Artificial Intelligence And Judicial Integrity: Evaluating The Impact, Risks And Implications Of AI Integration In Modern Court Systems

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Author(s): Asenath Chitunzi Anesu

Paper Details: Volume 3, Issue 4

Citation: IJLSSS 3(4) 27

Page No: 295 – 307

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ABSTRACT

In a visionary statement, the Hon’ble Prime Minister of India, Shri Narendra Modi stated that “Technology will integrate police, forensics, jails, and courts, speeding up their work; hence we are moving towards a justice system that will be fully future-ready.”[1] This statement reflects the growing rate of the digital transformation of India’s legal and judicial infrastructure. Among the most transformative technologies in this shift is Artificial Intelligence (AI), which is increasingly becoming a driving force in the functioning of India’s Judiciary. AI applications are now being implemented to assist in tasks such as legal research, predictive policing, case management, and even judicial decision-making. While these advancements offer immense potential in terms of efficiency, backlog reduction, and resource optimization, they also raise critical legal and ethical concerns. The chief among these concerns is the question, “To what extent could the use of Artificial Intelligence in judicial processes jeopardize the integrity, fairness, and accountability of court systems?” This inquiry lies at the heart of contemporary legal discourse, particularly in jurisdictions where the rules of law, due process, and judicial impartiality are cornerstones of constitutional democracy. This research article seeks to critically examine the impact of Artificial Intelligence (AI) on judicial decision making. It will assess whether the integration of AI without sufficient legal safeguards and human oversight could undermine core principles such as the right to a fair trial and equality before the law. The research is based on doctrinal legal research methodology analyzing constitutional provisions and international legal standards to evaluate the implications of AI on judicial integrity. As India progresses toward a technologically advanced legal system, it becomes of importance to strike a balance between innovation and the preservation of constitutional values.

Key Words: Artificial Intelligence, Judicial Integrity, Constitutional Values, Court System Accountability, Legal Ethics, Judicial Transparency, Fair Trial

INTRODUCTION

The integration of Artificial Intelligence into the modern court system represents a significant step forward in legal innovation. As AI technologies continue to evolve, they are transforming how justice is administered by automating tasks that were once solely handled by humans. In today’s judicial environment marked by increasing complexity, expanding caseloads, and mounting public expectations AI offers the potential to improve the efficiency, accuracy, and accessibility of court proceedings. For example, in India, where the judiciary faces a critical backlog exceeding 40 million cases, delayed hearings and restricted legal access for marginalized groups have contributed to a credibility crisis in the justice system. This has risen concerns of an urgent need for modernization. AI provides a valuable opportunity to revamp court operations by supporting case management, accelerating legal research, and enabling data driven judicial decision making.

Moreover, the modern court systems are beginning to leverage AI for several critical functions and these are that AI tools can quickly analyze vast volumes of legal data, assist in drafting and reviewing documents, and even predict legal outcomes based on historical precedents. These capabilities can help judges and legal professionals save time, reduce human error, and ensure more consistent judgments. Additionally, AI enabled e-courts and virtual hearings have become increasingly prominent, offering flexible and inclusive legal services especially beneficial for individuals in remote regions or those with limited resources.

However, while the modernization of courts through AI brings many advantages, it also raises serious ethical and legal concerns. These include issues like algorithmic discrimination, lack of transparency in decision making, and the risk of excessive dependence on automated systems must be addressed to maintain public trust in the judicial process. They arose the need for the modern court to adopt a balanced approach harnessing AI’s capabilities while establishing safeguards to ensure fairness and accountability. Also, to ensure that AI integration aligns with the core values of justice, legal professionals need training to work effectively with these technologies. Additionally, the development and deployment of AI systems must be guided by clear regulatory frameworks that promote transparency, protect data privacy, and guard against systemic bias.

