Artificial Intelligence in Criminal Investigations: Legal Implications for Evidence Admissibility, Accountability, and Protection of Fundamental Human Rights
DOI:
https://doi.org/10.70062/jccl.v1i3.141Keywords:
Accountability, Artificial Intelligence, Criminal Investigation, Evidence Law, TransparencyAbstract
The rapid development of Artificial Intelligence (AI) has brought significant changes to the criminal justice system, particularly in criminal investigations and evidentiary processes, while simultaneously raising complex legal and ethical challenges. Objective: This study aims to analyze the legal implications of the use of AI in criminal investigations, focusing on its benefits, risks, and challenges related to the admissibility of AI-based evidence, as well as the need for regulatory frameworks that ensure fairness, transparency, and accountability. Methods: This research employs a normative qualitative approach through the analysis of legal regulations, a review of legal and technological literature, and a comparative approach across jurisdictions, complemented by case studies of AI applications in law enforcement practices. Results: The findings indicate that AI enhances investigative efficiency through data analysis, crime prediction, and digital forensics; however, it also poses risks such as algorithmic bias, human rights violations, and issues concerning the reliability and transparency of evidence. Furthermore, differences across legal systems result in the absence of uniform standards for the admissibility of AI-based evidence. Therefore, adaptive regulatory frameworks grounded in the principles of fairness, transparency, and accountability are required, along with strengthened human oversight to ensure that the use of AI aligns with the principles of justice and human rights protection.
Downloads
References
Allen, R. J., Pardo, M. S., Lawrence, W. J., & Smiciklas, C. K. (2025). Minimal rationality and the law of evidence. Journal of Criminal Law and Criminology, 115(2), 269–315.
Andriati, S. L., Rizki, I. K., & Malian, A. N. B. M. (2024). Justice on trial: How artificial intelligence is reshaping judicial decision-making. Journal of Indonesian Legal Studies, 9(2), 909–942. https://doi.org/10.15294/jils.v9i2.13683
Bakkannavar, S., Parekh, U., & Gupta, S. (2025). Unveiling truth of artificial intelligence in forensic medicine and education: Better late than never. Journal of Forensic Medicine and Toxicology, 42(1), 127–132. https://doi.org/10.48165/jfmt.2025.42.1.19
Danišauskas, G. (2017). Towards safety of society: Rethinking principles of police financing. Journal of Security and Sustainability Issues, 7(2), 23–30. https://doi.org/10.9770/jssi.2017.7.2(3)
de Albuquerque, V. H. C., Kumar, B., Ghosh, M., Barman, S., & Jha, A. (2025). A primer on responsible AI. In A compendium of responsible artificial intelligence (pp. 1–27). https://doi.org/10.1201/9781003514497-1
Dhamo, A., Dhamo, I., & Manastirliu, I. (2023). Fundamental rights and new technologies. Interdisciplinary Journal of Research and Development, 10(3), 121–125. https://doi.org/10.56345/ijrdv10n319
Eddyono, S. W. (2024). The relationship between human rights and criminal law: A human rights-based criminal justice system. In International human rights and local courts: Human rights interpretation in Indonesia (pp. 114–135). https://doi.org/10.4324/9781003431350-7
Ersoz, F., Ersoz, T., Marcelloni, F., & Ruffini, F. (2025). Artificial intelligence in crime prediction: A survey with a focus on explainability. IEEE Access, 13, 59646–59674. https://doi.org/10.1109/ACCESS.2025.3553934
Fardin, S. J., & Filippi, C. G. (2024). Societal view. In Impact of artificial intelligence in radiology (pp. 199–203). https://doi.org/10.1201/9781003095279-39
Gentelet, K., & Mizrahi, S. K. (2024). A human-centered approach to AI governance. In Human-centered AI (pp. 215–230). https://doi.org/10.1201/9781003320791-24
Górski, Ł., & Ramakrishna, S. (2021). Explainable artificial intelligence: Lawyer’s perspective. In Proceedings of ICAIL (pp. 60–68). https://doi.org/10.1145/3462757.3466145
Górski, Ł., Ramakrishna, S., & Nowosielski, J. M. (2021). Towards Grad-CAM based explainability. In Lecture Notes in Computer Science (Vol. 13048, pp. 154–168). https://doi.org/10.1007/978-3-030-89811-3_11
Gupta, M., Sood, R. P., & Singh, R. (2025). AI in criminal investigation. In Rethinking the police (pp. 311–323). https://doi.org/10.1007/978-3-031-83173-7_21
Karunanithi, K., & Rajamanickam, R. (2024). Admissibility of illegally obtained evidence. International Journal of Public Law and Policy, 10(2), 116–144. https://doi.org/10.1504/IJPLAP.2024.137775
Kolthoff, E., & Janssen, J. (2023). Police corruption and human rights. In Applied human rights (pp. 299–321). https://doi.org/10.3920/978-90-8686-943-5_17
Kovatcheva, D. (2024). AI and human rights protection. Economic Alternatives, 30(2), 439–468. https://doi.org/10.37075/EA.2024.2.12
Matulionyte, R., & Hanif, A. (2021). Explainable AI in law enforcement. In IEEE EDOC Workshop (pp. 75–80). https://doi.org/10.1109/EDOCW52865.2021.00035
Meduri, K., Podicheti, S., Satish, S., & Whig, P. (2024). Accountability in AI. In Ethical dimensions of AI (pp. 83–102). https://doi.org/10.4018/979-8-3693-4147-6.ch004
Monika, E., & Rajesh Kumar, T. (2024). AI-based crime detection. In ICECA 2024 Proceedings (pp. 1557–1562). https://doi.org/10.1109/ICECA63461.2024.10800911
Nugeraha, Z. A. D., Marisa, D., Ayunistia, S., & Baan, B. B. (2025). AI in judicial decision-making. Engineering Proceedings, 107(1), 103. https://doi.org/10.3390/engproc2025107103
Padilla, S. D. F., Andrade, A. R. R., Cajo, F. R. H., Silva, R. D. B., & Ashqui, A. L. M. (2025). AI in judicial decision-making: A systematic review. Anales de la Academia de Ciencias de Cuba, 15(3), e3138.
