Generative Artificial Intelligence Systems in the Fight Against Corruption: Potential, Threats and Prospects for Ukraine

Authors

  • Mykhailo Dumchikov Criminal Law and Procedure Department, Sumy State University, Ukraine https://orcid.org/0000-0002-4244-2419
  • Olha Maletova Criminal Law and Procedure Department, Sumy State University, Ukraine

DOI:

https://doi.org/10.6000/1929-4409.2025.14.10

Keywords:

Artificial intelligence, corruption, digital governance, anti-corruption policy, Ukraine, ethical challenges, transparency, cybersecurity

Abstract

Corruption remains one of Ukraine's most pressing challenges, undermining the rule of law, hindering economic development, and eroding public trust in state institutions. In the contemporary digital transformation era, generative Artificial Intelligence (AI) systems present new opportunities for combating corruption through automated solutions for financial flow analysis, anomaly detection, and corruption risk assessment. However, deploying such technological systems raises significant legal, ethical, and technical concerns.

This article analyses the potential and challenges of applying generative AI systems in Ukraine's anti-corruption policy. Through comparative analysis of international experience, the study identifies effective methods for implementing AI in Ukraine's law enforcement and governance practices, considering the country's legislative framework and political context. The research examines risks associated with AI implementation, including algorithmic manipulation, cybersecurity threats, data protection concerns, and ethical challenges.

The authors propose recommendations for adapting AI technologies to Ukraine's anti-corruption efforts, including developing regulatory frameworks, introducing algorithmic accountability, implementing ethical AI standards, and strengthening international cooperation. The findings demonstrate that, with proper regulation and oversight, generative AI can enhance government transparency and reinforce the rule of law in anti-corruption efforts.

References

Bernatt, Maciej and Alison Jones. 2022. “Populism and Public Procurement: An EU Response to Increased Corruption and Collusion Risks in Hungary and Poland.” Yearbook of European Law 41:11-47. DOI: https://doi.org/10.1093/yel/yeac009

Bozhenko, V. and K. Petrenko. 2022. “Best Practices in Using Digital Technologies and AI to Combat Corruption.” Bulletin of Sumy State University. Economics Series (2):59-66. DOI: https://doi.org/10.21272/1817-9215.2022.2-6

Chaykovsky, D. 2023. “AI as a New Tool for Combating Crimes in the Economic Sphere.” Legal Bulletin (6):335-342. DOI: https://doi.org/10.32782/yuv.v6.2023.41

Chitimira, H., E. Torerai, and L. Jana. 2024. “Leveraging AI to Combat Money Laundering and Related Crimes in the South African Banking Sector.” Potchefstroom Electronic Law Journal 27:1-30. DOI: https://doi.org/10.17159/1727-3781/2024/v27i0a18024

Diia. 2019. “Government Services Online Search the Site.” Retrieved March 5, 2025 (https://diia.gov.ua).

Diia. 2023. “How AI is Used in the Field of Open Data.” Retrieved March 5, 2025 (https://diia.data.gov.ua/info-center/aiod).

DOZORRO. 2018. “How DOZORRO AI Monitors Purchases.” Retrieved March 5, 2025 (https://dozorro.org/blog/yak-shtuchnij-intelekt-dozorro-monitorit-zakupivli.

FBI. 2019. “AI Has Implications Not Just for the Commercial Sector but for National Security and Law Enforcement.” Retrieved March 5, 2025 (https://www.fbi.gov/investigate/ counterintelligence/emerging-and-advanced-technology/artificial-intelligence).

Ghimire, A. 2025. “AI-Powered Anomaly Detection for AML Compliance in US Banking: Enhancing Accuracy and Reducing False Positives.” Global Trends in Science and Technology 1(1):95-120. DOI: https://doi.org/10.70445/gtst.1.1.2025.95-120

Heaton, J., Goodfellow, I., Bengio, Y., & Courville, A. 2018. "Deep learning." Genet Program Evolvable Mach 19:305-307. DOI: https://doi.org/10.1007/s10710-017-9314-z

Hryshko, V. and S. Vozniuk. 2024. “Problematic Aspects of the Implementation of AI in the Field of Jurisprudence.” Analytical and Comparative Jurisprudence. DOI: https://doi.org/10.24144/2788-6018.2024.02.3

Kingma, D.P., & Welling, M. 2019. "An Introduction to Variational Autoencoders." Foundations and Trends® in Machine Learning 12(4):307-392. DOI: https://doi.org/10.1561/2200000056

Law of Ukraine. 2021. “On Approval of the Concept for the Development of AI in Ukraine.” Retrieved March 5, 2025 (https://zakon.rada.gov.ua/laws/show/1556-2020-%D1%80#Text).

