A Comparative Study On E-Court Case Management Between India And United States Of America

Author: LawSphereX

Category: General Law

Published: 2026-08-23T16:57:46.834308+00:00

Updated: 2026-08-26T17:12:44.38+00:00

A COMPARATIVE STUDY ON E-COURT CASE

MANAGEMENT BETWEEN INDIA AND UNITED STATES

OF AMERICA

Menaka R, The Tamil Nadu Dr. Ambedkar Law University, Chennai

ABSTRACT

The integration of e-courts main elements and Artificial Intelligence (AI) has significantly transformed judicial systems in both India and the United States. In India, AI technologies such as SUVAS and SUPASE have streamlined case management by enhancing speech-to-text and evidence processing capabilities. People in India do not need to pay for accessing Ecourt materials, whereas in U. S. , only researchers are exempt from purchasing e-court reports; otherwise, everyone must pay for the reports when they wish to access them. In U. S. , AI systems like, COMPAS is used for risk management in criminal cases, utilizing algorithms to assess recidivism risks and aid in sentencing. The U. S. legal system also navigates constitutional concerns, particularly with the First and Fourth Amendments, as they relate to AI’s role.

The paper deals with an overall comparative study of e-court case management between India and the United States of America.

1.1 Introduction

In the Indian judicial system, we recognize three key branches: the Legislative, the Executive, and the Judiciary. whereas, the functioning of e-Courts, a digital transformation of the judiciary, remains somewhat unclear. The Phase I project aimed to digitize and automate various processes within Indian courts. This phase primarily focused on the creation of an electronic system within the judicial framework. In Phase II, the project advanced by enhancing the interface, improving functionality, and enabling electronic payments in a digital format. Performance was also optimized. Phase III saw the expansion of the e-Court system to cover courts nationwide, integrating multiple platforms such as desktop computers, mobile apps, and leveraging Artificial Intelligence (AI) tools.

In contrast, the United States developed its judicial electronic systems differently, following models such as PACER (Public Access to Court Electronic Records) and CM/ECF (Case Management/Electronic Case Files). The U. S. system features a structured registration process, where individuals other than research scholars must pay a fee of $0. 10 (8. 425 INR) per page for accessing data through PACER searches. AI, a term coined by John McCarthy, has found significant applications in both the Indian and U. S. judicial systems. In India, two AI systems, SUVAS and SPACE, are being used to assist with legal research, predictive analysis, document review, and case management. These AI tools contribute to streamline judicial processes and enhance efficiency.

In the United States, the constitution, particularly the First and Fourth Amendments, plays a pivotal role in regulating AI’s interaction with legal actions. Additionally, AI is used in risk management tools within the U. S. criminal justice system. This paper analyses the evolution of the e-Court system and examines how AI is being used as an assisting tool in the judicial systems of both India and the United States.

1.2 Research Questions

1. How do e-court system in the United States of America and India function overall, and what

are the contributions to improve judicial efficiency?

2. How can AI involve in e-court case management in India and the United States of America?

2: Functions of E-court System

2.1 In India:

2.1.1. Phase I: e-courts Integrated Mission Mode Project

The e-Court Projects Phase-I was initiated in 2007. It is a National e-Governance project

implemented by the High Courts and District or Subordinate Courts of India. The projects central concept was based on the National Policy and Action Plan for ICT Enablement of the Indian Judiciary, which was established by the Supreme Court's e-Committee in 2005. The e- Committee, formed in 2004, was tasked with drawing up an action plan for ICT implementation. In March 2014, the government approved a project to computerize 14,249 District and Subordinate Courts at a budget of ₹935 crore. The e-Courts Project aimed to enable quick access to services for stakeholders such as litigants, lawyers, and justice staff by universally computerizing India's District and Subordinate Courts. It emphasized the role of ICT in evolving and modernizing the justice delivery system. The committee constitute by the chairpersonship of secretary, Department of Justice.

They are given strategic direction and guideline to the project. The project was conducted out by the National Informatics Centre (NIC). This project monitoring by the committee and every month NIC and e-committee monitor the progress of the project. On March 31, 2014, the ICT infrastructure of the Supreme Courts and High Courts was upgraded1. The following categories of improvements were implemented:

1. Laptops for Judicial Officers

Laptops were provided to 14,309 Judicial Officers.

