This essay is written by HIMANSHU YADAV, a Law student at TNNLU, Trichy. and he seeks first position in Online Legal Essay Writing Competition by Lawfer 2025.
I. Introduction
The emergence of Artificial Intelligence (AI) has changed nearly all dimensions of human venture – there is perhaps no area recently transformed more than in the judiciary system worldwide. Courts around the globe are experimenting with AI to increase efficiency, manage backlog, and create consistency in decision-making. The potential for AI to support judicial officers in India, where there are more than five crore pending cases in courts (National Judicial Data Grid, 2025), is significantly high. However, the use of AI to assist in undermining judicial decision-making presents very serious constitutional, ethical, and legal issues around due process of law, transparency, accountability, and independence.
This paper will critically evaluate the opportunities presented from the use of AI into the judicial process and also the constitutional implications, test it against the Constitution of India, and also gauge it against global developments.
II. Understanding Judicial AI: From Automation to Augmentation
The role of Artificial Intelligence in our court system does not take the place of judges, but rather complements decision-making in legal processes. There are three levels of judicial AI:
1. Administrative AI – this level refers to the automation of repeatable tasks (e.g. court scheduling, document organizing, or making a cause list) with the best example being the SUPACE system developed in India to automate these tasks.
2. Analytical AI – Judges can use this category of AI to find case laws and background based on the issues in a dispute (e.g. SUPACE with the Supreme Court of India).
3. Decisional AI – the Decisional AI category can help predict results or promote a suggested sentence based on statistics and data. Examples of decisions AI include COMPAS in the United States and PROMETHEE in France.
Although the first two categories are efficient, a third category of AI can suggest or influence decisions and raises potential constitutional issues.
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Also Read: Recent Amendments and Landmark Judgments in Indian Evidence Law
III. AI in the Indian Judiciary: Current Developments
The Indian legal system has taken a cautious approach to the use of AI tools:
SUPACE (Supreme Court Portal for Assistance in Courts Efficiency) was initiated in 2021 by former Chief Justice S. A. Bobde. SUPACE introduces a form of AI to assist judges in legal research by summarizing facts and case law, but does not determine an outcome.
SUVAAS is an AI translation tool developed to translate judgments into regional language, as a means of enhancing accessibility guaranteed under Article 19(1)(a).
The National Judicial Data Grid (NJDG) uses data analytics to identify backlogged cases, and assess judicial performance.
While these tools are a step in the right direction, India has not yet resorted to predictive or decisional AI, largely attributable to sensitivities around issues of bias, data integrity and values espoused by the Constitution.
IV. Opportunities: Efficiency, Consistency, and Access to Justice
A. Minimizing Backlogs and Increasing Efficiency
AI can greatly expedite legal and documentary review, legal research, and drafting of judgments. The 2023 NITI Aayog report stated that automating routine judicial functions could decrease backlog by as much as 25% in a five-year horizon. By instantly analyzing laws and precedents, justice delivery would be quicker and ultimately realize the constitutional purpose of speedy trials, as stated in Article 21.
B. Relying on Consistency in Judicial Outcomes
Judicial consistency, particularly with sentencing, is a continued concern. AI models can ultimately ensure that similar cases have similar cases, reducing arbitrariness and increasing public trust in the system. The U.S. Sentencing Commission has shown that algorithmic sentencing can aid consistency, although with caution.
C. Improving Access and Transparency
AI-powered translation, legal assistance, and case management tools provide unaffected levels of access to justice, especially for marginalized groups. Programs like SUVAAS channel the principles defined in the state policy (Article 39A), which promote equal justice and free legal aid.
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V. Constitutional and Legal Challenges
While there are many possibilities, the use of AI in judicial decision-making presents certain deep constitutional challenges.
A. Violation of Due process under Article 21
In Maneka Gandhi v. Union of India [(1978) 1 SCC 248] the Supreme Court broadened Article 21 to include the right to a fair and a reasonable procedure. If parties do not know how AI affected judicial reasoning, the secrecy of the AI algorithms – often termed the “black box” problem – could violate procedural fairness and due process rights.
B. Judicial Independence and Accountability
Article 50 of the Constitution requires separation between the judiciary and executive. The involvement of AI systems that may have been developed by executive agencies could potentially compromise that constitutional separation. Also complicating this issue is the question of accountability for an AI-assisted judicial decision- is it the responsibility of the programmer, the developer, or the judge? In answering this question, we must recognize the attribution of legal accountability is complex.
C. Algorithmic Bias and Discrimination
Apart from marginalizing voices in the judicial process, AI systems learn from existing historical data, which is likely to present social bias. In State of Uttar Pradesh v. Raj Narain [(1975) 4 SCC 428], the Supreme Court noted that the right to know or the right to information is fundamental to democracy. If the developing software of AI systems is opaque and possibly discriminatory, and if the AI is merely trained on datasets which may include bias, AI could exacerbate systemic injustice in a way that violates Articles 14 and 15.
