YAPAY ZEKÂ ORTAMINDAKİ DIJİTAL KAMU YÖNETİMİNİN YOL HARİTASI

Yıl 2022, Cilt: 4 Sayı: 1, 99 - 130, 14.10.2022

Ahmet Efe

Öz

ÖZ: Nesnelerin interneti (IoT), büyük veri, makine öğrenimi (ML), kuantum bilişim, blok zincir ve yapay zeka (YZ) gibi yenilikçi teknoloji dalgaları, kişisel ve profesyonel ortamları ve uygulamaları derinden derine yeniden şekillendirmektedir. Mevcut iş sınıflarının ve kariyer uzmanlık alanlarının çoğunun ortadan kalkacağı ve tamamen farklı beceriler isteyen yeni yetkinliklerin isteneceği yeni bir dünya beklenmektedir. Kamu yöneticileri ve bürokrasi bu yıkıcı yeniliklerle başa çıkabilmek için karşılaşacakları zorluklara ne yazık ki hazırlıksız görünmektedir. Son birkaç yüzyılda gelişen mevcut hükümet yapılarının, kamusal uygulamaların, kurumsal sistemlerin ve iş süreçlerinin çoğu yakın gelecekte büyük olasılıkla geçersiz hale gelecektir. Gelişmiş ülkelerdeki hükümetler, Endüstri 4.0 ve Toplum 5.0’a uygun alt yapı, politika ve düzenleme hazırlıkları kapsamında tüm seviyelerde kamu idarelerinin iç yönetimini yeniden düzenlerken, politika tasarımını ve değerlendirmesini iyileştirmek için YZ kullanımının potansiyelini arttırma çabası içerisindedirler. Bu çalışmada, YZ teknolojisi ile meydana gelen potansiyel yıkıcı yenilikçi teknolojilerden dolayı hükümetlerin, vatandaşlarına en iyi şekilde nasıl hizmet edebileceklerini yeniden düşünmeleri ve kamu çalışanlarının da yenilikçi yetkinlik seviyelerini geliştirmeleri için zemin hazırlamaya zorlayıcı bir ihtiyaç olduğu savunulmaktadır. Böylece yenilikçi ve proaktif kamu hizmeti sunum modellerinin yolu açılabilir ve kaynakları kısıtlı kuruluşları tekrarlayan rutin işlerde ciddi bir şekilde rahatlatabilir.