2. Software

A common national core application and Case Information System (CIS) software were

created and made accessible for use in all courts being computerized. Data entry of even past cases was completed, making information for approximately 3 crore cases available online.

3. Judicial Service Centre (JSC)

Judicial Service Centres were established in all computerized courts. These centres enable stakeholders and lawyers to file petitions and applications and obtain updates, such as copies of orders and judgments.

4. Process Re-engineering

The e-Committee undertook process re-engineering. Public Relations Committees were set up in all High Courts to study and suggest simplifications in existing rules, procedures, processes, and forms.

1 https://www.wbja.nic.in/wbja_adm/files/Brief%20on%20e-courts%20Project.pdf

5. Video Conferencing

Video conferencing services have been deployed in courts and jails. Initially launched in five districts under the supervision of the e-Committee as a pilot project, video conferencing was planned to be extended to 500 locations across the country.

6. Change Management and Training

Change management initiatives included training for 14,000 Judicial Officers. They were trained to use the Ubuntu-Linux operating system, and court staff received training in CIS software.

7. National Judicial Data Grid (NJDG)

The National e-Court portal (http://www.ecourts.gov.in) was introduced, allowing stakeholders to access details on case registration, cause lists, case statuses, daily orders, and final judgments. NJDG also supports the judiciary in monitoring and management, while the government can use the data for policymaking purposes. Overall, the Phase-I project had a total budget of ₹935 crore. The project was concluded with an extension of its timeline up to March 30, 2015.

2.1.2. Phase-II: Policy and Action Plan Document

The e-Committee of the Supreme Court approved the Policy and Action Plan Document in January 2014. In Phase-I, 1+3 systems were allocated per courtroom. The primary system was provided for the Judicial Officer, and three systems were allocated for court staff, including clerks, stenographers, or public interface use. However, in Phase-II, 2+6 systems are allocated per courtroom. The primary system is designated for the judge, while the remaining six systems are intended for staff, public use, e-filing, or video conferencing. The Phase-II Project also provides hardware, LAN, and other necessary infrastructure. While UPS and DG servers were introduced in Phase-I, there was no provision for backup power for hardware and printers. This issue is being addressed in Phase-II. This project helps to reduce environmental degradation.

Video conferencing is used by under-trial prisoners, reducing physical appearances in court. It also helps in recording evidence in sensitive cases. Phase-II provides Judicial Knowledge Management, including an Integrated Library Management System for the creation of digital libraries. The system for serving notices and summons has been strengthened.

2.1.2.1. Dynamic Implementation

Administrative backing and coordination are provided with the approved policy document. • The National Informatics Centre (NIC) provides technical expertise, infrastructure, and software documentation. • DeitY helps with the technological framework. • The Ministry of Finance allocates funds for project implementation. • Each High Court takes responsibility for executing the project within its jurisdiction to ensure the smooth running of cases in state and district courts. • The library of the court is being computerized. The Supreme Court has successfully implemented an Integrated Library Management System.

2.1.2.2. Infrastructure

Hardware and maintenance costs are reduced by transitioning to centralized setups. • The network room is created by converting the server room. • Judicial Service Centres act as Centralized Filing Centres for case filing and tracking, with kiosks and waiting areas for litigants. • The District Legal Service Authority and Taluka Legal Services Committees are improving access to legal aid. • The National Judicial Academy and State Judicial Academies develop the capacity of judicial officers and staff.

2.1.2.3. Core-Periphery Model

Free and Open-Source Solutions are modified based on judicial requirements. • Data is standardized at the horizontal and vertical levels of courts. • Applications are set up for mobile phones, SMS, and email to disseminate information. • Certified copies can be obtained through an online platform, and e-payment gateways are used for deposits, court fees, fines, and other payments.

2.1.2.4. Composition of the e-Committee

1. Chairperson: A sitting judge of the Supreme Court of India is appointed by the Chief

Justice of India.

2. Members: Selected from senior judges of High Courts or experts in IT, law, and project

management.

3. Member Secretary: Appointed from Judicial Officers or Technical Experts, who are

responsible for executing the decisions of the e-Committee.

