264, 121742. google scholar
28. Web of Science. (2024). https://www.webofscience.com/wos/woscc/summarY/a721ae20-c3dc-47bf-881f-d3e8b37c9f06-011b23829a/ (Erişim tarihi: 30.10.2024). google scholar