Perspectives of the application of artificial intelligence in civil legal proceedings: risk assessment and the method of their mitigation
- Authors: Danielyan A.S.1
-
Affiliations:
- Kuban State University
- Issue: No 4 (2024)
- Pages: 192-196
- Section: Scientific reports
- URL: https://journals.rcsi.science/1026-9452/article/view/260996
- DOI: https://doi.org/10.31857/S1026945224040181
- ID: 260996
Open Access
Access granted
Abstract
The goal of this study is to explore the current state and prospects for the use of artificial intelligence (Artificial intelligence, AI) in the framework of the administration of justice, in particular, in civil proceedings. In light of constantly changing social relations and the growing need to use modern technologies in various areas of life, including legal ones, it is important to understand what opportunities artificial intelligence can provide to improve legal proceedings and ensure the protection of citizens’ rights. The use of an artificial intelligence system in legal activities
has a number of advantages, such as speeding up the decision-making process, increasing the accuracy and objectivity of decisions made, and improving the accessibility of justice. However, it is also necessary to take into account possible disadvantages, for example, the risk of data privacy violations and the possibility of errors in the algorithms, which can lead to an unfair decision. The final conclusion of the study is that the use of information technology and
artificial intelligence systems should not be considered an end in itself but should be introduced as part of a strategy
to improve the legal system and increase the effectiveness of the protection and restoration of the rights of subjects
of legal relations. In addition, it is necessary to take into account the social and ethical aspects of legal proceedings.
Full Text
About the authors
Armen S. Danielyan
Kuban State University
Author for correspondence.
Email: armen1992@mail.ru
PhD in Law, Associate Professor of the Department
of Civil Procedure and International Law at Kuban State University
References
- Biryukov P. N. Artificial intelligence and “predicted justice”: foreign experience // Lex russica. 2019. No. 11. Pp. 79–87 (in Russ.).
- Biryukov P. N. Digitalization of justice in civil cases: EU experience // Arbitration and Civil Procedure. 2022. No. 2. Pp. 3–7 (in Russ.).
- Krisko V. S. On the issue of the implementation of the principle of accessibility of justice and the creation of a unified information space of the judicial system // Court Administrator. 2019. No. 1. Pp. 54–56 (in Russ.).
- Momotov V. V. Artificial intelligence in legal proceedings: state, prospects of use // Herald of Kutafin University (MSLA). 2021. No. 5. Pp. 188– 191 (in Russ.).
- Howard D., Guger S. Deep learning with fast ai and PyTorch: minimum formulas, minimum code, maximum efficiency. SPb., 2022 (in Russ.).
- Chudinovskaya N. A. Some directions of digitalization of justice in Russia and the EU countries // Arbitration and Civil Procedure. 2022. No. 7. Pp. 7–9 (in Russ.).
- Bogert E., Schecter A., Watson R. T. Humans rely more on algorithms than social influence as a task becomes more difficult // Science Reports. 2021. No. 11. P. 8028.
- Heaven W. D. Predictive policing algorithms are racist. They need to be dismantled // MIT Technology Review. 2020. No. 3.
- Godwin J. Position of Artificial Intelligence in Justice System: Justice of the Future. URL: https://nji.gov.ng/wp-content/uploads/2021/12/Position-of-Artificial-Intelligence-in-Justice-System-Justice-of-the-Future-by-Joel-Gogwim.pdf
- Jones N. AI science search engines expand their reach // Nature News. 2016. No. 11.
- Lee S., Lu X., Reijers Hajo A. The Analysis of Online Event Streams: Predicting the Next Activity for Anomaly Detection // arXiv. 2022. No. 3. Pp. 1–10.
- Lim S. Judicial Decision-Making and Explainable Artificial Intelligence // Singapore Academy of Law Journal. 2021. No. 33. P. 313.
- Pagano T. P., Loureiro R., Lisboa F., et al. Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods // Big Data and Cognitive Computing. 2023. Vol. 7. No. 1. P. 15.
- Reiling A. D. Courts and Artificial Intelligence // International Journal for Court Administration. 2020. Vol. 11. No. 2. P. 8.
- Richardson R., Schultz J., Crawford K. Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice // New York University Law Review. 2019. Vol. 94. Pp. 192–233.
- Yu Z., Xi X. A Pilot Study on Detecting Unfairness in Human Decisions with Machine Learning Algorithmic Bias Detection // arXiv. 2021. No. 12. Pp. 1–9.