2.1.2.5. ecourts.gov.in

The Hon’ble Chief Equity of India introduced the e-Courts National Entry, ecourts.gov.in, on 7th Eminent 2013.2 More than 2,852 District and Taluk Courts use the NJDG Portal to provide case statuses, cause lists, and judgments or orders online. Through this portal, over 7 crore pending and disposed cases have been recorded, and 3.3 crore orders or judgments from District Courts in India are currently available on the NJDG. The portal is updated daily. The NJDG serves as a valuable source of judicial information for all stakeholders and consolidates multiple databases for easy access.

2.1.3. Phase-III

On September 13, 2023, the Union Cabinet authorized Phase III of the e-courts Project for the ICT growth of the Indian Judiciary, with an outlay of Rs. 7,210 crore over four years3 beginning in 2023. Taking the gains of Phases I and II to the next level, e-Court Phase III aims to usher in a regime of maximum case of justice by transitioning to digital, online, and paperless courts by digitizing all court records, including legacy records, and by universalizing e-Filing or e- Payments through the saturation of all court complexes with e-Sewa Kendras. The e-courts Project Phase-III aims to implement intelligent smart solutions that will allow judges and registries to make data-driven decisions while scheduling or prioritizing cases.

Phase-III's primary goal is to provide a single technological platform for the judiciary, which will enable a smooth and paperless communication between the courts, litigants, and other interested parties. The initiative aims to improve the user experience by creating a "smart" ecology. The e-courts Phase-III might hence be an amusement changer in securing equity by making the Court involvement available, conservative, and hassle-free for all occupants of the nation. The different components of e-courts Phase-III include the digitization of 3108 crore pages of legacy data, cloud infrastructure, 4400 fully functional e-Sewa Kendras in all court complexes,

2 https://ecommitteesci.gov.in/project/brief-overview-of-e-courts-project

3 https://pib.gov.in/PressReleasePage.aspx?PRID=2040232

and the adoption of emerging technologies such as AI/ML, among others. The initiative is projected to produce the following outcomes:

1. Citizens will not require direct access to advanced technology; instead, they can access

judicial services through e-Sewa Kendras, bridging the digital divide.4

2. The project aims to become more environmentally friendly by reducing paper-based

filings and minimizing the physical movement of documents.

3. Facilitation of digital participation in court proceedings will help eliminate travel

expenses for witnesses, judges, and other stakeholders.

4. Expansion of e-filing will reduce processing times and promote paperless workflows.

5. Enable the payment of court fees, fines, and penalties from anywhere, at any time.

6. Strengthen court proceedings while ensuring greater transparency.

7. Promote the automatic delivery of court summons through the expansion of NSTEP,

significantly reducing delays in trials.

8. Leverage cutting-edge technologies, such as AI, ML, OCR, and NLP, to provide a

seamless user experience within a "smart" judicial ecosystem.

9. Integrate emerging technologies into court processes as needed, contributing to a

reduction in pending cases.

2.2. In U.S.A

In the U.S.A., two related case management systems provide online access to federal court records: PACER and CM/ECF. PACER is used by the general public to access U.S. federal court records, case dockets, and filed documents. It offers 24-hour access to case file documents, allowing users to download and print court documents easily. Multiple parties can simultaneously access case files. CM/ECF, on the other hand, is an electronic case filing system used in U.S. federal courts. Registration for PACER is available to individuals, attorneys, and organizations, but CM/ECF access is limited to litigants, attorneys, and court personnel for filing and handling case file documents online. CM/ECF is secure and reliable, providing automatic email notifications regarding case activity, facilitating easier case tracking, and updating court dockets immediately.

4 https://doj.gov.in/phase-iii

2.2.1. Fees

PACER allows users to print or download information on current and recently closed cases in federal courts. If a document is not available on PACER, the concerned parties must contact the court.5 The PSC dos not receive appropriations from the Federal government to provide electronic public access. Instead, Congress directed the Judiciary to fund PACER through user fees. A s a result, all registered agencies and individuals are charged $0.10 per page for PACER searches. This includes searches that yield no matches. In addition, audio files generate a $2.40 per-file charge.6

2.2.2. Option for Registration

To register, visit pacer.uscourts.gov and choose the type of account that suits your needs. Provide the required information, then create a username and password. After completing the registration, parties can either start using the service immediately or may need to verify their email address.

