BEST PRACTICES IN THE USE OF DIGITAL TECHNOLOGIES AND ARTIFICIAL INTELLIGENCE TO FIGHT CORRUPTION

V. Bozhenko, K. Petrenko
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Abstract

Artificial intelligence technologies, machine learning, and big data analysis are increasingly used to improve anti-corruption systems globally. Establishing international standards and cooperation at the international level allows forming a basis for reducing the manifestations of business misconduct in the global dimension. Innovative methods and algorithms for processing big data allow identifying anomalies, establishing patterns of informal relationships, as well as minimizing the role of human in the system of decision support for corruption. The purpose of the research is to analyze the world's best practices in the introduction of digital technologies and artificial intelligence to reduce corruption in society. In 2021 were published 279 publications, while in 2017 - 198 publications, which indicates the relevance of the chosen field of study worldwide. Half of the scientific work on the impact of digitalization on the fight against corruption belongs to scientists from four countries (USA, China, India, UK). Systematization of scientific literature suggests that the main causes of corruption are lack of strict social and legal control over the activity of authorities, imperfect legal system, low wages, and social services in the civil service, low tolerance of society to corruption. The authors have analysed the current digital tools for combating corruption in Ukraine, the world experience of using artificial intelligence to combat corruption. Estonia is the leader in the introduction of digital information technologies in the economy among the countries of the European Union. The paper analyzes the dependence of the Corruption Perceptions Index on such indicators as the level of digital technology development and the level of e-government. The object of the study was 28 countries of the European Union. The source of primary data was Transparency International (Corruption Perceptions Index), European Commission (Digital Economy and Society Index) and United Nations (E-government Development Index). According to the results of the correlation analysis, the following is established: first, the higher the level of development of digital technologies, the lower the value of the corruption perception index in the country; secondly, reducing the level of corruption depending on the growth of the digitalization of public sector processes. The results of the study have practical value for public authorities to improve the anti-corruption system in the national economy through innovative information technologies.
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利用数字技术和人工智能打击腐败的最佳做法
人工智能技术、机器学习和大数据分析越来越多地用于改善全球反腐败体系。在国际一级建立国际标准和合作,可以为在全球范围内减少商业不端行为的表现奠定基础。处理大数据的创新方法和算法可以识别异常情况,建立非正式关系的模式,以及最大限度地减少人在腐败决策支持系统中的作用。该研究的目的是分析世界上在引入数字技术和人工智能以减少社会腐败方面的最佳做法。2021年发表了279篇论文,而2017年发表了198篇论文,这表明所选研究领域在全球范围内的相关性。关于数字化对反腐败影响的科学工作有一半来自四个国家(美国、中国、印度和英国)的科学家。科学文献的系统化表明,腐败的主要原因是对当局的活动缺乏严格的社会和法律控制,法律制度不完善,工资低,公务员的社会服务水平低,社会对腐败的容忍度低。作者分析了乌克兰目前用于打击腐败的数字工具,以及世界上使用人工智能打击腐败的经验。爱沙尼亚是欧盟国家中在经济中引入数字信息技术的领导者。本文分析了清廉指数对数字技术发展水平和电子政务水平等指标的依赖关系。这项研究的对象是欧盟的28个国家。主要数据来源为透明国际(清廉指数)、欧盟委员会(数字经济与社会指数)和联合国(电子政务发展指数)。根据相关分析的结果,建立了以下结论:第一,数字技术发展水平越高,国家的腐败感知指数值越低;其次,减少腐败程度取决于公共部门流程数字化的增长。研究结果对公共部门利用创新信息技术完善国民经济中的反腐败体系具有实用价值。
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