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Prevention of judicial errors and their prevention using AI

Author

Listed:
  • Natalya Sidorova
  • Larissa Kussainova
  • Sergey Bachurin
  • Evgeniy Shulgin
  • Ainura Omarova

Abstract

The article is devoted to the study of the possibilities of digitalization, artificial intelligence in preventing judicial errors and increasing access to justice. The study emphasizes the importance of digital technologies in the legal sphere, including the automation of judicial processes and modeling of judicial decisions, being an important step to ensure justice. The literature review analyzes international experience in using digital tools in various sectors, including the legal system, and identifies their potential for minimizing judicial errors. The research methodology is based on the use of predictive analysis of the integration of artificial intelligence into the judicial system, as well as a comparative analysis of foreign experience. The results show that digitalization of artificial intelligence-based systems, can increase the efficiency and transparency of justice, improve the quality of decisions and reduce the number of judicial errors. The discussion focuses on the need to adapt international experience to Kazakhstan's realities and develop a regulatory framework for the integration of artificial intelligence into the judicial system. The analysis highlights that successful digitalization requires a comprehensive approach, including technology development, training of specialists and creation of a transparent legal framework, suggesting directions for future work in the field of digitalization of justice, emphasizing the importance of interaction between people and technology.

Suggested Citation

  • Natalya Sidorova & Larissa Kussainova & Sergey Bachurin & Evgeniy Shulgin & Ainura Omarova, 2025. "Prevention of judicial errors and their prevention using AI," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(1), pages 841-853.
    • Handle: RePEc:aac:ijirss:v:8:y:2025:i:1:p:841-853:id:4429
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