ABSTRACT
The right to access timely information, protection, participation and redress are key to a fair criminal justice system of victims. Machine learning (ML) can provide the means of enhancing the victimization detection, tailoring support, predicting the risk of becoming a victim (e.g., in domestic violence), and minimum resource allocation. Nevertheless, historical bias, loss of privacy, and diminished participation or procedural justice are also potential outcomes of unprotected use of ML systems. This article summarizes the recent information on ML applications in the area of victim protection, suggests a victim-centered ML framework that should stress its transparency, fairness, and privacy-by-design, and provides an implementation roadmap along with legal and ethical guardrails. Suggestions include human control, auditability, participatory design with survivors, and legal protection to help ML empower, instead of undermine, the rights of survivors.
Keywords: Victim rights, machine learning, criminal justice, fairness, transparency
- INTRODUCTION
The emergence of machine learning (ML) is a turning point in the criminal justice system, as it allows shifting law enforcement to proactive victim protection. Machine learning algorithms are also a subset of the larger field of artificial intelligence and examine large volumes of data to identify trends in criminal behaviour, forecast at-risk zones, and customize victim services. These technologies have made judicial processes efficient, transparent, and just and have resolved historical issues of underreporting of crimes, lack of resources, and the delay in the delivery of justice[1].
ML is being introduced in law enforcement and judicial processes worldwide to aid in predictive policing, assessing the risk to victims, and identifying threats in real-time. An AI-based system is used to assist case management, legal research, and victim counselling interfaces in India and elsewhere to provide timely psychological and procedural advice. With the evolution of crime in terms of complexity and transnationalism, especially in areas such as human trafficking and cybercrime, ML models are important to mark vulnerable groups and link them to preventive and remedial systems[2][3][4].
Nevertheless, although this prospect of ML in enhancing the rights of the victims is quite important, it should be restrained by the moral control. The issues of privacy, bias in the algorithms, and automated profiling explain the importance of establishing governance mechanisms that would guarantee the dignity of the victims, justice, and responsibility. An ethical approach to machine learning hence incorporates a balanced understanding of technology effectiveness and constitutional values and procedural justice. It is a cross-section of law, technology, and human rights, which is the new paradigm of AI-assisted victim protection a paradigm shift intended to bring to life compassionate justice with the help of computational intelligence.
The rights of the victims are a crucial component of the criminal justice system that guarantees that the victims of the crime receive justice, dignity, and fair treatment. The right to information, the right to participate in the proceedings and the right to compensation or rehabilitation have all been included in the idea of victim rights. Nevertheless, even when legal frameworks and institutional apparatus are progressive, victims report to face systemic hurdles like delays in the system, secondary victimization, and failure of justice agencies to communicate with the victim in a timely manner.
Criminal cases in the modern world have grown more complicated, with large volumes of digital evidence and cross-jurisdictional crime as well as data-intensive crime investigations. Such intricacy can usually cause strain among customary procedures of inquiry, prosecution, and support of victims. As a result, the need to have a technological intervention to enhance efficiency, accuracy and responsiveness of the justice delivery systems is increasing.
Machine Learning (ML) as the branch of Artificial Intelligence (AI) has become the game changer, having the ability to process vast amounts of data, detect latent patterns, and contribute to making informed decisions. ML used in a proper manner may lead to an increased level of protection of the victims and include predicting possible risks, customizing support services, streamlining routine administrative procedures, and prompt response to re-victimization or domestic violence. Nevertheless, unless they are ethically and legally protected, these technologies have a risk of violating privacy and sustaining discrimination.
[1] TECHUK, https://www.techuk.org/resource/all-you-need-to-know-about-ai-adoption-in-criminal-justice.html, (last visited Oct. 20, 2015)
[2] NJAGOV, https://nja.gov.in/Concluded_Programmes/2021-22/P-1281_PPTs/2.Introduction%20of%20Artificial%20Inteligence%20in%20the%20Judicial%20System.pdf
[3] Kristen Bell, Jenny Hong, Nick McKeown, Catalin Voss, A New Direction for Machine Learning in Criminal Law, HAI STANFORD UNIVERSITY 1-7, (2021).
[4] Muskan Shokeen, Vinit Sharma, Artificial intelligence and criminal justice system in India: A critical study, 5 INTERNATIONAL JOURNAL OF LAW, POLICY AND SOCIAL REVIEW 156-162, (2023).