YAPAY ZEKANIN DENETİMDE KULLANILMASI VE ETİK SORUNLAR

Year 2024, , 395 - 423, 15.12.2024

Mehmet Polat

https://doi.org/10.52836/sayistay.1554497

Abstract

Benzersiz bir yenilik olan yapay zekâ, yaşamın hemen her alanını etkilemektedir. Diğer alanlarda olduğu kamu yönetiminde de verimlilik ve etkinliği çok önemli ölçüde artırması beklenen yapay zekaya dayalı teknolojiler, sağladığı avantajlar kadar, çeşitli risklere ve tehditlere de kaynaklık etmektedir. Denetim, yapay zekanın en yüksek katkı potansiyeline sahip olduğu alanlardan biri olarak görülmektedir. Bu nedenle yapay zekanın denetimde kullanımının artması ile birlikte karşılaşılabilecek etik sorunlar yoğun tartışmalara konu olmaktadır. Bu çalışma, literatür taraması yöntemiyle yapay zekanın denetimde kullanılmasının yol açabileceği etik sorunlar, Uluslararası Yüksek Denetim Kurumları Örgütü (INTOSAI) ve İç Denetim Koordinasyon Kurulu’nun etik ilkeleri çerçevesinde bütüncül bir şekilde, daha çok fütüristtik bir yaklaşımla ele almayı amaçlamaktadır. Çalışma, etik sorunlara yol açma potansiyeli yüksek karmaşık hususların tamamen makinelere bırakılmaması gerektiği, ancak denetimde yapay zekânın kullanılmasından da vazgeçilemeyeceği çıkarımlarından hareketle, yapay zekanın denetimde etik ilkeler çerçevesinde kullanılmasına ilişkin yöntem ve yaklaşımlara odaklanmaktadır.

Keywords

Denetim, Yapay Zekâ, Etik, Önyargı, Opaklık, Gizlilik

Ethical Statement

Bu çalışmanın tüm aşamalarında bilimsel etik ilkelere uyulduğunu beyan ederim.