Anahtar Kelimeler

Yapay zeka, e-devlet, m-devlet, YBS, YZ kamu yönetimi

Kaynakça

• Abbate T., Bassano C., Coppola A., Miranda S., and Rarità L., (2014) "A knowledge-based decision support system for the service quality improvement in organizations," in 7th International Workshop of Information Logistics and Knowledge Supply, ILOG, pp. 49-60.
• Adorni G., (2000) "DESIREE: A decision support system for inundation risk evaluation and emergencies management," in International Conference on High-Performance Computing and Networking, pp. 555-557, Springer, Berlin, Heidelberg.
• Aguilera, and M. Ramos, (2016) "Technological unemployment: An approximation to the Latin American Case," AD-minister, vol. 29, pp. 58- 78.
• Alan F. T. Winfield and Jirotka M., (2018) ‘Ethical Governance is Essential to Building Trust in Robotics and Artificial Intelligence Systems’, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences (Vol. 376, No. 2133,), pp. 1–13.
• Arkin R., (2009) "Governing lethal behavior in autonomous robots," Chapman and Gall/CRC.
• Asaro P., (2012) "On banning autonomous weapon systems: Human rights, automation, and the dehumanization of lethal decision-making," International Review of the Red Cross, vol. 94, n. 886, pp. 687-709.
• Bode I., and Huelss H., (2018), "Autonomous weapons systems and changing norms in international relations," Review of International Studies, pp. 1- 21.
• Boselli R., Cesarini M, and Mezzanzanica M., (2011) "Framework guidelines to measure the impact of business intelligence and decision support methodologies in the public sector," in Proceedings of the European Conference on e-Government, pp. 107-115.
• Brauneis, R. and Goodman, E. P., (2017) Algorithmic Transparency for the Smart City. 20 Yale J. of Law & Tech. GWU Law School Public Law Research Paper, https://ssrn.com/abstract=3012499.
• Carli R., Albino V., Dotoli M., Mummolo G., and Savino M., (2015) "A dashboard and decision support tool for the energy governance of smart cities," in Environmental, Energy and Structural Monitoring Systems, IEEE Workshop on, pp. 23-28.
• Castellano M., Mastronardi G., Aprile A., Minardi M., Catalano P., Dicensi V., and Tarricone G., (2007) "A decision support system base line flexible architecture to intrusion detection," Journal of Software, vol. 2, n. 6, pp. 30-41.
• Chen H., (2009) AI, e-government, and politics 2.0," IEEE Intelligent Systems, vol. 24, n. 5.
• Chen Y, Lee J. (2018) Collaborative data networks for public service: governance, management, and performance. Public Manage. Rev. 20, 672–690. (doi:10.1080/14719037.2017.1305691)
• Corallo A., Fortunato L., Matera M., Alessi M., Camillò A., Chetta V., Giangreco E., and Storelli D., (2015), "Sentiment analysis for government: An optimized approach," in International Workshop on Machine Learning and Data Mining in Pattern Recognition, pp. 98-112, Springer, Cham.
• Coşkun, Y. (2015). Iletişim Teknolojilerinin Stratejik Kaynak Yönetimi: Ttaş Örneği, Uluslararası İktisadi ve İdari Bilimler Dergisi, 1 (1), 31-53. https://dergipark.org.tr/tr/pub/uiibd/issue/21611/232118
• Costa A., Julian V., and Novais P., (2018) "Personal assitants: Emerging computional technologies," Intelligent Systems Reference Library, vol. 132, Springer, Cham.
• Denham E. (2017) Four lessons NHS Trusts can learn from the Royal Free case. Information Commissioner's Office blog, 3 July. See https://iconewsblog.org.uk/2017/07/03/fourlessons-nhs-trusts-can-learn-from-the-royal-free-case/
• Dhanabalan T., and Sathish A., (2018) "Transforming Indian industries through artificial intelligence and robotics in industry 4.0," International Journal of Mechanical Engineering and Technology, vol. 9, n. 10. 835-845.
• Dzone. (2019) "28 Artificial Intelligence Terms You Need to Know." Dzone.com. https://dzone.com/articles/ai-glossary (accessed 3/22/19).
• Efe, A. & Özdemir, G. (2021). Yapay Zekâ Ortaminda Kamu Yönetiminin Geleceği Üzerinde Bir Değerlendirme. Kamu Yönetimi ve Teknoloji Dergisi, 3 (1), 34-60. Retrieved from https://dergipark.org.tr/tr/pub/kaytek/issue/64162/927834
• EY, (2018) "The future workplace: How to automate intelligently," October 29.
• Floreano D., and Wood R., (2015), "Science, technology and the future of small autonomous drones," Nature, vol. 521, n. 7553, p. 460-466.
• Etscheid J. (2019) Artificial Intelligence in Public Administration. In: Lindgren I. et al. (eds) Electronic Government. EGOV 2019. Lecture Notes in Computer Science, vol 11685. Springer, Cham. https://doi.org/10.1007/978-3-030-27325-5_19
• Freedberg S., 2019 ‘Should We Ban Killer Robots? Can We?’, Breaking Defense, 2019, <https://breakingdefense.com/2019/03/should-we-ban-killer-robots-can-we/>, accessed 4 September.
• Gasser U. and Almeida V., ‘A Layered Model for AI Governance’, IEEE Internet Computing (Vol. 21, No. 6, 2017), pp. 58–62.
• Google, 2019 ‘Perspectives on Issues in AI Governance’, 2019, <https://ai.google/static/documents/perspectives-on-issues-in-ai-governance.pdf>, accessed 4 September.
• Gunning D., ‘Explainable Artificial Intelligence (XAI)’, Defense Advanced Research Projects Agency (DARPA), 2016.