2.2.3. Types of Registration

There are no fees for registration in the following categories.

2.2.3.1. Case Search Only

The "Case Search Only" option is the most common registration type. The "Register for a PACER Account" link can be clicked by users to register. If a credit card is provided during registration, the case search capability is activated after successful validation of the card and review of the account details. If no credit card is provided, authentication will be sent via U.S. mail within 7–10 days to complete the registration process. For users registering from outside the United States, five zeros (00000) should be entered in the Zip Code field.

2.2.3.2. Attorney Filers

Attorney Filers are attorneys authorized and registered to file documents electronically in federal courts. This e-filing registration applies to all appellate, district, and bankruptcy courts. To begin, attorneys must determine whether the court uses the Legacy or NextGen system and submit their application through the PACER website. After this, they must apply for registration with each court individually. The PACER Service Centre (PSC) will forward the registration

5 https://pacer.uscourts.gov/sites/default/files/files/PACER%20User%20Manual.pdf

6 https://pacer.uscourts.gov/sites/default/files/files/PACER%20User%20Manual.pdf

to the respective court, and the parties will receive a notification once the court approves the registration.

2.2.3.3. Non-Attorney Filers

Court reporters, necessary parties, filing agent, trustees, Creditors and other Parties are nonattorney.7 Not all courts accept non-attorney filers, and some only allow specific types of nonattorney filers. The registration process for non-attorney filers is similar to that for attorney filers.8 If a court does not permit non-attorney filers to register, the parties cannot obtain filing privileges at that court.

2.2.4. E-File Registration in the Appellate Court

The NextGen CM/ECF system enables parties to use a single account for both PACER access and electronic filing. All appellate courts have transitioned to the NextGen CM/ECF system. If parties previously had a legacy PACER account, they must complete a separate e-file registration to obtain filing privileges. This is because legacy PACER accounts are older and do not support the centralized registration and e-filing process used by the NextGen system.

2.2.5. E-filing Registration on District and Bankruptcy Court

When you register a filer account and a PACER account, each district and bankruptcy court handles filer registration independently. While a PACER account allows you to manage and access multiple courts, each district and bankruptcy court independently manages its own efiling registration.

2.2.6. Researcher Fee Exemption

PACER charges $0.10 per page to access court documents. Researchers may need access to a large number of case records, but they might not have the budget to cover per-page fees. However, they don’t need to worry about the costs, as the U.S. federal government provides a fee exemption for researchers, including academics, journalists, and nonprofit organizations. The research must serve the public interest or contribute to public knowledge. National Veterans Legal Services Program V. United States9 (2020) he courts ruled that a reform of the PACER system is the provision of court records without charge.

7 https://pacer.uscourts.gov/

8 https://pacer.uscourts.gov/register-account/non-attorney-filers-cmecf

9 National Veterans Legal Services Program v. United States, 68 F.3d 1345 (Fed. Cir. 2020).

3: AI in E-Court Case Management

3.1. In India

The concept of AI was established in the 1950s. John McCarthy coined the term "AI" in 1956. He was an American computer scientist. John McCarthy defined Artificial Intelligence as “the science and engineering of making intelligent machines”.10

3.1.1. Needed of AI

A crucial role is played by the judiciary in every nation. In the Indian legal system, the country

has a huge population, which is why courts struggle to handle the large number of pending cases. This led to the implementation of Alternative Dispute Resolution (ADR) methods. However, these measures have not fully resolved the backlog of cases. For this reason, courts have recently turned to Artificial Intelligence (AI) to address this issue. Recent growth of AI in Indian legal system:

3.1.1.1. Supreme Court Vidhik Anuvaad Software (SUVAS)

An official application bases on Artificial Intelligence (AI) have been released by the Supreme Court of India to translate legal documents and orders written in English into nine vernacular languages. In terms of Artificial Intelligence, this is the first action our judiciary has taken11 3.1.1.2. Supreme Court Portal for Assistance in Court’s Efficiency (SUPACE)

It is also recently launched by Supreme Court of India as a tool that collects relevant facts and laws and makes them available to a judge. It will yield outcomes customized to the specific requirement of the case and the way the judge thinks12 3.1.1.3. The Official Multilingual Mobile Application of the Supreme Court of India