References

• Abdolmohammadi, M. ve Wright, A. (1987). An Examination of the Effects of Experience and Task Complexity on Audit Judgments. The Accounting Review, 62(1), 1-13.
• Agarwal, P. K. (2018). Public Administration Challenges in the World of AI and Bots. Public Administration Review, 78(6), 917-921.
• Ahmed, I., Jeon, G. ve Piccialli, F. (2022). From Artificial Intelligence to Explainable Artificial Intelligence in Industry 4.0: A Survey on What, How, and Where. IEEE Transactions on Industrial Informatics, 18(8), 5031-5042.
• AICPA (2023). Code of Professional Conduct, Erişim Tarihi: 11.11.2024 https://pub.aicpa.org/ codeofconduct/Ethics.aspx#
• Aitkazinov, A. (2023). The Role of Artificial Intelligence in Auditing: Opportunities and Challenges. International Journal of Research in Engineering, Science and Management, 6(6), 117-119.
• Aneesh, A. (2009). Global Labor: Algocratic Modes of Organization. Sociological Theory, 27(4), 347-370.
• Angelov, P. P., Soares, E. A., Jiang, R., Arnold, N. I. ve Atkinson, P. M. (2021). Explainable artificial intelligence: an analytical review. WIREs Data Mining and Knowledge Discovery, 11(5), e1424.
• Arnold, V. ve Sutton, S. G. (1998). The theory of technology dominance: Understanding the impact of intelligent decision aids on decision maker’s judgments. Advances in accounting behavioral research, 1(3), 175-194.
• Avundukluoğlu, P. (2023). SAI20 2023 Gündemi: Mavi Ekonomi ve Sorumlu YAPAY ZEKÂ. Sayıştay Dergisi, 34 (128), 169-176.
• Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R. ve Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82-115.
• Becker, A. (2019). Artificial intelligence in medicine: What is it doing for us today? Health Policy and Technology, 8(2), 198-205.
• Bozkurt Gümrükçüoğlu, Y. ve Yakacak, G. A. (2023). Yapay zekânın işe alım süreçlerinde kullanımı ve algoritmik ayrımcılık, Ankara Üni. Hukuk Fak. Dergisi, 72 (4),1701-1757.
• Busuioc, M. (2021). Accountable Artificial Intelligence: Holding Algorithms to Account. Public Administration Review, 81(5), 825-836.
• Chawla, N. V., Japkowicz, N. ve Kotcz, A. (2004). Special issue on learning from imbalanced data sets. ACM SIGKDD explorations newsletter, 6(1), 1-6.
• Chowdhury, E. K. (2021). Prospects and challenges of using artificial intelligence in the audit process. The Essentials of Machine Learning in Finance and Accounting, 139-156.
• Citron, D. B. ve Taffler, R.J. (2001). Ethical Behaviour in the U.K. Audit Profession: The Case of the Self-Fulfilling Prophecy Under Going-Concern Uncertainties. Journal of Business Ethics, 29(4), 353-363.
• Commerford, B. P., Dennis, S. A., Joe, J. R. ve Ulla, J. W. (2022). Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence. Journal of Accounting Research, 60(1), 171-201.
• Criado, J. I. ve O.de Zarate-Alcarazo, L. (2022). Technological frames, CIOs, and Artificial Intelligence in public administration: A socio-cognitive exploratory study in Spanish local governments. Government Information Quarterly, 39(3), 101688.
• Damar, M., Köse, H. Ö., Cagle, M. N. ve Özen, A. (2024). Mapping the Digital Frontier: Bibliometric and Machine Learning Insights into Public Administration Transformation. TCA Journal/Sayıştay Dergisi, 35(132), 9-41.
• Danaher, J. (2016). The Threat of Algocracy: Reality, Resistance and Accommodation. Philosophy & Technology, 29(3), 245-268.
• Davenport, T., Guha, A., Grewal, D. ve Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42.
• Davenport, T. H. ve Kirby, J. (2016). Just how smart are smart machines? MIT Sloan Management Review, 57(3), 21.
• Davenport, T. H. ve Ronanki, R. (2018). Artificial intelligence for the real world. Harvard business review, 96(1), 108-116.
• Deniz, N. (2024). Yapay Zekânın Sürdürülebilirliği: Sorumlu Yapay Zekâ . Dijital Teknolojiler ve Eğitim Dergisi, 3(1), 69–79.
• Deloitte (2018). Artificial Intelligence. Erişim Tarihi 18.09.2024, https://www.deloitte. com/content/dam/Deloitte/nl/Documents/deloitte-analytics/deloitte-nl-dataanalytics-artificial-intelligence-whitepaper-eng.pdf
• Dietvorst, B. J. ve Bharti, S. (2020). People Reject Algorithms in Uncertain Decision Domains Because They Have Diminishing Sensitivity to Forecasting Error. Psychological Science, 31(10), 1302-1314.
• Dietvorst, B. J., Simmons, J. P. ve Massey, C. (2015). Algorithm aversion: People erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology: General, 144(1), 114-126.
