Research Article
BibTex RIS Cite

THE RISE OF ARTIFICIAL INTELLIGENCE: FRIEND OR FOE OF ECONOMIC GROWTH?

Year 2025, Volume: 16 Issue: 1, 362 - 390, 30.06.2025
https://doi.org/10.54688/ayd.1629620

Abstract

Artificial Intelligence (AI) is fundamentally altering the global economic landscape, unveiling both remarkable growth opportunities and significant challenges. As a pivotal technology of the 21st century, AI is set to revolutionize productivity, catalyze innovation, and spawn entirely new sectors within the economy. Its applications extend across various industries—including healthcare, manufacturing, finance, and logistics—where it streamlines operations and enables advancements that were previously inconceivable. However, the transformative power of AI is accompanied by critical concerns. Potential job displacement resulting from automation, the exacerbation of economic inequality, and ethical considerations surrounding AI deployment remain pressing issues. This analysis delves into the complex and dualistic impact of AI on economic growth, focusing on its ability to enhance productivity and drive innovation while also examining the implications for the labour market and the regulatory framework needed to address these challenges. This discussion evaluates AI's dual role in driving economic prosperity and posing risks to inclusive, sustainable growth. Ultimately, it questions whether AI will be an ally or adversary in achieving equitable economic development.

References

  • Acemoglu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. In D. Card & O. Ashenfelter (Eds.), Handbook of Labor Economics (Vol. 4, pp. 1043–1171). Elsevier.
  • Amershi, S., Inkpen, K., Teevan, J., et al. (2019). Guidelines for Human-AI Interaction. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM Press.
  • Amin, S. (1976). Unequal Development: An Essay on the Social Formations of Peripheral Capitalism. New York: Monthly Review Press.
  • Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine Bias. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
  • Autor, D., Levy, F., & Murnane, R. J. (2003). The Skill Content of Recent Technological Change: An Empirical Exploration. The Quarterly Journal of Economics, 118(4), 1279–1333.
  • Bessen, J. E. (2019). AI and Jobs: The Role of Demand. In A. Agrawal & J. Gans & A. Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda (pp. 291-307). University of Chicago Press.
  • Boyer, R. (2010). Is a Finance-Led Growth Regime a Viable Alternative to Fordism? A Preliminary Analysis. Economy and Society, 29(1), 111–145.
  • Brynjolfsson, E., & McAfee, A. (2016). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.
  • Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of Machine Learning Research, 81, 77-91.
  • Couldry, N., & Mejias, U. A. (2019). The Costs of Connection: How Data is Colonizing Human Life and Appropriating It for Capitalism. Stanford University Press.
  • Dwivedi, Y. K., Hughes, D. L., Ismagilova, E., et al. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy. International Journal of Information Management, 57.
  • Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2023). GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models. arXiv:2303.10130.
  • Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.
  • Frank, A. G. (1967). Capitalism and Underdevelopment in Latin America. Monthly Review Press.
  • Frey, C. B., & Osborne, M. A. (2017). The Future of Employment: How Susceptible Are Jobs to Computerisation? Technological Forecasting and Social Change, 114, 254-280.
  • Goos, M., Manning, A., & Salomons, A. (2014). Explaining Job Polarization: Routine-Biased Technological Change and Offshoring. American Economic Review, 104(8), 2509–2526.
  • Hall, P. A., & Soskice, D. (2001). Varieties of Capitalism: The Institutional Foundations of Comparative Advantage. Oxford University Press.
  • Harvey, D. (2001). Spaces of Capital: Towards a Critical Geograpy. London: Routledge.
  • Huang, Y. (2024). The Labor Market Impact of Artificial Intelligence: Evidence from US Regions. IMF Working Paper No. 2024/199.
  • Jasanoff, S. (2004). States of Knowledge: The Co-Production of Science and the Social Order. Routledge.