With the help of the National Informatics Centre, our nation’s highest court has launched an app that will enable the citizens to authentically access cases, judgements, important circulars, display boards and a plethora of other crucial information with just a single click13

3.1.1.4. e-courts

One of most significant advancements brought about by the judicial reforms is the availability of all pertinent information about court orders and judgements online for free. The

10 Rajaraman V, John McCarthy – Father of Artificial Intelligence, Resonance, 198-206 (2014).

11 Harshul Gupta, Scope Of Artificial Intelligence As A Judge In Judicial Sector, IJLPA, 1-14.

12 https://www.drishtiias.com/daily-news-analysis/ai-portal-supace/print_manually

13 Harshul Gupta, Scope Of Artificial Intelligence As A Judge In Judicial Sector, IJLPA, 1-14.

establishment of an E-Court will result in quick disposal of cases, ease of record maintenance, reliability of the evidence recorded and to bring more transparency in the functioning of courts14 3.1.1.5. An Artificial Intelligence System created at IIT Kharagpur to read Court

Orders An AI-assisted technology that can read court orders and judgements has been developed by IIT Kharagpur researchers. It also uses machine learning to identify laws that are being violated15 3.1.1.6. Kira Systems by Cyril Amarchand Mangaldas

By collaboration with Canadian AI helper Kira Systems, Indian company Cyril Amarchand Mangaldas is now using AI for contract analysis and review16

3.1.2. How Artificial Intelligence helpful in Indian Courts

Artificial Intelligence has a tremendous impact on the judiciary. It serves as a parallel support system for judges. It updates stakeholders, advocates, judges, and court officers daily. Additionally, it provides several other benefits for judges: 3.1.2.1. Legal Research and Analysis

AI systems can quickly analyse vast databases of legal precedents, statutes, and case laws to provide judges with relevant information17. This can significantly speed up the legal research process, ensuring that judges have access to comprehensive and upto-date information when making decisions18 3.1.2.2. Accelerating the delivery of justice

In India, it is observed that the adjudication of a criminal as well as civil trial often takes years. Ultimately, this leads to ineffective and delayed justice delivery. This can be minimized, and by handling more cases at a faster pace, more cases can be handled, and justice can be served 14 Rishi Prakash, et al. , ICT in Indian Court Challenges & Solution, V-1. International Journal of Internet Computing, 21-25 (2011). 15Harshul Gupta, Scope Of Artificial Intelligence As A Judge In Judicial Sector, IJLPA, 1-14. 16Parth Jain, Artificial Intelligence for Sustainable and Effective Justice Delivery in India, Vol. 11. International Journal of Sustainable Development, 64-68 (2018). 17Sharma B, Impact of Artificial Intelligence on the Legal Industry: Advantages, Challenges, and Ethical Implications, Vol 12 Issue 02 2023. A Journal for New Zealand Herpetology, 3363-3373 (2023).

18Kabir MS, et al. , The Role of AI Technology for Legal Research and Decision Making, Vol. 10 Issue 07. International Research Journal of Engineering and Technology, 1088-1091(2023).

to citizens more quickly19. This provides citizens with a better experience by enabling faster resolution of cases.

3.1.2.3. Predictive Analytics

By examining past case data, AI systems are able to forecast possible case outcomes. One of the biggest problems faced by the judiciary is the volume of cases that are still pending and the lack of judges to decide on those motions. Therefore, to resolve these issues, courts may utilize predictive analytics to show the likely outcomes to the parties involved in a dispute and persuade them to reach an out-of-court settlement20. It saves the court's time, and parties can avoid spending unnecessary time.

3.1.2.4. Document Review

By highlighting important details and finding relevant information, AI-powered technologies can help with the review of legal documents. This makes it easier for judges to quickly understand the key facts of a case and concentrate on the important points at the time of hearings21.

3.1.2.5. Case Management

Judges can better arrange and prioritize their caseload by using AI to expediate case management procedures. Automated systems can help with scheduling, monitoring due dates, and improving workflow management more efficiently22.