• Head, B. W., & Alford, J. (2015). Wicked Problems: Implications for Public Policy and Management. Administration & Society, 47(6), 711–739. https://doi.org/10.1177/0095399713481601
• Horgan D, Hackett J, Westphalen C, B, Kalra D, Richer E, Romao M, Andreu A, L, Lal J, A, Bernini C, Tumiene B, Boccia S, Montserrat A: Digitalisation and COVID-19: The Perfect Storm. Biomed Hub 2020; 5:1-23. doi: 10.1159/000511232
• House of Lords. (2018) AI in the UK: ready, willing and able? Select Committee on Artificial Intelligence. Report number: HL Paper 100.
• IBM, 2019 ‘Introducing AI Fairness 360’, 2018, https://www.ibm.com/blogs/research/2018/ 09/ai-fairness-360/ ,
• Ithaca, NY, (2018) Cornell University, www.cs.cornell.edu/courses/cs4732/2017sp/ . Shark, Alan. "The Future Is Now: Artificial Intelligence and Robots and What It Means for Local Government." Public Technology Institute, www.pti.org/cals/previous/2018events/041818.asp.
• Jess C., (2017) Future job automation to hit hardest in low wage metropolitan areas like Las Vegas, Orlando and Riverside-San Bernardino, Institute for Spatial Economic Analysis, May 3.
• Kim PS (2017) The development of modern public administration in East Asia. Int Rev Adm Sci 83:225–240. https://doi.org/10.1177/0020852316685162
• Kolbjørnsrud V., Amico R., and Thomas R. J. (2016) How Artificial Intelligence Will Redefine Management, Harward Bussiness Review, Leadership Development, https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management
• Maas M. M, 2019 ‘How Viable is International Arms Control for Military Artificial Intelligence? Three Lessons from Nuclear Weapons’, Contemporary Security Policy (Vol. 40, No. 3, ), pp. 285–311.
• Meritalk, (2020) Governments Need to Hurry AI Adoption, MeriTalk Survey Finds, Mertalk News, https://www.meritalk.com/articles/governments-need-to-hurry-ai-adoption-meritalk-survey-finds/
• Pandey SK (2017) Theory and method in public administration. Rev Public Pers Admin 37:131–138. https://doi.org/10.1177/0734371X17707036
• Poolla C., Ishihara A., Rosenberg S., Martin R., Fong A., Ray S., and Basu C., (2014) "Neural networks forecasting of solar power for NASA Ames sustainability base," in Computational Intelligence Applications in Smart Grid, IEEE Symposium on, p. 1-8.
• Russel S., Hauert S., Altman R., and Veloso M., (2015), "Ethics of artificial intelligence," Nature, vol. 521, n. 7553, pp. 415-416.
• Saygılı, Hilal (2020), Yapay Zeka Kamu Politikaları: ABD ve Çin’in Yapay Zeka Kamu Politikalarının Karşılaştırılması, Yüksek Lisans Tezi, http://acikerisim.ybu.edu.tr:8080/xmlui/handle/123456789/2648
• Sara N., Halland R., Igel C., and Alstrup S., (2015), "High-scool dropout prediction using machine learning: A danish large-scale study," ESANN 2015 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, pp. 319-324.
• Savoie, D.J. (2006), "What is Wrong with the New Public Management?", Otenyo, E.E. and Lind, N.S. (Ed.) Comparative Public Administration (Research in Public Policy Analysis and Management, Vol. 15), Emerald Group Publishing Limited, Bingley, pp. 593-602. https://doi.org/10.1016/S0732-1317(06)15025-3
• Schott, R. (1976). Public Administration as a Profession: Problems and Prospects. Public Administration Review, 36(3), 253-259. doi:10.2307/974582
• Shen H., Hu J., Zhao J., and Dong J., (2012), "Ontology based modeling of emergency incidents and crisis management," in Proceedings of the 9th International ISCREAM Conference, Vancouver, Canada.
• Sivarajah U., Lee H., Irani Z., and Weerakkody V., (2014) "Forecasting smart cities through ICT driven policy-making: Expected outcomes and impacts of DAREED project," International Journal of Electronic Government Research, vol. 10, n. 3, pp. 1-18.
• Stanek S., and Drosio S., (2014) "Intelligent computer support for crisis management," Intelligent Decision Technologies, vol. 8, n. 1, pp. 53-63.
• Stanek S., Drosio and S., (2012) "A Hybrid Decision Support System for disaster/crisis management", in DSS, pp. 279-290.
• Sutherland J., (2008) "Directive decision devices: Reversing the locus of authority in human-computer associations," Technological Forecasting and Social Change, vol. 75, n. 7, pp. 1068-1089.
• Wachter S., Mittelstadt B. and Floridi L. (2017) ‘Transparent, Explainable, and Accountable AI for Robotics’, Science Robotics (Vol. 2, No. 6,).
• Weber E, Khademian A. (2008) Wicked problems, knowledge challenges, and collaborative capacity builders in network settings. Public Administr. Rev. 68, 334–349. (doi:10.1111/ j.1540-6210.2007.00866.x)
• WEF, (2018) World Economic Forum, "The Future of Jobs Report," p.8.
• Winfield and Jirotka, (2018) ‘Ethical Governance is Essential to Building Trust in Robotics and Artificial Intelligence Systems’. https://royalsocietypublishing.org/doi/full/10.1098/rsta. 2018.0085
• Wirtz BW, Weyerer JC, Geyer C (2018) Artificial intelligence and the public sector – applications and challenges. Int J Public Adm 13(7):1–20. https://doi.org/10.1080/01900692.2018.1498103
• Xenakis A., and Macintosh A., (2004) "Trust in public administration e-transactions: E-voting in the UK," in International Conference on Trust, Privacy and Security in Digital Business, pp. 162-171, Springer, Berlin, Heidelberg.