UNDERSTANDING THE ORIGIN OF ARTIFICIAL INTELLIGENCE IN THE JUDICIAL CONTEXT

Artificial Intelligence refers to the use of computer systems to mimic human cognitive functions such as reasoning, learning, and language understanding. The core AI technologies like machine learning allow systems to learn from data patterns, while natural language processing enables interaction using human language. The concept of Artificial Intelligence has evolved significantly since its origins in the mid-20th century with thinkers like Alan Turing 1950 paper on “Computing Machinery and Intelligence”[2] and John McCarthy who laid the foundational ground and coined the term Artificial Intelligence and the 1956 Dartmouth Conference, which is considered the birth of AI as a field[3].

The application of AI in modern court systems, especially through expert systems, began in the 1970s as early computer programs were created to simulate the reasoning of legal professionals. One of the first such systems was the Taxman Project at Stanford University, which focused specifically on tax law interpretation. Also, the British Nationality Act as a Logic Program, was another pivotal event which showcased how AI could be used to apply statutory law through logical programming. These initial efforts laid the groundwork for further AI advancements in legal settings. Moreso, in the 1980s, Artificial Intelligence began to reshape legal research practices with the introduction of tools like LexisNexis and Westlaw. These platforms used early AI methods to organize, classify, and retrieve legal documents efficiently. For the first time, legal professionals could conduct in-depth research within minutes, transforming the way legal information was accessed and significantly reducing the time and effort needed for case preparation[4].

Furthermore, in the 1990s and early 2000s they saw further expansion of AI in law through the development of legal automation tools. These technologies began to take over routine administrative tasks such as document preparation, billing, and case scheduling, thus by automating such functions, AI helped legal offices improve workflow efficiency and reduce the burden of repetitive, time-consuming activities. A major breakthrough occurred in the late 2000s with the integration of Natural Language Processing (NLP) into legal AI systems. NLP enabled machines to better understand the structure, context, and meaning of human language, allowing for more accurate analysis of legal texts. This advancement significantly enhanced tasks like contract review, risk assessment, and regulatory compliance checks by providing deeper insights into legal language. In the current era, the legal sector has embraced machine learning a subset of AI that enables systems to learn from data and improve over time. Machine learning is now widely used in legal analytics to predict case outcomes, examine past judgments, and assist in strategic decision-making. These tools offer capabilities that go far beyond human processing limits, marking a shift toward data-driven law practice. Alongside these technological advancements, there is growing awareness of the ethical challenges associated with AI in law. As AI becomes more involved in legal decision-making, concerns have emerged regarding algorithmic bias, data security, and the transparency of automated processes. Ensuring that AI systems are used responsibly has become a central issue, prompting discussions around the need for strong governance, regulation, and ethical frameworks within the legal industry.

TRANSFORMATIVE AI TOOLS RESHAPING THE LEGAL PROFESSION AND THE MODERN COURTROOM

The rapid development of artificial intelligence (AI) has had a major impact on the legal field, an area traditionally known for its complexity and time-consuming processes. As legal systems face growing demands for speed and efficiency, AI tools like Natural Language Processing, Machine Learning, and AI-based decision support systems are becoming valuable assets. These technologies are changing not only how legal work is done but also how accurately and efficiently it can be managed, especially when handling large volumes of data that would be overwhelming for humans alone. The improvements in speed and efficiency brought by AI offer a promising outlook for the future of the legal profession. Natural Language Processing is a key Al technology used in the legal system for promoting justice and this tool has greatly improved how legal documents are analyzed. In the past, reviewing legal texts required long hours of manual work and was often prone to human error thus this tool allows these tasks to be automated, making them faster and more accurate.

Moreover, another Al tool being used in the modern court rooms is Machine learning. This is also playing a growing role in the legal sector, especially through predictive analytics. These models are used to forecast case outcomes, assess risks, and guide legal decisions. While this can improve efficiency and support better decisions, there are concerns about fairness particularly if the training data used contains biases. Hence, they raise the need to evaluate the accuracy, reliability, and ethical implications of Machine Learning predictions in important areas like bail decisions, sentencing, and parole. Furthermore, AI based decision support tools help legal professionals by offering insights and recommendations based on complex data analysis. These systems are becoming more common in real world legal settings.