  • Jumper, J., Evans, R., Pritzel, A., et al. (2021). Highly Accurate Protein Structure Prediction with AlphaFold. Nature, 596(7873), 583–589.
  • Korea Information Society Development Institute (KISDI). (2023). South Korea’s National AI Strategy Update. https://www.kisdi.re.kr
  • Marguerit, D. (2025). Augmenting or Automating Labor? The Effect of AI Development on New Work, Employment, and Wages. arXiv preprint arXiv:2503.19159.
  • National Information Society Agency (NIA). (2020). The National Guidelines for AI Ethics. https://ai.kisdi.re.kr/eng/main/contents.do?menuNo=500011
  • OECD. (2023). Science, Technology and Innovation Outlook 2023. OECD Publishing. https://www.oecd.org/en/publications/oecd-science-technology-and-innovation-outlook-2023_0b55736e-en.html
  • OECD. (n.d.). Artificial Intelligence. https://www.oecd.org/en/topics/artificial-intelligence.html Office of Science and Technology Policy (OSTP) (2022). Blueprint for an AI Bill of Rights. https://www.whitehouse.gov/ostp/ai-bill-of-rights
  • Pizzinelli, C., Panton, A. J., Mendes Tavares, M., Cazzaniga, M., & Li, L. (2023). Labor Market Exposure to AI: Cross-country Differences and Distributional Implications. IMF Working Paper No. 2023/216.
  • PwC. (2017). Sizing the prize. https://www.pwc.com/gx/en/issues/artificial-intelligence/publications/artificial-intelligence-study.html
  • Qiao, D., Rui, H., & Xiong, Q. (2024). AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform. arXiv preprint arXiv:2312.04180.
  • Raji, I. D., & Buolamwini, J. (2019). Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. Conference on AI, Ethics, and Society.
  • Schumpeter, J. A. (1942). Capitalism, Socialism and Democracy. New York: Harper & Brothers.
  • Stanford HAI. (2024). AI Index Report 2024. https://hai.stanford.edu/ai-index/2025-ai-index-report
  • Stilgoe, J., Owen, R., & Macnaghten, P. (2013). Developing a Framework for Responsible Innovation. Research Policy, 42(9), 1568–1580.
  • Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and Policy Considerations for Deep Learning in NLP. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 3645–3650.
  • Trammell, P., & Korinek, A. (2023). Economic Growth under Transformative AI. NBER Working Paper No. 31815.
  • Winner, L. (1980). Do Artifacts Have Politics? Daedalus, 109(1), 121–136.
  • Zuboff, S. (2019). The Age of Surveillance Capitalism. PublicAffairs.
  • Rodrik, D. (2011). The Globalization Paradox: Democracy and the Future of the World Economy. W. W. Norton.
  • Acemoglu, D., & Restrepo, P. (2017, March). Robots and Jobs: Evidence from US Labor Markets. Nber Working Paper No 23285.
  • Cockburn, I. M., Henderson, R., & Stern, S. (2018, March 18). The Impact of Artificial Intelligence on Innovation. National Bureau of Economic Research.
  • Hao, K. (2019, October 10). The biggest threat of deepfakes isn’t the deepfakes themselves. https://www.technologyreview.com/2019/10/10/132667/the-biggest-threat-of-deepfakes-isnt-the-deepfakes-themselves/
  • World Economic Forum. (2023, April 30). The Future of Jobs Report. https://www.weforum.org/publications/the-future-of-jobs-report-2023/
  • McKinsey Global Institute. (2023, June 14). The economic potential of generative AI : The next productivity frontier. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier?utm_source=chatgpt.com
  • McKinsey Global Institute. (2024, May 21). A New Future of Work : The race to deploy AI and raise skills in Europe and beyond. https://www.mckinsey.com/mgi/our-research/a-new-future-of-work-the-race-to-deploy-ai-and-raise-skills-in-europe-and-beyond
  • UNESCO. (2024, August 19). UNESCO launches open consultation to inform AI governance. https://www.unesco.org/en/articles/unesco-launches-open-consultation-inform-ai-governance?utm_source=chatgpt.com
  • UNESCO. (2024, September 24). Recommendation on the Ethics of Artificial Intelligence. https://www.unesco.org/en/articles/recommendation-ethics-artificial-intelligence
  • World Economic Forum. (2025, January 07). Future of Jobs Report 2025: 78 Million New Job Opportunities by 2030 but Urgent Upskilling Needed to Prepare Workforces. https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/?utm_source=chatgpt.com

YAPAY ZEKÂNIN YÜKSELİŞİ: İKTİSADİ BÜYÜMENİN DOSTU MU DÜŞMANI MI?

