This Article Is Written By Ayush Kumar, 4th Year B A LL.B University Of Lucknow, Lucknow, During Internship At Ledroit India.
Keywords
Artificial Intelligence (AI), Machine Learning (ML), Legal Regulation of AI, AI Ethics and Accountability, Algorithmic Bias, Data Privacy and Protection, Automated Decision-Making, AI in Judicial Systems, Techno-Legal Framework.
Abstract
Almost all professional fields throughout the world have had technological revolutions. To be precise, the driving factor behind this transition or revolution has been the application of big data. Better judgments and actions to address problems have been calculated with the use of data compilation to establish a certain pattern and provide results that are only data specific and unaffected by extraneous outside variables like human error. Laws have remained strict and traditional in the face of technological advancement. The introduction of online databases as the first step in changing the legal education system made it much easier for professionals and law students to work efficiently and provide results on time with Minimum Errors.
What is AI
Any intellect exhibited by a computer, robot, or other machine that resembles that of a person is referred to as artificial intelligence (AI). The term artificial intelligence refers to the ability of a computer or machine to mimic the functions of the human brain, such as learning from models and experience, perceiving objects, understanding and responding to language, making decisions, and resolving problems. These and other abilities can then be combined to perform tasks that a human could perform, such as greeting a guest at a hotel or operating a vehicle. Artificial intelligence is predicated on the idea that human intellect can be described in a way that allows a computer to reproduce it and carry out tasks ranging from the simplest to the most complex.
Big Data and Law –
Legal analytics, or the use of data to assist attorneys and legal decision-makers in improving their work—such as forecasting results, allocating resources, and reducing expenses—is one way artificial intelligence is being used in the legal field. To put it simply, it’s a method of transforming legal facts into insightful knowledge to help in decision-making. Legal Analytics leverages AI and big data to speed up and improve the accuracy of legal research, much like we do when searching internet databases for legislation and previous rulings. It improves efficiency, saves time, and aids attorneys in making more accurate case predictions.
Application Of ICTs in Legal Education
ICT- Information and Communication Technology
The legal profession is seen as honourable from the beginning. Therefore, it is necessary to have the best legal education system. 18 Law schools and universities have long had a low priority for using ICTs to teach law. Consequently, they face several difficulties, such as reduced enrolment, fewer legal professionals, and the inability of recent graduates to argue their arguments in court, among other factors, which resulted in the closure of several law schools. In contrast, there is compelling potential for technology to enhance the efficacy and efficiency of legal education. For this reason, all legal schools are working to provide ICT facilities in the modern world:
The electronic equivalents of printed books are called e-books. In addition to text, the e-books provide multimedia features, search features, and hyperlinks. Additionally, e-book compilers transform source files into readily distributable forms like RTF, HTML, and PDF. To put it another way, an e-book is a book that has electronic material that the reader can see.
Electronic Books – The electronic equivalents of printed books are called e-books. In addition to text, the e-books provide multimedia features, search features, and hyperlinks. Additionally, e-book compilers transform source files into readily distributable forms like RTF, HTML, and PDF. To put it another way, an e-book is a book that has electronic material that the reader can see.
E-Journals – Electronic journals are magazines produced on a regular basis, usually online. There are a number of advantages that electronic publications provide over traditional printed journals. To locate the article of their choosing, students can browse the journal’s full text content page. They are able to .They don’t need to be in the library to read it; they can do it anywhere on their computers or even on their phones. For future use, students can store the journal on their laptops or desktop computers.
Introduction: Courtroom Innovation in the Contemporary World
From digital evidence analysis to predictive policing and case law study, the nexus of artificial intelligence (AI) and machine learning (ML) is changing the legal landscape. But while India’s top courts are gradually adopting new technology, the lower judiciary is still lagging behind because of inadequate infrastructure, a lack of established procedures, and digital illiteracy. Particularly in rural and semi-urban regions, where the majority of trial courts are located, this technology disparity not only exacerbates the efficiency gap in the legal system but also has an impact on prompt access to justice. The load on lower courts might be greatly reduced by integrating technology and artificial intelligence (AI) into judicial processes, including document review, case management, evidence collection, and summons. But there are intricate issues with algorithmic bias, transparency, and the requirement for a robust techno-legal framework. AI systems run the danger of reproducing preexisting biases or making ambiguous judgments without human oversight if proper protections are not in place. Additionally, for AI in court systems to be genuinely successful at the local level, it must be tailored to local languages and legal realities.
In addition to these practical difficulties, the emergence of AI-powered technologies in society also brings up significant issues with data privacy, AI ethics, and legal control of AI, particularly when it comes to situations involving deepfakes, morphing photos, intellectual property rights, and copyright infringement. Because Indian law presently lacks comprehensive rules to control AI-generated material, courts, especially those at the lower level, are ill-prepared to manage new challenges such as ownership of AI-created works, synthetic media evidence, and intellectual property infringement. Our judicial system must develop together with AI and ML to maintain accessibility, impartiality, and responsiveness in this new digital age.
For instance, a more technologically advanced method to criminal processes is introduced by the recently passed Bharatiya Nagarik Suraksha Sanhita (BNSS), 2023, which supersedes the Criminal Procedure Code (CrPC), 1973. Because they deal with the issue of summonses, Sections 63 and 227 of the BNSS are important in this situation. These clauses provide the court the authority to call people to attend in the proceedings, including the complainant’s witnesses, the accused, and any witnesses of the accused. Previously, the CrPC either prohibited or did not specifically recognize the use of electronic communication (e.g., email, SMS, or electronic platforms) for summons or notifications. Administrative backlogs, reliance on manual delivery by police or process servers, and service delays resulted from this. Nonetheless, it is not only acceptable but also strongly encouraged in the BNSS to serve summonses and legal documents by electronic communication. This illustrates the court system’s gradual transition to digitalization and procedural efficiency.
