THE IMPACTS OF ARTIFICIAL INTELLIGENCE TECHNOLOGY ON PUBLIC ADMINISTRATION: AN ASSESSMENT IN TERMS OF OPPORTUNITIES

Year 2025, Volume: 9 Issue: 1, 408 - 426, 28.03.2025

Müslüm Kayacı

Abstract

Artificial Intelligence (AI) technologies offer significant opportunities to enhance efficiency in public administration, improve decision-making processes, and support citizen-centered service delivery. AI-powered systems accelerate public services by reducing bureaucratic burdens, while various AI tools (such as virtual assistants and chatbots) facilitate citizens' access to public services. The contributions of AI to public administration can be examined at both individual and organizational levels. At the individual level, AI reduces human-induced inconsistencies in public services, ensuring that citizens receive equitable and predictable services. At the organizational level, AI helps public institutions optimize resource allocation, streamline processes, and strengthen inter-agency collaboration. Additionally, AI is considered to play a crucial role in combating corruption, enhancing transparency, and strengthening accountability in public administration. In this context, the primary aim of this study is to explore the transformative opportunities that AI offers at both individual and organizational levels in public administration. The scope of the study includes examining the advantages of AI in service delivery, decision-making, efficiency, transparency, and anti-corruption efforts through academic sources and concrete examples.

Keywords

Artificial İntelligence, Public Administration, Transparency, Algorithm

YAPAY ZEKÂ TEKNOLOJİSİNİN KAMU YÖNETİMİNE ETKİLERİ: FIRSATLAR AÇISINDAN BİR DEĞERLENDİRME

Abstract

Yapay zekâ (YZ) teknolojileri, kamu yönetiminde verimliliği artıran, karar alma süreçlerini geliştiren ve vatandaş odaklı hizmet sunumunu destekleyen önemli fırsatlar sunmaktadır. YZ destekli sistemler, bürokratik yükleri azaltarak kamu hizmetlerinin hızlanmasını sağlarken, çeşitli YZ araçlarıyla (sanal asistenler, chatbotlar) vatandaşların kamu hizmetlerine erişimini kolaylaştırmaktadır. YZ’nin kamu yönetimine katkısı bireysel ve örgütsel düzeylerde ele alınabilir. Bireysel düzeyde YZ, kamu hizmetlerinde insan kaynaklı tutarsızlıkları azaltarak, vatandaşlara eşit ve öngörülebilir hizmet sunulmasını sağlar. Örgütsel düzeyde ise kamu kurumlarının kaynak tahsisini optimize etmesine, süreçlerini hızlandırmasına ve kurumlar arası iş birliğini güçlendirmesine katkı sağlamaktadır. Ayrıca, YZ’nin kamu yönetiminde yolsuzlukla mücadele, şeffaflığın artırılması ve hesap verebilirliğin güçlendirilmesi gibi konularda da önemli bir rol oynayabileceği öne sürülmektedir. Bu çerçevede bu çalışmanın temel amacı, YZ’nin kamu yönetiminde bireysel ve örgütsel düzeyde sunduğu dönüştürücü fırsatları incelemektir. Çalışmanın kapsamı, YZ'nin hizmet sunumu, karar alma, verimlilik, şeffaflık, yolsuzlukla mücadele gibi alanlarda sağladığı avantajları akademik kaynaklar ve somut örneklerle geliştirmektir.