However, despite all the Al tools benefits in the legal system, integrating AI into the modern court system also has its own risks which include the transparency of AI systems, accountability for their decisions, and ethical risks especially in sensitive legal matters. Thus, the research critically examines the need to balance AI’s advantages with the potential threat to justice, fairness, and due process.

ARTIFICIAL INTELLIGENCE IN MODERN COURTROOMS AND CONSTITUTIONAL VALUES

As Artificial Intelligence becomes increasingly integrated into judicial systems, it is of importance to assess its impact on core constitutional values, especially in a country like India, where the legal framework places a strong emphasis on the protection of fundamental rights. While AI promises speed, efficiency, and consistency its use in judicial decision making raises critical concerns about fairness and accountability. The “centaur’s dilemma”, a term adapted from military strategy, aptly captures the challenge faced in legal AI integration. Concerns such as, “should we reduce human involvement to allow AI to perform optimally, or increase oversight to ensure justice and constitutional principles are upheld? [5]. This becomes particularly pressing when AI is used in criminal justice, where life, liberty, and dignity are at stake.

According to Cesare Beccaria, four foundational values must guide any modern criminal justice system that is the due process, equal treatment, fairness, and transparency[6]. These values are enshrined in the Indian Constitution looking at Article 14[7], which guarantees equality before the law, and Article 21[8], which protects the right to life and personal liberty. Any use of AI in courts must be measured against these constitutional benchmarks. For example, the deployment of AI based predictive models in criminal sentencing or bail decisions introduces the risk of reinforcing existing societal biases if the data fed into the system reflects historical discrimination. This reflects the “garbage in, garbage out” principle if biased data is used, biased outcomes will follow thus such results threaten the very essence of constitutional morality and justice.[9]

Furthermore, transparency in how AI arrives at decisions is essential. Unlike human judges who provide reasoned judgments, many AI systems operate as “black boxes,” making it difficult to challenge their logic. This lack of explainability can directly undermine the right to a fair trial, which includes the right to understand and contest the basis of a decision. Therefore, while AI holds great potential to transform the judicial process, its implementation must be accompanied by well-structured legal safeguards, continuous human oversight, and a firm commitment to constitutional values. Hence, ensuring that AI serves as a tool to aid and not replace human judgment is important to preserve the principles of justice in a digital era.

INTEGRATING AI INTO LEGAL PROCESSES AND COURTROOM APPLICATIONS

The integration of Artificial Intelligence into the legal field has deeply reshaped how legal professionals conduct their work, impacting everything from research and documentation to litigation strategies and courtroom operations. AI has enhanced the efficiency, precision, and scope of legal services while also playing an increasing role in judicial proceedings and ensuring broader access to justice.

To begin with, legal research once a time-consuming and often fragmented process has been transformed by AI-driven tools that use Natural Language Processing (NLP) and machine learning to process extensive databases of statutes, case law, regulations, and academic commentary. These tools assist lawyers in identifying relevant precedents, interpreting statutory texts, and even predicting how courts might interpret a specific legal argument. Consequently, AI enables more strategic planning, reduces turnaround time, and supports collaborative research by allowing multiple team members to work in real time across shared platforms.[10]

Moreover, document review has become far more efficient with AI-powered systems capable of categorizing vast volumes of files, identifying relevant content, and highlighting inconsistencies or legal anomalies such as signs of fraud or privileged material. These platforms automate large portions of the review process, ensuring higher accuracy, minimizing risks of disclosure, and significantly lowering time and cost. In addition, they provide real-time progress tracking and generate summaries that support case preparation and due diligence processes.

