Abstract
The integration of Artificial Intelligence (AI) into the criminal justice system is reshaping how law enforcement agencies, courts, and correctional institutions operate. AI-driven technologiessuch as facial recognition systems, predictive policing software, and algorithmic risk assessment toolsare increasingly used to inform decisions related to crime prediction, suspect identification, bail eligibility, and sentencing. These innovations offer the potential for enhanced efficiency, data-driven decisions, and the reduction of human error and prejudice.
However, the deployment of AI in criminal justice also introduces complex legal and ethical challenges that threaten to compromise foundational legal principles. Concerns have been raised about the opacity of algorithmic decision-making, lack of accountability, and embedded biases that may reinforce systemic discrimination, particularly against marginalized groups. The inability to explain how AI reaches its conclusionsoften referred to as the “black box” problemundermines due process and the right to a fair trial. Additionally, the unregulated use of AI in surveillance raises serious questions regarding privacy, freedom of movement, and data protection.
This paper examines these issues through a legal lens, focusing on constitutional protections, human rights obligations, and the pressing need for transparent and enforceable AI governance in the criminal justice domain. It evaluates current national and international frameworks and offers policy recommendations aimed at ensuring that AI enhances, rather than erodes, justice. Ultimately, the paper advocates for a rights-respecting, ethically guided, and legally robust approach to the use of AI in criminal justice systems worldwide.
Keywords- Artificial Intelligence (AI), Criminal Justice System, Predictive Policing, Algorithmic Bias, Risk Assessment Tools, etc.
- Introduction
The modern criminal justice system is undergoing a technological transformation with the increasing adoption of Artificial Intelligence (AI) tools across its various stages—from investigation and policing to adjudication and corrections. AI systems are being used to predict criminal behaviour, assess risks of recidivism, and determine sentencing outcomes, thereby replacing or supplementing human judgment in critical areas of law enforcement and judicial decision-making.[1]
For instance, predictive policing algorithms analyse past crime data to forecast where crimes are likely to occur and who may commit them, allowing law enforcement agencies to allocate resources more efficiently[2]. Courts are also utilizing risk assessment tools like COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) to evaluate a defendant’s likelihood of reoffending and inform decisions on bail and sentencing[3]. Meanwhile, facial recognition technologies are increasingly used to identify suspects in real-time surveillance and public spaces[4].
These applications promise significant advantages: improved efficiency, consistency in decision-making, reduced human bias, and cost-effectiveness. However, the deployment of AI in criminal justice has also raised serious legal and ethical concerns. Key among these are issues related to transparency (how AI systems reach conclusions), bias and discrimination (especially against racial and socioeconomic groups), and lack of accountability when errors occur[5].
Moreover, many of these AI tools operate as “black boxes” their inner workings are inaccessible to users and defendants alike, thereby impeding the right to a fair trial and effective legal defence. These challenges are compounded by the absence of comprehensive legal frameworks governing the use of AI in criminal justice, especially in developing countries like India, where adoption is increasing but regulation remains minimal.
This paper critically examines these concerns through a legal and constitutional lens. It aims to map the evolving legal landscape related to AI in criminal justice, assess the compatibility of AI tools with due process, equal protection, and privacy rights, and propose reforms to ensure that the deployment of AI respects fundamental legal principles and human rights standards.
[1]Casey, B., Farhangi, A., & Vogl, R. (2019). Rethinking Explainable Machines: The GDPR’s “Right to Explanation” Debate and the Rise of Algorithmic Accountability in the United States. Columbia Business Law Review, 2019(1), 1–59.
[2]Ferguson, A. G. (2017). The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement. NYU Press.
[3]Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine Bias. ProPublica. Retrieved from https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
[4]Garvie, C., Bedoya, A., & Frankle, J. (2016). The Perpetual Line-Up: Unregulated Police Face Recognition in America. Georgetown Law Center on Privacy & Technology.
[5]Eubanks, V. (2018). Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin’s Press.