Keywords

Yapay Zekâ, Kamu Yönetimi, Şeffaflık, Algoritma

References

• Adams, S., Arel, I., Bach, J., Coop, R., Furlan, R., Goertzel, B., Hall, J. S., Samsonovich, A., Scheutz, M., Schlesinger, M., Shapiro, S. C., Sowa, J. (2012). Mapping the landscape of human-level artificial general intelligence. AI magazine, 33(1), 25-42.
• Alhosani, K., & Alhashmi, S. M. (2024). Opportunities, challenges, and benefits of AI innovation in government services: a review. Discover Artificial Intelligence, 4(1), 18, 1-19.
• Armstrong, E. (2005). Integrity, transparency and accountability in public administration: Recent trends, regional and international developments and emerging issues. United Nations, Department of Economic and Social Affairs, 1(10), 1-10.
• Barth, T. J., & Arnold, E. (1999). Artificial intelligence and administrative discretion: Implications for public administration. The American Review of Public Administration, 29(4), 332-351.
• Bostrom, N. (1998). How long before superintelligence. International Journal of Futures Studies, 2(1), 1-14.
• Bostrom, N. (2016). The control problem. Excerpts from superintelligence: Paths, dangers, strategies. Science Fiction and Philosophy: From Time Travel to Superintelligence, 308-330.
• Boyd, M., & Wilson, N. (2017). Rapid developments in artificial intelligence: how might the New Zealand government respond?. Policy Quarterly, 13(4), 36-43.
• Bullock, J. B. (2019). Artificial intelligence, discretion, and bureaucracy. The American Review of Public Administration, 49(7), 751-761.
• Bullock, J., Young, M. M., & Wang, Y. F. (2020). Artificial intelligence, bureaucratic form, and discretion in public service. Information Polity, 25(4), 491-506.
• Busuioc, M. (2021). Accountable artificial intelligence: Holding algorithms to account. Public Administration Review, 81(5), 825-836.
• Caiden, G. E., & Caiden, N. J. (1977). Administrative corruption. Public Administration Review, 37(3), 301-309.
• Calo, R., & Citron, D. K. (2021). The automated administrative state: crisis of legitimacy. Emory Law Journal, 70(4), 797-846.
• David, G. (2024). Artificial Intelligence: Opportunities and Challenges for Public Administration. Canadian Public Administration, 67(3), 388-406.
• Eren, V., & Duman, H. (2025). Artificial Intelligence Support In Disaster Management. Kamu Yönetimi ve Teknoloji Dergisi, 7(1), 13-36.
• Erickson, J. (2023). Algorithms. https://archive.org/details/Algorithms-Jeff-Erickson (Erişim: 14.02.2025).
• Finlay, S. (2018). Artificial intelligence and machine learning for business. A no-nonsense guide to data driven Technologies. http://repository.bitscollege.edu.et:8080/bitstream/handle/123456789/744/ARTIFI~1.PDF?sequence=1 (Erişim: 10.02.2025)
• Goertzel, B. (2014). Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence, 5(1), 1-46.
• Grimmelikhuijsen, S. G., & Meijer, A. J. (2014). Effects of transparency on the perceived trustworthiness of a government organization: Evidence from an online experiment. Journal of Public Administration Research and Theory, 24(1), 137-157.
• Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. X. (2017). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 143, 23-37.
• Knuth, D. E. (1977). Algorithms. Scientific American, 236(4), 63-81.
• Levy, K., Chasalow, K. E., & Riley, S. (2021). Algorithms and decision-making in the public sector. Annual Review of Law and Social Science, 17(1), 309-334.
• Lima, M. S. M., & Delen, D. (2020). Predicting and explaining corruption across countries: A machine learning approach. Government Information Quarterly, 37(1), 101407.
• Margetts, H., & Dorobantu, C. (2019). Rethink government with AI. Nature, 568(7751), 163-165.
• Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt.
• McGinnis, J. O. (2010). Accelerating ai. Northwestern University Law Review, 104(3), 1253-1270.
• Mehr, H. (2017). Artificial intelligence for citizen services and government. Cambridge, MA: Harvard Kennedy School, Ash Center for Democratic Governance And Innovation. 1-19.
• Ng, G. W., & Leung, W. C. (2020). Strong artificial intelligence and consciousness. Journal of Artificial Intelligence and Consciousness, 7(1), 63-72.
• OECD (2019). Artificial Intelligence in Society. OECD Publishing, Paris https://www.oecd.org/content/dam/oecd/en/publications/reports/2019/06/artificial-intelligence-in-society_c0054fa1/eedfee77-en.pdf (Erişim: 04.02.2025)
• Poister, T. H. (2010). The future of strategic planning in the public sector: Linking strategic management and performance. Public Administration Review, 70, 246-254.
• Rosa, A., Feyereisl, J., & Team, T. G. (2016). A framework for searching for general artificial intelligence. http://arxiv.org/abs/1611.00685 (Erişim: 07.02.2025)
• Sobrino-García, I. (2021). Artificial intelligence risks and challenges in the Spanish public administration: An exploratory analysis through expert judgements. Administrative Sciences, 11(3), 1-23.
• Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368-383.
• Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533.
• Thierer, A., O’Sullivan, A., & Russell, R. (2017). Artificial intelligence and public policy. Arlington, VA: Mercatus Center George Mason University.
• Tyler, T. R. (2000). Social justice: Outcome and procedure. International Journal of Psychology, 35(2), 117-125.
• Van Ryzin, G. G. (2011). Outcomes, process, and trust of civil servants. Journal of Public Administration Research and Theory, 21(4), 745-760.
• Vogl, T. M., Seidelin, C., Ganesh, B., & Bright, J. (2020). Smart technology and the emergence of algorithmic bureaucracy: Artificial intelligence in UK local authorities. Public Administration Review, 80(6), 946-961.
• Voss, P. (2007). Essentials of general intelligence: The direct path to artificial general intelligence. Artificial General Intelligence, 131-157.
• Voss, P. (2017). From Narrow to General AI and from External to Internal Intelligence. Intuition Machine, October 3. Medium https://medium.com/intuitionmachine/from-narrow-to-general-ai-e21b568155b9 (Erişim: 04.02.2025)
• Wirtz, B. W., & Müller, W. M. (2019). An integrated artificial intelligence framework for public management. Public Management Review, 21(7), 1076-1100.
• Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596-615.
• Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The dark sides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration, 43(9), 818-829.
• Young, M. M., Bullock, J. B., & Lecy, J. D. (2019). Artificial discretion as a tool of governance: a framework for understanding the impact of artificial intelligence on public administration. Perspectives on Public Management and Governance, 2(4), 301-313.
• Ziewitz, M. (2016). Governing algorithms: Myth, mess, and methods. Science, Technology, & Human Values, 41(1), 3-16.