D. Data Protection and Privacy Concerns
Following the implementation of the Digital Personal Data Protection Act, 2023, judicial data is considered sensitive personal information. The unfettered and large-scale use of judicial data in artificial intelligence systems poses significant threats to privacy – a recognized constitutional right in K.S. Puttaswamy v. Union of India [(2017) 10 SCC 1]. Consequently, judicial AI must adhere to the principles of data minimization, purpose limitation, and consent-based processing of personal data.
VI. Global Comparative Perspective
A. United States: Predictive Policing and Sentencing
In the United States, recidivism risk assessment tools, such as COMPAS, are used during the sentencing hearing stage. However, the Wisconsin Supreme Court held in State v. Loomis (2016) that the trial court should exercise caution in relying heavily on opaque algorithms, and that the defendants should be informed of the limitations of AI-generated risk assessments.
B. European Union: Ethical Regulation of AI
Under the EU’s Artificial Intelligence Act (2024) for instance, it categorizes judicial applications of AI, as a “high-risk system,” which entails strict requirements for data and algorithmic transparency, human oversight, and accountability. This model offers practical guidelines and insights for India, which does not have a comparable legal framework.
C. China: AI-Powered Courts
China’s so-called “Smart Courts” utilize algorithms to help evaluate evidence, and settle disputes online. However, this level of automation and reliance on algorithms brings forward the question of the necessity of human judicial discretion as an element of one of the core elements of natural justice (namely, the right to a fair hearing), which Indian courts have recognized as intrinsic to the conditions for the fair administration of justice.
VII. Judicial Interpretation and AI: Can Machines Interpret Law?
Legal interpretation includes human values, empathy, and moral reasoning– attributes that cannot be replicated by algorithms. For example, in Union of India v. R. Gandhi [(2010) 11 SCC 1], the Court held that adjudication involves than a mechanical task, and requires application of the judicial mind. Machine learning systems lack certain qualitative judgments, rendering AI unconstitutionally unsuitable to substitute winners of discretion.
We must also consider that the doctrine of stare decisis to avoid instability in the law cannot rest upon machine learning systems to reproduce precedents without understanding the context and the socio-legal reasoning behind those decisions. Machine learning analytical and/or judgement is effectively a mechanism for mechanical justice with no empathy.
VIII. Towards a Constitutional Framework for Judicial AI
In order to implement AI integration within the framework of constitutional requirements, India requires a legal framework that encompasses the following:
1. Human Oversight: Judges must maintain ultimate control and accountability for AI-informed determinations.
2. Algorithmic Transparency: The AI systems utilized in courts must be required to disclose the parameters used in their decision-making processes, to maintain procedural fairness.
3. Data Protection: There must be adherence to the Digital Personal Data Protection Act, and secure treatment of judicial data.
4. Ethical and Technical Standards: The AI Ethics Commission for the Judiciary should be established to govern and certify AI tools designed for the judiciary.
5. Training and Capacity Building: The Judicial Officer must be provided training in AI literacy to ensure the competent use of technological tools.
IX. The Way Forward: Harmonizing Technology with Justice
Chief Justice D.Y. Chandrachud has consistently argued for a “judiciary that is technologically empowered, yet human-centered.” The challenge is to take advantage of the potential of AI while upholding human judgment, empathy, and constitutional morality. In Navtej Singh Johar v. Union of India [(2018) 10 SCC 1], the Supreme Court endorsed the view that the Constitution is a “living document” and can evolve in response to changes in society. The same holds true for the process of evolution of the judiciary, and the challenges it faces, while retaining its human aspect.
X. Conclusion
Artificial Intelligence holds uncharted possibilities for reforming the judiciary– speed, consistency, transparency. These aspects must nonetheless be ensured within a constitutional framework as part of decision-making. The difference presently facing the Indian judiciary is whether AI can be accepted as an assistive tool rather than a replacement in the absence of judicial conscience. A robust legal and ethical framework based on Articles 14, 19, 21 and 50 can even strengthen rather than replace the rule of law if AI does not supplant the conscience of the judiciary.
As Justice Krishna Iyer said, “Technology is a good servant and a dangerous master.” The challenge for the Indian judiciary is to continue to ensure that AI is the former, that it assists in the pursuit of justice and avoid becoming the latter– the making of judgment.
References:
1. Maneka Gandhi v. Union of India, (1978) 1 SCC 248.
2. K.S. Puttaswamy v. Union of India, (2017) 10 SCC 1.
3. State v. Loomis, 881 N.W.2d 749 (Wis. 2016).
4. Union of India v. R. Gandhi, (2010) 11 SCC 1.
5. Navtej Singh Johar v. Union of India, (2018) 10 SCC 1.
6. State of Uttar Pradesh v. Raj Narain, (1975) 4 SCC 428.
7. EU Artificial Intelligence Act, 2024.
8. Digital Personal Data Protection Act, 2023 (India).
9. National Judicial Data Grid (NJDG) Statistics, 2025.
10. NITI Aayog, AI for All: Strategy for India, 2023.