Uses of Artificial Intelligence in Achieving Predictive Criminal Justice According to the Provisions of Jordanian Law

Authors

  • Randa Alsayed El-bheery

DOI:

https://doi.org/10.59759/law.v5i2.1879

Keywords:

Artificial intelligence, Predictive justice, Judicial rulings, Fair trial.

Abstract

  This study aimed to analyze the role of artificial intelligence in achieving predictive justice within the framework of Jordanian law by identifying the possibility of employing smart technologies in supporting the Jordanian judicial process and enhancing its efficiency. The study focuses on the concept of predictive justice as one of the tools that is based on analyzing judicial precedents in order to reuse their data to predict future judicial rulings, while discussing the ethical and legal challenges resulting from the use of such technologies 

For this purpose, the study used both the analytical and descriptive approaches to collect relevant Jordanian legal texts for use in the study. The study reached several conclusions, the most important of which is that artificial intelligence algorithms cannot perform the process of investigation and inference according to the provisions of the Jordanian Code of Criminal Procedure under penalty of invalidity unless they are used as one of the means within that process and not as standalone tools. Therefore, it recommended enacting some legal texts that allow judicial bodies to accept the use of artificial intelligence algorithms, so that flexibility is the basis for the use of predictive criminal justice in the Jordanian judiciary. 

 

 

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References

Alexandra Chouldechova, Fair prediction with disparate impact: A study of bias in recidivism prediction instruments, https://www.andrew.cmu.edu/user/achoulde/files/disparate_impact.pdf

Commission européenne pour l'efficacité de la justice, Charte éthique européenne d'utilisation de l'intelligence artificielle dans les systèmes judiciaires et leur environnement, Conseil de l'Europe, op. cit.

Kadar, C., Maculan, R., & Feuerriegel, S. (2019). Public: Decision support for low population density areas: an imbalance-aware hyper-ensemble for spatio-temporal crime prediction. Decis. Support Syst. 107.

Larson, Jeff, Surya Mattu, Lauren Kirchner, and Julia Angwin. (2018). How We Analyzed the COMPAS Recidivism Algorithm, Northeastern University Library, https://perma.cc/BGA6-D6J7

Paris Innovation Review « La justice prédictive, ou quand les algorithmes s'attaquent au droit », publié le 9 juin 2017, p. 2. Disponible en ligne le 29 octobre 2022 sur http://parisinnovationreview.com/article/justice-predictive-les-algorithmes-sattaquent-au-droit.

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Published

2026-07-26

How to Cite

Alsayed El-bheery, R. (2026). Uses of Artificial Intelligence in Achieving Predictive Criminal Justice According to the Provisions of Jordanian Law. Political Sciences and Law Series, 5(2). https://doi.org/10.59759/law.v5i2.1879