Moreso, looking at contracts, which is another core area of legal practice, have benefited immensely from AI integration. Tools designed for contract analysis help extract key clauses such as payment terms, liability limits, indemnities, and dispute resolution mechanisms while identifying legal and commercial risks. These systems also detect ambiguities and suggest standardized language that aligns with current legal norms and industry practices. As a result, legal professionals can negotiate and draft agreements with greater clarity, consistency, and speed improving outcomes for clients and reduce exposure to legal uncertainty.

Furthermore, AI has proven invaluable in litigation through the use of predictive analytics. By examining historical case data, judicial behavior and court trends, AI systems generate insight into the likely outcomes of cases, helping lawyers in court rooms evaluate whether to settle or proceed to trial. In turn, these tools guide decision-making by anticipating judicial reasoning, assessing jury tendencies, and identifying key witnesses. They also contribute to litigation budgeting, timeline forecasting, and risk analysis, offering a more informed, data-driven approach to dispute resolution.

In the courtroom context, AI has increasingly been integrated into judicial systems. In some jurisdictions, courts use AI to assist with docket management, automate scheduling, and prioritize cases based on urgency or complexity. Additionally, AI supports judges in reviewing documents by organizing case files, identifying relevant precedents, and summarizing lengthy submissions. During trials, real-time tools assist legal teams by retrieving legal references, transcribing proceedings, and translating testimony when needed. Notably, in certain pilot programs, AI is also used during pre-trial processes such as bail assessments and sentencing recommendations, though these applications continue to raise significant ethical and constitutional questions.

In addition to its role in professional legal practice, AI plays a crucial role in bridging the access to justice gap. For underserved or marginalized populations, AI-based chatbots and virtual legal advisors provide basic legal guidance and procedural support. Furthermore, automated systems can generate essential documents for routine legal matters such as tenancy, small claims, or family disputes. Online Dispute Resolution (ODR) platforms often AI-enabled allow users to resolve issues without attending court, thereby increasing system accessibility and reducing burdens on judicial infrastructure. As a result, legal aid organizations have adopted these technologies to expand outreach and improve service delivery, allowing them to serve more clients more efficiently.[11]

Moreover, as law firms and judicial institutions increasingly depend on digital platforms, cybersecurity has become a critical concern. AI-powered security systems help protect sensitive legal data by detecting threats in real time, monitoring abnormal behavior, and automating breach response protocols. These tools also incorporate encryption, intrusion detection, and regulatory compliance mechanisms to ensure the confidentiality and integrity of legal communications. In cases of data breaches, AI-based digital forensics assist in tracing the source, assessing impact, and implementing preventive measures thus safeguarding both client interests and institutional reputation.

CHALLENGES AND ETHICAL CONSIDERATIONS IN AI INTEGRATION IN THE MODERN COURT SYSTEM

While Artificial Intelligence offers remarkable opportunities for improving efficiency and access to justice, its integration into the modern court system also raises several complex challenges and ethical concerns. The increasing use of algorithms in judicial decision-making especially in areas such as bail, sentencing, and risk assessment has drawn attention to potential biases embedded within these systems. Notably, experiences from jurisdictions like the United States have shown instances where AI tools have produced racially biased outcomes, reinforcing systemic inequalities. These issues underscore the urgent need for transparent oversight and ethical governance in the deployment of AI in courts.[12]

ADDRESSING ALGORITHMIC BIAS AND PROMOTING FAIRNESS

One of the foremost challenges in adopting AI in the judiciary lies in ensuring that the technology operates free from inherent bias. Since AI systems are trained on historical data, any existing societal or institutional prejudices reflected in the data can be reproduced and even amplified in the AI’s outputs. This can result in unjust legal outcomes, especially for marginalized communities. To mitigate this risk, it is essential that the datasets used for training AI are critically evaluated for fairness and representativeness. Additionally, robust safeguards and bias-auditing mechanisms must be established to ensure that AI tools support, rather than hinder, equitable justice.