3.1.2.6. Artificial Intelligence (AI) via Natural Language Processing (NLP)

NLP technologies facilitate computer comprehension and interpretation of human language. Judges can use Natural Language Processing (NLP) to help with tasks such as summarizing case documents, analysing legal arguments, and extracting relevant information from spoken or written statements. For instance, ROSS Intelligence is an AI- driven legal research tool that leverages Natural Language Processing (NLP) to comprehend inquiries in natural language and deliver relevant legal information23. 19Sunil Kumar Srivastava, AI for Improving Justice Delivery: International Scenario, Potential Applications & Way Forward for India, Informatica, 21-38 (2023). 20 Parth Jain, Artificial Intelligence for Sustainable and Effective Justice Delivery in India, Vol. 11. International Journal of Sustainable Development, 64-68 (2018).

21Zichun Xu, Human Judges in the Era of Artificial Intelligence: Challenges and Opportunities, Vol 36 Issue1. Applied Artificial Intelligence, 1026-1042 (2021).

22 Cary Coglianese, et al., AI in Adjudication and Administration, Vol.86.SSRN, 791-838 (2021).

23Kabir MS, et al., The Role of AI Technology for Legal Research and Decision Making, Vol.10 Issue 07, International Research Journal of Engineering and Technology, 1088-1091(2023).

3.1.2.7. Remote Proceedings and Virtual Courts

Artificial Intelligence (AI) technologies enable secure video conferencing, real-time transcription, and language translation, among other features that make virtual courtrooms and remote proceedings run more smoothly. This is especially important when it comes to circumstances requiring remote hearings24.

3.1.2.8. Decision Support Systems

Artificial Intelligence (AI) systems have the potential to serve as decision support tools by providing judges with relevant information, precedents, and legal analyses to aid in their decision-making process25. In this concept, the emphasis is on AI being a helpful tool, not taking on the role of a judge.

3.1.3. Challenge

AI provides benefits but also presents challenges. The following are the recent challenges in the legal system of Indian courts: 3.1.3.1. Concerns about Bias and Fairness

AI systems may unintentionally reinforce or even worsen biases found in past legal data, raising questions about fairness and bias. AI algorithms may generate biased results, resulting in unfair or discriminatory decisions and violation of fundamental rights26. 3.1.3.2. Absence of Transparency

Many AI algorithms function as “black boxes”, making it difficult for humans to understand how they make decisions. Concerns regarding accountability may arise from AI system’s lack of transparency. The absence of openness may have a direct impact on litigants and can cause trouble for judges27. 3.1.3.3. Information Security and Privacy Risks

It is particularly difficult to protect the security and privacy of sensitive legal data, especially when bad actors may be able to exploit vulnerabilities in AI systems. 3.1.3.4. High Resource Requirements and Costs

24 Monika Zalnieriute, et al., Technology and Judicial Role, SSRN, 31-37 (2019).

25 Vijipriya RA, Critical Study on Artificial Intelligence (AI) in Indian Legal Sector, Vol 9 Issue4.International Journals of Arts, Science and Humanities, 58-63 (2022). 26 Rocha c, et al., Artificial Intelligence in the Judiciary: Uses and Threats, EGOV-CeDEM-ePart 2022, 1-6 (2022).

27 Themeli E, et al., AI as the Court: Assessing AI Deployment in Civil Cases, SSRN, 1-19 (2021).

The development, installation, and maintenance of AI systems can be costly. For AI technologies to be broadly and fairly embraced in the legal system, their price and scalability must be carefully considered. 3.1.3.5. Technical Limitations and Errors

Artificial intelligence (AI) systems are imperfect and prone to errors. It's likely that the AI system won't be aware of legislative changes or would interpret them wrongly. Furthermore, like any other technology, an Artificial Intelligence (AI) system might have faults or malfunctions that result in incorrect conclusions or forecasts. 3.1.3.6. Acceptance by Judges

Judges' approval or rejection of AI can impact its incorporation in judicial proceedings. Judges that employ AI Technology nowadays tends to have younger judges. Senior judges are resistant to AI technology because they fear it will not help them handle cases effectively. Some judges believe that allowing cold robots to handle socially interactive litigation issues is emotionally inappropriate. Rather than relying on AI, people prefer to make their own decisions.