Law of Ukraine. 2022. “About Electronic Identification and Electronic Trust Services.” Retrieved March 5, 2025 (https://zakon.rada.gov.ua/laws/show/2155-19#Text).

Law of Ukraine. 2023. “About Access to Public Information.” Retrieved March 5, 2025 (https://zakon.rada.gov.ua/ laws/show/2939-17#Text).

National Agency for the Prevention of Corruption. 2025. “Business Showed Record Activity in Reporting Corruption Last Year: Survey Results.” Retrieved March 5, 2025 (https://nazk.gov.ua/uk/biznes-proyavyv-rekordnu-aktyvnist-u-povidomlenni-pro-koruptsiyu-mynulogo-roku-rezultaty-opytuvannya/).

Ortynskyi, V. 2024. “Criminal-Legal Characterization of Criminal Offenses Related to Corruption in Ukraine.” Bulletin of Lviv Polytechnic National University. Series: Legal Sciences 11(2):1-6. DOI: https://doi.org/10.23939/law2024.42.001

Podobnuy, O. 2022. “Deepfake in the Context of Declaration for the Future of Internet.” Retrieved March 5, 2025 (https://dspace.onua.edu.ua/bitstreams/6555a817-3832-492e-b340-b832c1d2dbef/download).

ProZorro. 2023. “AI Will Predict Competition in ProZorro Tenders.” Retrieved March 5, 2025 (https://prozorro.gov.ua/uk/ news/shtuchnij-intelekt-budeprognozuvati-konkurenciyu-na-tenderah-prozorro).

Renew Europe. 2024. “ARACHNE - A Success Story in Addressing Fraud in EU Funds?” Retrieved March 5, 2025 (https://www.reneweuropegroup.eu/events/2022-06-07/arachne-a-success-story-in-addressing-fraud-in-eu-funds).

Russell, S., & Norvig, P. 2021. Artificial Intelligence: A Modern Approach (4th ed.). Pearson. Retrieved March 5, 2025 (http://lib.ysu.am/disciplines_bk/efdd4d1d4c2087fe1cbe03d9ced67f34.pdf)

Sun, GaoAng. 2020. “Government Governance of Smart Cities in China.” DOI: https://doi.org/10.2991/msie-19.2020.61

Susar, D., & Aquaro, V. 2019. "Artificial Intelligence: Opportunities and Challenges for the Public Sector." ICEGOV '19: Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance. DOI: https://doi.org/10.1145/3326365.3326420

The EU AI Act. 2023. Retrieved March 5, 2025 (https://artificialintelligenceact.eu).

Transparency International. 2023. “Corruption Perceptions Index 2023.” Retrieved March 5, 2025 (https://www.transparency. org/en/cpi/2023).

Transparency International. 2024. “Corruption Perceptions Index 2024.” Retrieved March 5, 2025 (https://www.transparency. org/en/cpi/2024).

Utkina, M., Bondarenko O., Chernadchuk, T. and Chernadchuk, O. 2023. “Intellectual Property Rights on Objects Created by AI.” Law, State & Telecommunications Review / Revista de Direito, Estado e Telecomunicações 15(1):85-105. DOI: https://doi.org/10.26512/lstr.v15i1.41729

Vinnikova, N. A. 2022. “Digital Technologies in the Fight Against Global Corruption.” Bulletin of the V.N. Karazin Kharkiv National University, Series ‘Issues of Political Science’ (41):30-39. DOI: https://doi.org/10.26565/2220-8089-2022-41-04

Zachek, O. I., Y. I. Dmytryk, and V. V. Senyk. 2023. “The Role of AI in Increasing the Effectiveness of Law Enforcement Activities.” Scientific Bulletin of the Lviv State University of Internal Affairs (3):148-156. Retrieved March 5, 2025 (https://dspace.lvduvs.edu.ua/bitstream/1234567890/5945/1/19.pdf).

Downloads

Published

2025-04-25

How to Cite

Dumchikov, M. ., & Maletova, O. . (2025). Generative Artificial Intelligence Systems in the Fight Against Corruption: Potential, Threats and Prospects for Ukraine. International Journal of Criminology and Sociology, 14, 106–115. https://doi.org/10.6000/1929-4409.2025.14.10

Issue

Section

Articles