DEVELOPING A CLEAR REGULATORY FRAMEWORK FOR AI IN COURTS

As AI tools become more prevalent in judicial processes, there is a growing need for a well-defined regulatory framework that governs their development and application. These rules should ensure that AI is used ethically, fairly, and in a manner that respects fundamental rights. Ethical AI must be transparent in its functioning, explainable in its reasoning, and impartial in its outcomes. Institutions such as the Vidhi Centre for Legal Policy have rightly emphasized the importance of creating these regulatory guardrails to build public trust and confidence in AI systems used within the judiciary.[13] Such regulations should address several core areas like the quality and neutrality of training data, the transparency of algorithms, the accountability of AI developers and users, and the periodic auditing of AI tools in practice. Equally important is the need for continuous human oversight to prevent overreliance on automated outputs and to ensure that AI functions only as a decision-support tool not as a decision-maker.

AI AS A CATALYST FOR REFORM IN INDIA’S JUDICIAL SYSTEM

India’s judicial system is currently facing a crisis of pendency, with over 4.32 crore cases awaiting resolution. The adoption of AI technologies offers a promising solution to alleviate this backlog. AI can assist in automating routine administrative functions such as organizing digital case files, scheduling hearings, and conducting preliminary legal research thereby allowing judges to focus on core adjudicatory responsibilities. This increased efficiency can significantly improve the speed and quality of judicial proceedings. Moreover, AI tools such as SUVAS (Supreme Court Vidhik Anuvaad Software), which translates legal documents into multiple Indian languages, enhance accessibility by overcoming language barriers.[14] This technological advancement ensures that litigants from diverse linguistic backgrounds can better understand and participate in legal processes, fostering a more inclusive and equitable justice system. The impact of judicial delays extends beyond individuals it can adversely affect economic activity, deter investment, and weaken the rule of law. By streamlining processes through AI integration, courts can enhance public trust in legal institutions and contribute to broader economic and social stability.

CASE ILLUSTRATION AND RESPONSIBLE USE

The potential of AI as a consultative tool in the modern court system was demonstrated in the Jaswinder Singh v. State of Punjab[15] case, where a judge sought assistance from ChatGPT regarding bail jurisprudence in matters involving allegations of cruelty. This example highlights the appropriate use of AI as an aid that provides broader legal insights while leaving the ultimate judgment to human discretion. Similarly, tools like SUPACE (Supreme Court Portal for Assistance in Court Efficiency) have been deployed to support judicial research and case analysis without influencing judicial reasoning directly.[16]

SUSTAINING ETHICAL AND RESPONSIBLE AI INTEGRATION

For AI to be successfully integrated into modern courts, continuous development, rigorous monitoring, and adherence to ethical standards are essential. Safeguards must be put in place to detect and correct algorithmic biases, ensure transparency in decision-making processes, and prevent misuse or overdependence. Building such a system requires collaboration among technologists, legal scholars, judges, and policymakers. The modernization of the court system through AI has the potential to not only resolve existing inefficiencies but also to reimagine access to justice in a digital era. However, this transformation must be guided by a principled approach that prioritizes accountability, inclusivity, and judicial independence. AI should serve as a powerful tool to augment judicial functions that do not replace the wisdom, empathy, and discretion that only human judges can provide.

CONCLUSION

The integration of Artificial Intelligence (AI) into modern court systems represents not merely a technological advancement but a fundamental shift in the administration of justice. In jurisdictions like India, where the judiciary is burdened by over 4.32 crore pending cases, AI presents a compelling solution to streamline court functions, reduce pendency, and improve access to justice. Tools such as SUPACE (for judicial research and data processing) and SUVAS (for multilingual translation of legal documents) have demonstrated how AI can enhance operational efficiency and inclusivity by automating routine tasks and breaking language barriers.