Year 2025, Volume: 16 Issue: 1, 362 - 390, 30.06.2025
https://doi.org/10.54688/ayd.1629620

Abstract

Yapay zekâ (YZ), küresel ekonomik manzarayı temelden değiştirmekte ve hem dikkate değer büyüme fırsatlarını hem de önemli zorlukları ortaya çıkarmaktadır. Yapay zekâ, 21. yüzyılın en önemli teknolojilerinden biri olarak üretkenlikte devrim yaratacak, inovasyonu katalize edecek ve ekonomide tamamen yeni sektörler ortaya çıkaracaktır. Uygulamaları sağlık, üretim, finans ve lojistik dahil olmak üzere çeşitli sektörlere yayılmakta, operasyonları kolaylaştırmakta ve daha önce düşünülemeyen ilerlemelere olanak sağlamaktadır. Bununla birlikte, yapay zekanın dönüştürücü gücüne bazı endişeler de eşlik etmektedir. Otomasyondan kaynaklanan potansiyel işten çıkarmalar, ekonomik eşitsizliğin artması ve yapay zekâ kullanımını çevreleyen etik hususlar önemli endişeler olarak görülmektedir. Bu çalışma, yapay zekânın ekonomik büyüme üzerindeki karmaşık ve dualistik etkisini araştırmakta, üretkenliği artırma ve yeniliği teşvik etme kabiliyetine odaklanırken, aynı zamanda işgücü piyasası ve bu zorlukları ele almak için gereken düzenleyici çerçeve üzerindeki etkilerini incelemektedir. Çalışma aynı zamanda yapay zekânın iktisadi refahı artırmadaki ikili rolünü ve kapsayıcı, sürdürülebilir büyümeye yönelik riskleri değerlendirmektedir. Nihayetinde, yapay zekânın eşitlikçi iktisadi kalkınmanın sağlanmasındaki rolü sorgulanmaktadır.

