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Complementary Competitiveness: Crafting an Employment Policy to Address Technological Unemployment in The Age of Artificial Intelligence

Sayı: 19 31 Mayıs 2024
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Complementary Competitiveness: Crafting an Employment Policy to Address Technological Unemployment in The Age of Artificial Intelligence

Abstract

Technological unemployment has been a concern since the Industrial Revolution. Approximately two centuries later, this issue has reemerged with the rapid advancements in machine learning and artificial intelligence technologies (AI). In contrast to the Industrial Revolution era, the unemployment caused by AI in the present age is different. Unlike earlier times, where unemployment primarily resulted from automating basic manual labor, the current challenge arises from AI automating tasks that were previously considered too complex for machines to handle. This is due to the capacity of AI-powered machines to learn and adapt to new situations. As a result, the evolving job market necessitates a different approach to employment policies compared to those applied over the last century. In this study, a new policy suggestion referred to as "Complementary Competitiveness" is discussed, taking a nuanced stance, avoiding simplistic categorizations of AI as purely beneficial or detrimental. Instead, it concentrates on formulating an employment strategy that distinguishes between sectors, taking into account firms resaons’ of AI preferences, all while not impeding technological progress. This approach seeks to align employment policies with the evolving needs of the AI age, which goes beyond the conventional binary classification of professions and competencies as necessary or obsolete as it seen in the literature.

Keywords

Kaynakça

  1. Acemoglu, D., & Restrepo, P. (2018). Artificial intelligence, automation, and work. In The economics of artificial intelligence: An agenda (pp. 197-236). University of Chicago Press.
  2. Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of political economy, 128(6), 2188-2244.
  3. Aghion, P., Antonin, C., & Bunel, S. (2019). Artificial intelligence, growth and employment: The role of policy. Economie et Statistique/Economics and Statistics, (510-511-512), 150-164.
  4. Alhaddad, M. M. (2018). Artificial intelligence in banking industry: A review on fraud detection, credit management, and document processing. ResearchBerg Review of Science and Technology, 2(3), 25-46.
  5. Atkinson, R. D. (2018). Testimony of Robert D. Atkinson President Information Technology and Innovation Foundation.
  6. Autor, D. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3-30.
  7. Autor, D., Dorn, D., Katz, L. F., Patterson, C., & Van Reenen, J. (2020). The fall of the labor share and the rise of superstar firms. The Quarterly Journal of Economics, 135(2), 645-709.
  8. Bao, Y., Hilary, G., & Ke, B. (2022). Artificial intelligence and fraud detection. Innovative Technology at the Interface of Finance and Operations: Volume I, 223-247.

Ayrıntılar

Birincil Dil

İngilizce

Konular

İstihdam , Maliye Politikası , Para Politikası

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

29 Mayıs 2024

Yayımlanma Tarihi

31 Mayıs 2024

Gönderilme Tarihi

14 Kasım 2023

Kabul Tarihi

2 Ocak 2024

Yayımlandığı Sayı

Yıl 2024 Sayı: 19

Kaynak Göster

APA
Algül, Y. (2024). Complementary Competitiveness: Crafting an Employment Policy to Address Technological Unemployment in The Age of Artificial Intelligence. Erzurum Teknik Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 19, 59-78. https://doi.org/10.29157/etusbed.1390993

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