However, the integration of AI into judicial systems cannot be approached as a purely technical reform. At its core lies a critical intersection between technology, ethics, legality, and institutional trust. AI systems, being data driven, inherit the biases embedded in their training datasets biases that may be historically, socially, or institutionally rooted. This makes them susceptible to replicating patterns of discrimination related to caste, race, gender, religion, or socio-economic background. The deployment of such biased tools in judicial decision-making, particularly in sensitive domains like bail, sentencing, or case prioritization, poses a grave threat to the principle of equal protection under law and can lead to the legitimization of systemic inequities.

A pertinent illustration of AI’s limitations is found in the Mata v. Avianca, Inc. case, where the use of ChatGPT for legal research led to the submission of fabricated case citations. The incident underscores the dangers of unverified reliance on generative AI tools and raises broader concerns about professional accountability and ethical responsibility in legal practice. Unlike human legal practitioners, AI systems are not subject to licensing requirements, judicial ethics, or professional conduct rules. This regulatory vacuum challenges the very notion of accountability in the event of erroneous, harmful, or biased AI-generated legal outputs.

Moreover, the opacity of AI algorithms often described as “black boxes” can obscure the reasoning behind a decision or recommendation. In judicial contexts, this lack of transparency compromises the right to a reasoned judgment, a key tenet of natural justice. Without explainability, affected parties cannot challenge or appeal decisions effectively, undermining procedural fairness and legal certainty.

To navigate these challenges, it is imperative to establish a multi-layered regulatory and ethical framework that governs the design, deployment, and operation of AI in the judiciary. This framework must:

  • Ensure data integrity and diversity in AI training sets to minimize biases
  • Mandate transparency and explainability of AI outputs, particularly when they inform judicial decision-making
  • Clearly delineate accountability for developers, deploying institutions, and end-users of AI systems
  • Incorporate continuous monitoring and auditing mechanisms to evaluate AI performance over time
  • Promote capacity-building and digital literacy among judicial officers and legal practitioners to ensure informed use of AI.

Institutions such as the Vidhi Centre for Legal Policy have rightly emphasized the importance of regulatory guardrails and judicial ethics in governing AI use. Their recommendations, which stress both constitutional safeguards and functional oversight, form a crucial basis for national policy development on AI in the legal domain. Ultimately, the deployment of AI in the court system must be rooted in the recognition that technology is a facilitator not a substitute for human judgment. While AI can accelerate procedural efficiency and democratize access to legal information, it cannot replicate the nuanced reasoning, empathy, moral discretion, or contextual interpretation that characterize human adjudication. The modern court must therefore adopt AI in a hybrid model where automation supports, but never overrides, judicial wisdom.

In conclusion, AI holds the potential to transform the delivery of justice making it faster, more accessible and potentially more consistent. Yet, without adequate ethical, legal, and institutional safeguards it also poses risks that could destabilize the very ideals it aims to uphold. The future of judicial integrity in the AI era will depend not merely on technological innovation, but on our collective commitment to justice, fairness, and human dignity.

BIBLIOGRAPHY

JOURNAL ARTICLES

  • Choudhary, Khushbu & Chandan Bala, Impact of Artificial Intelligence on Judicial System, 10 Int’l J. Advance Res. & Dev. 1 (2024), https://www.multistudiesjournal.com/ [Published Jan. 30, 2025]
  • Mahima, The Growing Influence of Artificial Intelligence on the Legal Profession: Opportunities, Challenges, and Implications, 6 Int’l J. L. Pol’y & Soc. Rev. 119 (2024).
  • Rawat, Priyadarshini, Artificial Intelligence and Judicial System of India, 10 Int’l J. Advances Res. Ideas & Innovations Educ. (IJARIIE) (Issue 4) (2024), https://www.ijariie.com/.