References

  • Acemoglu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. In D. Card & O. Ashenfelter (Eds.), Handbook of Labor Economics (Vol. 4, pp. 1043–1171). Elsevier.
  • Amershi, S., Inkpen, K., Teevan, J., et al. (2019). Guidelines for Human-AI Interaction. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM Press.
  • Amin, S. (1976). Unequal Development: An Essay on the Social Formations of Peripheral Capitalism. New York: Monthly Review Press.
  • Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine Bias. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
  • Autor, D., Levy, F., & Murnane, R. J. (2003). The Skill Content of Recent Technological Change: An Empirical Exploration. The Quarterly Journal of Economics, 118(4), 1279–1333.
  • Bessen, J. E. (2019). AI and Jobs: The Role of Demand. In A. Agrawal & J. Gans & A. Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda (pp. 291-307). University of Chicago Press.
  • Boyer, R. (2010). Is a Finance-Led Growth Regime a Viable Alternative to Fordism? A Preliminary Analysis. Economy and Society, 29(1), 111–145.
  • Brynjolfsson, E., & McAfee, A. (2016). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.
  • Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of Machine Learning Research, 81, 77-91.
  • Couldry, N., & Mejias, U. A. (2019). The Costs of Connection: How Data is Colonizing Human Life and Appropriating It for Capitalism. Stanford University Press.
  • Dwivedi, Y. K., Hughes, D. L., Ismagilova, E., et al. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy. International Journal of Information Management, 57.
  • Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2023). GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models. arXiv:2303.10130.
  • Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118.
  • Frank, A. G. (1967). Capitalism and Underdevelopment in Latin America. Monthly Review Press.
  • Frey, C. B., & Osborne, M. A. (2017). The Future of Employment: How Susceptible Are Jobs to Computerisation? Technological Forecasting and Social Change, 114, 254-280.
  • Goos, M., Manning, A., & Salomons, A. (2014). Explaining Job Polarization: Routine-Biased Technological Change and Offshoring. American Economic Review, 104(8), 2509–2526.
  • Hall, P. A., & Soskice, D. (2001). Varieties of Capitalism: The Institutional Foundations of Comparative Advantage. Oxford University Press.
  • Harvey, D. (2001). Spaces of Capital: Towards a Critical Geograpy. London: Routledge.
  • Huang, Y. (2024). The Labor Market Impact of Artificial Intelligence: Evidence from US Regions. IMF Working Paper No. 2024/199.
  • Jasanoff, S. (2004). States of Knowledge: The Co-Production of Science and the Social Order. Routledge.
  • Jumper, J., Evans, R., Pritzel, A., et al. (2021). Highly Accurate Protein Structure Prediction with AlphaFold. Nature, 596(7873), 583–589.
  • Korea Information Society Development Institute (KISDI). (2023). South Korea’s National AI Strategy Update. https://www.kisdi.re.kr
  • Marguerit, D. (2025). Augmenting or Automating Labor? The Effect of AI Development on New Work, Employment, and Wages. arXiv preprint arXiv:2503.19159.
  • National Information Society Agency (NIA). (2020). The National Guidelines for AI Ethics. https://ai.kisdi.re.kr/eng/main/contents.do?menuNo=500011
  • OECD. (2023). Science, Technology and Innovation Outlook 2023. OECD Publishing. https://www.oecd.org/en/publications/oecd-science-technology-and-innovation-outlook-2023_0b55736e-en.html
  • OECD. (n.d.). Artificial Intelligence. https://www.oecd.org/en/topics/artificial-intelligence.html Office of Science and Technology Policy (OSTP) (2022). Blueprint for an AI Bill of Rights. https://www.whitehouse.gov/ostp/ai-bill-of-rights
  • Pizzinelli, C., Panton, A. J., Mendes Tavares, M., Cazzaniga, M., & Li, L. (2023). Labor Market Exposure to AI: Cross-country Differences and Distributional Implications. IMF Working Paper No. 2023/216.
  • PwC. (2017). Sizing the prize. https://www.pwc.com/gx/en/issues/artificial-intelligence/publications/artificial-intelligence-study.html
  • Qiao, D., Rui, H., & Xiong, Q. (2024). AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor Platform. arXiv preprint arXiv:2312.04180.
  • Raji, I. D., & Buolamwini, J. (2019). Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products. Conference on AI, Ethics, and Society.
  • Schumpeter, J. A. (1942). Capitalism, Socialism and Democracy. New York: Harper & Brothers.
  • Stanford HAI. (2024). AI Index Report 2024. https://hai.stanford.edu/ai-index/2025-ai-index-report
  • Stilgoe, J., Owen, R., & Macnaghten, P. (2013). Developing a Framework for Responsible Innovation. Research Policy, 42(9), 1568–1580.
  • Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and Policy Considerations for Deep Learning in NLP. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 3645–3650.
  • Trammell, P., & Korinek, A. (2023). Economic Growth under Transformative AI. NBER Working Paper No. 31815.
  • Winner, L. (1980). Do Artifacts Have Politics? Daedalus, 109(1), 121–136.
  • Zuboff, S. (2019). The Age of Surveillance Capitalism. PublicAffairs.
  • Rodrik, D. (2011). The Globalization Paradox: Democracy and the Future of the World Economy. W. W. Norton.
  • Acemoglu, D., & Restrepo, P. (2017, March). Robots and Jobs: Evidence from US Labor Markets. Nber Working Paper No 23285.
  • Cockburn, I. M., Henderson, R., & Stern, S. (2018, March 18). The Impact of Artificial Intelligence on Innovation. National Bureau of Economic Research.
  • Hao, K. (2019, October 10). The biggest threat of deepfakes isn’t the deepfakes themselves. https://www.technologyreview.com/2019/10/10/132667/the-biggest-threat-of-deepfakes-isnt-the-deepfakes-themselves/
  • World Economic Forum. (2023, April 30). The Future of Jobs Report. https://www.weforum.org/publications/the-future-of-jobs-report-2023/
  • McKinsey Global Institute. (2023, June 14). The economic potential of generative AI : The next productivity frontier. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier?utm_source=chatgpt.com
  • McKinsey Global Institute. (2024, May 21). A New Future of Work : The race to deploy AI and raise skills in Europe and beyond. https://www.mckinsey.com/mgi/our-research/a-new-future-of-work-the-race-to-deploy-ai-and-raise-skills-in-europe-and-beyond
  • UNESCO. (2024, August 19). UNESCO launches open consultation to inform AI governance. https://www.unesco.org/en/articles/unesco-launches-open-consultation-inform-ai-governance?utm_source=chatgpt.com
  • UNESCO. (2024, September 24). Recommendation on the Ethics of Artificial Intelligence. https://www.unesco.org/en/articles/recommendation-ethics-artificial-intelligence
  • World Economic Forum. (2025, January 07). Future of Jobs Report 2025: 78 Million New Job Opportunities by 2030 but Urgent Upskilling Needed to Prepare Workforces. https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/?utm_source=chatgpt.com
There are 47 citations in total.

Details

Primary Language English
Subjects Economic Theory (Other)
Journal Section Makaleler
Authors

Aras Yolusever 0000-0001-9810-2571

Early Pub Date June 27, 2025
Publication Date June 30, 2025
Submission Date January 30, 2025
Acceptance Date May 12, 2025
Published in Issue Year 2025 Volume: 16 Issue: 1

Cite

APA Yolusever, A. (2025). THE RISE OF ARTIFICIAL INTELLIGENCE: FRIEND OR FOE OF ECONOMIC GROWTH?. Akademik Yaklaşımlar Dergisi, 16(1), 362-390. https://doi.org/10.54688/ayd.1629620