• Du-Harpur, X., Watt, F. M., Luscombe, N. M. ve Lynch, M. D. (2020). What is AI? Applications of artificial intelligence to dermatology. British Journal of Dermatology, 183(3), 423-430 . Dunleavy, P. ve Margetts, H. (2023). Data science, artificial intelligence and the third wave of digital era governance. Public Policy and Administration, 0(0), 1-30.
• Efe, A. ve Tunçbilek, M. (2023). Yapay Zekâ Algoritmalari İle Dönüşen Denetim Araçlari Üzerine Bir Değerlendirme. Denetişim(27), 72-102.
• Eggers, W. D., Malik, N. ve Gracie, M. (2019). Using AI to unleash the power of unstructured government data. https://www2.deloitte.com/us/en/insights/focus/cognitivetechnologies/natural-language-processing-examples-in-government-data.html
• Etscheid, J. (2019). Artificial Intelligence in Public Administration. Electronic Government, Cham.
• Fedyk, A., Hodson, J., Khimich, N. ve Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27(3), 938-985.
• Fetzer, J. H. (1990). What is Artificial Intelligence? In J. H. Fetzer (Ed.), Artificial Intelligence: Its Scope and Limits (pp. 3-27). Springer Netherlands.
• Gams, M., Gu, I. Y.-H., Härmä, A., Muñoz, A. ve Tam, V. (2019). Artificial intelligence and ambient intelligence. Journal of Ambient Intelligence and Smart Environments, 11, 71-86.
• Gendron, Y., Cooper, D. J. ve Townley, B. (2001). In the name of accountability - State auditing, independence and new public management. Accounting, Auditing & Accountability Journal, 14(3), 278-310.
• Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S. ve Yang, G. Z. (2019). XAI-Explainable artificial intelligence. Sci Robot, 4(37).
• Hasan, A. R. (2022). Artificial Intelligence (AI) in Accounting & Auditing: A Literature Review. Open Journal of Business and Management, 10, 440-465.
• Holzinger, A., Langs, G., Denk, H., Zatloukal, K. ve Müller, H. (2019). Causability and explainability of artificial intelligence in medicine. WIREs Data Mining and Knowledge Discovery, 9(4), e1312.
• INTOSIA (2019) ISSAI 130 Code of Ethics, Erişim Tarihi: 11.11.2024 https://www.intosai.org/ fileadmin/downloads/documents/open_access/ISSAI_100_to_400/issai_130/ISSAI_130_EN.pdf
• Issa, H., Sun, T. ve Vasarhelyi, M. A. (2016). Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce Supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1-20.
• Jakovljević, N. (2021). Application of artificial intelligence in audit. Monografija konferencije STES21, 277-290.
• Jiang, Y., Li, X., Luo, H., Yin, S. ve Kaynak, O. (2022). Quo vadis artificial intelligence? Discover Artificial Intelligence, 2(1), 4.
• Koçberber, S. (2008). Dünyada ve Türkiye’de Denetim Etiği. Sayıştay Dergisi (68), 65-89.
• Kokina, J. ve Davenport, T. H. (2017). The Emergence of Artificial Intelligence: How Automation is Changing Auditing. Journal of Emerging Technologies in Accounting, 14(1), 115-122.
• Köse, H. Ö. ve Polat, N. (2021). Dijital Dönüşüm ve Denetimin Geleceğine Etkisi, Sayıştay Dergisi, 32(123): 9-41.
• Madan, R. ve Ashok, M. (2022). A Public Values Perspective on the Application of Artificial Intelligence in Government Practices: A Synthesis of Case Studies. In J. R. Saura ve F. Debasa (Ed.), Handbook of Research on Artificial Intelligence in Government Practices and Processes (pp. 162-189). IGI Global.
• Madan, R. ve Ashok, M. (2023). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly, 40(1), 101774.
• McCarthy, J. (2007). What is artificial intelligence. Retrieved 03.08.2024 from https://cse. unl.edu/~choueiry/S09-476-876/Documents/whatisai.pdf
• Mehdiyev, N., Houy, C., Gutermuth, O., Mayer, L. ve Fettke, P. (2021, 2021//). Explainable Artificial Intelligence (XAI) Supporting Public Administration Processes – On the Potential of XAI in Tax Audit Processes. Innovation Through Information Systems, Cham.
• Minh, D., Wang, H. X., Li, Y. F. ve Nguyen, T. N. (2022). Explainable artificial intelligence: a comprehensive review. Artificial Intelligence Review, 55(5), 3503-3568.
• Minkkinen, M., Laine, J. ve Mäntymäki, M. (2022). Continuous Auditing of Artificial Intelligence: a Conceptualization and Assessment of Tools and Frameworks. Digital Society, 1(3), 21.
• Misra, S. K., Das, S., Gupta, S. ve Sharma, S. K. (2020, 2020//). Public Policy and Regulatory Challenges of Artificial Intelligence (AI). Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation, Cham.