BOOKS AND ACADEMIC MONOGRAPHS

  • Baker, James E., The Centaur’s Dilemma: National Security Law for the Coming AI Revolution (Brookings Inst. Press 2020).
  • Beccaria, Cesare, On Crimes and Punishments (Henry Paolucci trans., Bobbs-Merrill Co. 1963) (originally published in 1764).

REPORTS, GOVERNMENT PUBLICATIONS, AND OFFICIAL SOURCES

  • Meghwal, Arjun Ram, Use of AI in Supreme Court Case Management, Press Information Bureau, Govt. of India (Mar. 20, 2025), https://pib.gov.in/PressReleasePage.aspx.
  • Modi, Narendra, Address at the Foundation Day of the National Legal Services Authority (NALSA), New Delhi, Nov. 26, 2021, https://www.pmindia.gov.in.
  • Supreme Court of India, SUVAS: Supreme Court Vidhik Anuvaad Software (2019).
  • Vidhi Centre for Legal Policy, Designing a Framework for Regulation of AI in India (2021).

 ARTICLES / ESSAYS

  • Imam, Md Arif, The Integration and Impact of AI in the Indian Judiciary (2024).
  • Mirza, Aslam B., Role of Artificial Intelligence in Legal Education and Legal Profession, Legal Service India E-Journal.

CONSTITUTIONAL AND LEGAL FRAMEWORKS

  • India Const. art. 14.,1950
  • India Const. art. 21.,1950

 CASES

  • Jaswinder Singh v. State of Punjab, CRM-M-M 22496 of 2022 (P&H HC Mar. 27, 2023).

 FOUNDATIONAL AI WORKS

  • McCarthy, John et al., A Proposal for the Dartmouth Summer Research Project on Al (Aug. 31, 1955), https://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html.
  • Turing, A.M., Computing Machinery and Intelligence, 59 Mind 433 (1950)

[1] Prime Minister Narendra Modi, Address at the Foundation Day of the National Legal Services Authority (NALSA), New Delhi, November 26, 2021. Available at: https://www.pmindia.gov.in

[2] A.M. Turing, Computing Machinery and Intelligence, 59 Mind 433 (1950).

[3] John McCarthy et al., A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence (Aug. 31, 1955), https://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html

[4] Khushbu Choudhary & Chandan Bala, Impact of Artificial Intelligence on Judicial System, 10 Int’l J. Advance Res. & Dev. 1 (2024), https://www.multistudiesjournal.com/ [Published Jan. 30, 2025].

[5] James E. Baker, The Centaur’s Dilemma: National Security Law for the Coming AI Revolution (Brookings Inst. Press 2020)

[6] Cesare Beccaria, On Crimes and Punishments (Henry Paolucci trans., Bobbs-Merrill Co. 1963) published in 1764.

[7] India Const. art. 14.

[8] India Const. art. 21

[9] Priyadarshini Rawat, Artificial Intelligence and Judicial System of India, 10 Int’l J. Advances Res. Ideas & Innovations Educ. (IJARIIE) (Issue 4) (2024), https://www.ijariie.com/.

[10] Mahima, The Growing Influence of Artificial Intelligence on the Legal Profession: Opportunities, Challenges, and Implications, 6Int’l J. L. Pol’y & Soc. Rev. 119 (2024).

[11] Mirza Aslam B. Role of Artificial Intelligence in Legal Education and Legal Profession, Legal service India E- Journal.

[12] Md Arif, Imam, The integration and Impact of Al in the Indian Judiciary, 2024

[13] Vidhi Centre for Legal Policy, Designing a Framework for Regulation of AI in India (2021)

[14] Supreme Court of India, SUVAS: Supreme Court Vidhik Anuvaad Software (2019)

[15] Jaswinder Singh v. State of Punjab, CRM‑M‑22496‑2022 (P&H HC Mar. 27, 2023).

[16] MoS Law & Justice Arjun Ram Meghwal, Use of AI in Supreme Court Case Management, Press Information Bureau, Govt. of India (Mar. 20, 2025)

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