3.1.4. Role and Function of AI in Judiciary system

The judicial system uses AI to assist judges but not to act as judges. Judicial judgments involve not only one-dimensional thinking but also multi-dimensional decision-making. AI technology helps ensure faster adjudication of cases. Since 2021, AI has been used to collect information and provide it to judges for decision-making. The Supreme Court has used SUVAS, an AI tool, to translate legal documents from English into vernacular languages. In the case of Jaswinder Singh v. State of Punjab28 The Punjab and Haryana High Court rejected the bail petition on the grounds that the petitioner was involved in a brutal and fatal assault. The presiding judge consulted ChatGPT to explore general grounds related to granting bail in cases involving cruelty. However, ChatGPT did not express an opinion on the merits of the case, and the trial court did not consider the merits either.

ChatGPT was used solely to gain a broader understanding of bail-related principles. The Supreme Court’s Judgment in D. Velusamy v. D. Patchaiammal29 When a court interprets the law, it should rely on sound, well-established legal principles and avoid using unreliable or inappropriate sources, such as Wikipedia or ChatGPT, to make pivotal legal decisions. Using

28 V Jaswinder Singh v. State of Punjab, (2020) 3 SCC 123.

29 D. Velusamy v. D. Patchaiammal, (2010) 10 SCC 469.

inappropriate sources can jeopardize justice and deprive a person of their life and liberty. In this case, the court referred to Wikipedia to interpret the concept of common law marriage and defined the relationship in the nature of marriage under the Protection of Women from Domestic Violence Act, 2005.

3.2. U.S.A

Loomis’ COMPAS score has identified the person who doing a high-risk violence, high risk recidivism, and a high pretrial flight risk. The risk score base on the criminal history, age, substance abuse, employment status, and social connections. Risk score problem was origin, authenticity or algorithm weighting.

3.2.1. The First Amendment

The First Amendment primarily focuses on issues related to AI surveillance and government regulation. It addresses the idea that people can use AI for purposes such as speech, press, and gathering information. However, government regulation of social media postings whether direct or through indirect pressure, such as actions taken against individuals for public statements, hearings, or informal communication raises concerns. Additionally, the government’s funding of AI development may amplify certain voices while suppressing others. AI's ability to analyse facial expressions through surveillance can also play a role in preventing actions against places of worship or illegal assemblies in public spaces.

3.2.2. The Fourth Amendment

The Fourth Amendment primarily focuses on issues such as data aggregation, drones, and facial recognition. These concepts are being applied with the help of AI. The Privacy Test established in Katz v. United States the Court held that the Warrantless wiretaps were unreasonable, reasoning that the fourth Amendment protects people, not places.30 However, the Third-Party Doctrine approaches it differently. In the cases of Smith v. Maryland31 and United States v. Miller32, it is stated that when information is shared with a third party, it loses constitutional privacy protection.

3.2.3. Authentication of AI Evidence

To authenticate AI evidence under Federal Rule of Evidence 901(a), the proponent must

30 Katz v. United States, 389 U.S. 347 (1967).

31 Smith v. Maryland, 442 U.S. 735 (1979).

32 United States v. Miller, 425 U.S. 435 (1976).

provide sufficient evidence to show the item is what it is claimed to be. Rule 901(b) offers nonexclusive methods for this, including using testimony (Rule 901(b)(1)) and describing processes or systems that yield accurate results (Rule 901(b)(9)). For testimony under Rule 901(b)(1), Rule 602 mandates that the witness have personal knowledge of the AI's functioning, while expert testimony under Rule 702 and Rule 703 allows reliance on reliable external data and methods. Given the complexity of AI systems, multiple experts may be needed to authenticate inputs, processes, and outputs. Developers, data scientists, and operators might each contribute distinct expertise. Alternatively, a single expert with sufficient qualifications under Rule 702 and 703 could consolidate this testimony.

Authentication must meet at least a preponderance of evidence (more likely than not), but AI evidence with high risks of adverse consequences requires stricter scrutiny. Judges should demand robust evidence of reliability, particularly when flaws could lead to severe outcomes, such as biased sentencing or wrongful arrests. If the proponent fails to meet this standard, the judge may exclude the evidence under Rule 403 to avoid unfair prejudice or jury confusion.