Padovan, P. H., Martins, C. M., & Reed, C. (2023). AI liability. Artificial Intelligence and Law, 31(1), 133–167. https://doi.org/10.1007/s10506-022-09308-9
Paramjeet. (2023). Evidence laws analysis. MSW Management, 33(1), 187–193. https://doi.org/10.7492/keabsn38
Patel, K., Parikh, H., Dodiya, K. R., Patel, D., & Patel, A. (2025). AI in forensic science. In Combating cyberbullying with generative AI (pp. 365–388). https://doi.org/10.4018/9798337305431.ch013
Raja, A. K., & Zhou, J. (2023). AI accountability. Computer, 56(4), 61–70. https://doi.org/10.1109/MC.2023.3238390
Rama, T., & Prinsloo, T. (2025). FATE in AI. In Lecture Notes in Electrical Engineering (Vol. 1385, pp. 153–167). https://doi.org/10.1007/978-981-96-5066-8_11
Rankin, S. M. G. (2025). Criminal investigations. In Elgar encyclopedia of AI and law (pp. 143–148). https://doi.org/10.4337/9781035336906.00041
Riekkinen, J., & Söderholm, S. (2023). AI and evidence law in Finland. Revue Internationale de Droit Penal, 287–314.
Rodrigues, R. (2020). Legal and human rights issues of AI. Journal of Responsible Technology, 4, 100005. https://doi.org/10.1016/j.jrt.2020.100005
Rohatgi, S., Shrivastava, S., & Singla, S. (2022). Penology and justice. In Crime scene management (pp. 367–405). https://doi.org/10.1007/978-981-16-6683-4_14
Saini, K., Sonone, S. S., Sankhla, M. S., & Kumar, N. (2024). AI in forensic science. https://doi.org/10.4324/9781003287810
Sampaio, R. X. M. (2025). AI and admissibility of evidence. Revista do CAAP, 30(2). https://doi.org/10.69811/8bmk6478
Sawalhi, G., Abdallah, M., & Barqawi, L. (2025). AI ethical regulations. In ICCIAA Proceedings. https://doi.org/10.1109/ICCIAA65327.2025.11013404
Sierocka, H. (2025). Legal and ethical issues of AI. Bialostockie Studia Prawnicze, 30(4), 177–195. https://doi.org/10.15290/bsp.2025.30.04.11
Silva, S. R., & Vadillo, D. C. (2024). AI and judiciary. Revista de Internet, Derecho y Política, 41. https://doi.org/10.7238/idp.v0i41.426865
Singh, V., et al. (2023). AI in criminal investigation. In IEEE Proceedings. https://doi.org/10.1109/iQ-CCHESS56596.2023.10391288
Sorvatzioti, D. F. (2021). Free evaluation of evidence. International Criminal Law Review, 22(5–6), 895–919. https://doi.org/10.1163/15718123-bja10109
State, L., et al. (2025). Explanation dialogues under GDPR. Artificial Intelligence and Law. https://doi.org/10.1007/s10506-024-09430-w
Stoica, A. (2025). Loyalty of evidence. Studia Iuridica Lublinensia, 34(4), 211–226. https://doi.org/10.17951/sil.2025.34.4.211-226
Studzińska, J. (2024). AI in civil procedure. Frontiers in AI and Applications, 396, 446–452. https://doi.org/10.3233/FAIA241371
Thomas, A. (2024). AI-driven judicial decision making. In AI-driven decision making (pp. 337–351). https://doi.org/10.4018/979-8-3693-0639-0.ch015
Turner, J. (2025). Algorithmic evidence. In Elgar encyclopedia of AI and law (pp. 28–32). https://doi.org/10.4337/9781035336906.00013
Voitovich, L. V., Nakhova, E. A., & Silina, E. V. (2023). Burden of proof. Vestnik SPb University Law, 14(4), 1062–1076. https://doi.org/10.21638/spbu14.2023.414
Xu, Z. (2022). Human judges in AI era. Applied Artificial Intelligence, 36(1), 2013652. https://doi.org/10.1080/08839514.2021.2013652
Yadav, A., Yadav, P., & Yadav, D. (2024). AI in criminal justice in India. In Lecture Notes in Networks and Systems (Vol. 1085, pp. 379–389). https://doi.org/10.1007/978-981-97-6726-7_30
Yasynok, D., et al. (2025). Standard of proof. Law of Justice Journal, 39(1), 125–152. https://doi.org/10.5335/rjd.v39i1.16882
Zarosylo, V. O., et al. (2020). Law enforcement reform in Ukraine. Asia Life Sciences, Supp. 22(2), 791–800
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Journal of Civil Criminal Law
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