• Mökander, J., Morley, J., Taddeo, M. ve Floridi, L. (2021). Ethics-Based Auditing of Automated Decision-Making Systems: Nature, Scope, and Limitations. Science and Engineering Ethics, 27(4), 44.
• Munoko, I., Brown-Liburd, H. L. ve Vasarhelyi, M. (2020). The Ethical Implications of Using Artificial Intelligence in Auditing. Journal of Business Ethics, 167(2), 209-234.
• Müller, V.C. ve Bostrom, N. (2016). Future Progress in Artificial Intelligence: A Survey of Expert Opinion. In V.C. Müller (Ed.), Fundamental Issues of Artificial Intelligence (pp.555-572). Springer International Publishing.
• Noordin, N. A., Hussainey, K. ve Hayek, A. F. (2022). The Use of Artificial Intelligence and Audit Quality: An Analysis from the Perspectives of External Auditors in the UAE. Journal of Risk and Financial Management, 15(8), 339.
• Parasuraman, R. ve Manzey, D. H. (2010). Complacency and bias in human use of automation: An attentional integration. Human Factors, 32(3), 381–410.
• Parycek, P., Schmid, V. ve Novak, A.-S. (2023). Artificial Intelligence (AI) and Automation in Administrative Procedures: Potentials, Limitations, and Framework Conditions. Journal of the Knowledge Economy.
• Polat, M. (2024). Kamu Yönetiminde Algoritmaların Egemenliği: Algokrasi ve Tehditleri. Kamu Yönetimi ve Teknoloji Dergisi, 6(2), 194-219.
• Qadir, H. A. (2017). Will Artificial Intelligence Brighten or Threaten the Future. Erişim Tarihi 01.08.2024, https://www.researchgate.net/publication/323535179_Will_Artificial_Intelligence_Brighten_or_Threaten_the_Future
• Ryan, M. (2020). In AI We Trust: Ethics, Artificial Intelligence, and Reliability. Science and Engineering Ethics, 26(5), 2749-2767.
• Samsonova-Taddei, A. ve Siddiqui, J. (2016). Regulation and the Promotion of Audit Ethics: Analysis of the Content of the EU’s Policy. Journal of Business Ethics, 139(1), 183-195.
• Seethamraju, R. ve Hecimovic, A. (2023). Adoption of artificial intelligence in auditing: An exploratory study. Australian Journal of Management, 48(4), 780-800.
• Sheth, A., Roy, K. ve Gaur, M. (2023). Neurosymbolic Artificial Intelligence (Why, What, and How). IEEE Intelligent Systems, 38(3), 56-62.
• Sobrino-García, I. (2021). Artificial Intelligence Risks and Challenges in the Spanish Public Administration: An Exploratory Analysis through Expert Judgements. Administrative Sciences, 11(3), 102.
• Sousa, W. G. d., Melo, E. R. P. d., Bermejo, P. H. D. S., Farias, R. A. S. ve Gomes, A. O. (2019). How and where is artificial intelligence in the public sector going? A literature review and research agenda. Government Information Quarterly, 36(4), 101392.
• Sutton, S. G., Arnold, V. ve Holt, M. (2023). An extension of the theory of technology dominance: Capturing the underlying causal complexity. International Journal of Accounting Information Systems, 50, 100626.
• Tagiew, R. (2020). Roadmap to algocracy-a feasibility study. Available at SSRN 3650010.
• Taşdöken, Ö. (2024). Use of Artificial Intelligence and Audit Analytics in Internal Audit Processes in The Public Sector. EDPACS, 1-15.
• Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, LIX(236), 433-460. van Noordt, C. ve
• Misuraca, G. (2022). Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), 101714.
• Veale, M. ve Brass, I. (2019). Administration by algorithm? Public management meets public sector machine learning. In K. Yeung ve M. Lodge (Ed.), Algorithmic Regulation. Oxford University Press.
• Wang, P. (2019). On defining artificial intelligence. Journal of Artificial General Intelligence, 10(2), 1-37.
• Yeşilçelebi, G. (2022). Denetimde Dijital Dönüşüm: Bilimetrik Bir İnceleme. Sayıştay Dergisi, 33(126), 381-408.
• Young, M. M., Himmelreich, J., Bullock, J. B. ve Kim, K.-C. (2021). Artificial Intelligence and Administrative Evil. Perspectives on Public Management and Governance, 4(3), 244-258.
• Zemankova, A. (2019, 8-10 Dec.). Artificial Intelligence in Audit and Accounting: Development, Current Trends, Opportunities and Threats - Literature Review. 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO),
• Zhang, C., Cho, S. ve Vasarhelyi, M. (2022). Explainable Artificial Intelligence (XAI) in auditing. International Journal of Accounting Information Systems, 46, 100572.