3.2.4. Risk Management in Criminal Justice

In criminal justice, algorithmic risk assessment tools, such as COMPAS, are widely used. These AI systems help predict habitual offenders, guide pretrial release decisions, assist in probation assessments, parole and support sentencing decisions. Additionally, some developed countries occasionally use proprietary machine learning algorithms for similar purposes. In State v. Loomis33, the court allowed COMPAS to be used only for corroborative purposes, specifically to determine the defendant's risk level. Beyond that, the use of COMPAS was emphasized to be limited in scope. Chapter 4: SUGGESTION Hence, the PACER system is very useful for attorneys, researchers, and the public to access federal case records and documents. However, the current phase of the project does not address fee exemptions for researchers; only individuals directly involved in a case should use the ecourt system.

In the Indian e-court system project, there is no per-page charge to access case records, whereas PACER charges $0. 10 per page. Overall, the PACER system in the U. S. is more efficient compared to India’s current e-court project. The Indian judiciary must develop its e-court system to cater to the needs of the modern generation. The integration of AI into the judiciary in both India and the U. S. presents significant advantages in terms of efficiency and

33 State v. Loomis, 881 N.W.2d 749 (Wis. 2016).

case management. However, both systems face similar challenges such as bias, lack of transparency, and the over-reliance on AI tools. In India, tools like SUVAS and SUPACE are designed to assist judges without replacing human judgment, ensuring a more supportive role in decision-making. In contrast, the U. S. uses tools like COMPAS, which have faced heavy criticism for reinforcing biases, privacy concerns, and lack of transparency, making them less reliable and more controversial. While India's AI tools focus on enhancing judicial efficiency without directly affecting case outcomes, U. S. AI systems like COMPAS have been linked to potential constitutional violations and unfair sentencing due to their unvalidated algorithms. India’s more cautious approach, which emphasizes transparency and support for judges, may be a more sustainable model.

Ultimately, India’s AI integration seems to prioritize aiding decision-making without overshadowing judicial discretion, while the U. S. faces greater challenges with biases and the reliability of its AI-driven tools.

CONCLUSION

The integration of e-court systems and AI technologies in the judicial frameworks of India and the United States has brought significant improvements in case management and efficiency. India’s e-court system, with its free access to case records, stands in stark contrast to the U. S. PACER system, which charges a fee for access. While PACER offers a more structured and efficient approach to accessing court records, India’s system is still evolving but aims to provide greater public access and transparency. The use of AI in both countries has enhanced legal research, predictive analysis, and decision-making. However, both systems face critical challenges, such as the potential for AI tools to reinforce biases and undermine judicial discretion.

In India, AI tools like SUVAS and SUPACE are designed to assist judges without replacing their judgment, ensuring a supportive role in case management. In contrast, AI tools like COMPAS in the U. S. have faced scrutiny for their lack of transparency and potential constitutional violations, particularly regarding biased algorithms. While India’s approach to AI integration is more cautious and focused on enhancing judicial efficiency without compromising fairness, the U. S. faces greater challenges regarding the reliability and ethical implications of its AI systems. As both nations continue to refine their e-court projects, it is essential to strike a balance between technological advancements and human oversight to ensure that AI contributes positively to the judicial process without undermining justice.

Moving forward, the development of a more transparent, fair, and efficient system will be vital for both countries in achieving a just legal environment.

REFERENCES

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WEBLIOGRAPHY

1. https://ecommitteesci.gov.in/project/brief-overview-of-e-courts-project

(visited on Nov 12, 2024)

2. https://pib.gov.in/PressReleasePage.aspx?PRID=2040232 (visited on Nov 8, 2024)

3. https://doj.gov.in/phase-iii (visited on Nov 15, 2024)

4. pacer.uscourts.gov (visited on Nov 17, 2024)

5. https://pacer.uscourts.gov/register-account/non-attorney-filers-cmecf (visited on Nov

24, 2024)

6. https://www.ias.ac.in/article/fulltext/reso/019/03/0198-0207 (visited on Nov 30, 2024)

7. https://www.drishtiias.com/daily-news-analysis/ai-portal-supace/print_manually

(visited on Nov 20, 2024)

8. https://morth.nic.in/bharatmalaphase (visited on Nov 17, 2024)

9. https://pcl.uscourts.gov/pcl/index.jsf (visited on Nov 17, 2024)

CONSTITUTION

1. The Constitution of United States, 1789