Even with these legislative developments, there are still many issues with actual execution. In India, lower courts frequently lack the necessary digital infrastructure, including video conferencing capabilities, secure servers, and staff with the necessary skills to oversee virtual appearances and e-summons. Furthermore, there is a lack of public awareness, especially in rural regions where many people are not aware that they have the right to receive or reply to court communications via digital channels.
Because of this, the potential of technology to speed up legal proceedings is still not fully harnessed. Delays frequently persist because of the court’s reluctance to completely embrace the electronic method because of reservations regarding access, legitimacy, or procedural clarity, or because of the continuous reliance on antiquated manual procedures.
Supporting Developments and Similar Provisions –
1. Electronic communication is also permitted for the serving of processes, such as notifications and orders, under Section 105 of the BNSS.
2. Digitizing summonses, warrants, and legal notifications is a crucial step in judicial modernization, according to the Ministry of Law and Justice’s Justice Delivery and Legal Reforms Committee.
3. As of 2024, only 40–45% of district and subordinate courts had a reliable infrastructure for frequent video conferencing (despite e-Courts Phase II and III projects), and only a small percentage had included e-Summons modules into their daily case process.
4. Video conferencing has previously been acknowledged by the Supreme Court of India in cases such as State of Maharashtra v. Dr. Praful Desai (2003).
“AI and Machine Learning in Legal Practice: Enhancing Analysis, Research, and Decision-Making”
By making important information instantly accessible, these technologies are relieving litigants and attorneys of the manual strain. Lawyers no longer spend hours reading legal documents; instead, they use intelligent databases and predictive technologies that not only find pertinent legislation and court decisions but also make predictions about the probable outcomes of cases based on previous decisions. Decision-making in the legal industry is moving away from intuition and toward data-driven analysis thanks to AI-enabled technologies like contract analyzers, document automation software, and predictive coding systems. This is especially crucial at a time when data is becoming a key component of legal strategy; people who have better access to and comprehension of data are frequently better prepared and more convincing in court.
AI in Law: Opportunities on the Horizon
Three main perspectives, specifically (1) data, ; (2) algorithms, and ; (3) implementation, limit the development and application of AI for the planning of legal administrations. Data is a fundamental component of AI frameworks, serving both as information for the actual application of AI as well as preparation material for developing AI algorithms. The lack of readily available and analyzable datasets limits the development and application of AI algorithms in the planning of legal administrations. According to the saying, the majority of law offices are “archive rich and data poor,” meaning that public data, such as legal decisions and conclusions—is either unavailable or so dissimilar in design that it is difficult to use effectively.
Furthermore, AI frameworks may produce biased conclusions due to poor or flawed datasets. . For a variety of reasons, datasets may be imperfect or of poor quality. For example, the data may show human propensity, such as the sex segregation of up-and-coming vocation spotters. Planning techniques or data assortment may introduce real biases into the dataset, such as choosing tendency or unrepresentative samples. It is also possible to purposefully manipulate or corrupt datasets in order to produce biased research. In addition to problems with data quality, significant data protection and network security challenges also surface when AI frameworks use enormous volumes of data.
The application of AI in the legal industry is also influenced by algorithmic constraints. ” According to the concepts mentioned above, every AI framework now in use carries out an unquestionably distinct arrangement of operations. When there are well-defined data designs and a comprehensive response, man-made intelligence functions at its finest. When used in hypothetical or open-ended situations that call for judgment, such as those that legal counsel commonly encounter, it is ineffective. Under these circumstances, human ability and knowledge are still fundamental to the course of events, and the available AI systems are still insufficiently developed to understand and adapt to nuances, respond to presumptions and layered significance, and grasp the common sense aspects of human experience. As a result, AI is still far from completely replacing people in the legal profession.
The use of AI is further limited by issues that arise throughout an organization’s AI execution cycle, and this viewpoint would also benefit from more research facilities. In the first place, being aware of the strategy and impact of AI setups in this particular field that have The productivity gains that AI frameworks can provide may not be enhanced by many hourly-based plans of action, such as those typically used by law enforcement. A well-defined use case and work measure, strong specialized expertise, extensive personnel and algorithm preparation, professional change management measures, a desire for change, and the ability to work with the latest developments are also necessary for the successful deployment of AI. Prospective AI customers should understand that effectively communicating the technology may require more work than they would think. Getting anticipated clientele to understand and trust the technology may be the finest test, but it’s not actually expressing it.
Illustration :
1. Postponement of Bail Order Transfer to Jail
If the accused is not freed right away because digital transmission facilities are unavailable or because platforms such as e-Prisons or e-Courts are not employed, this will be considered an administrative lapse rather than a legal procedural need.
2. Delay in Issuance and Service of Summons
A delay in summons service that results from the failure to use digital service methods or from a court officer’s ignorance of available technology (like e-Summons or secure messaging portals) will not be ascribed to the legal system but rather to operational inefficiencies.
3. Lack of Knowledge Among Court Officers
If the officer’s lack of familiarity with digital systems or new legislative revisions causes the act to be delayed or executed erroneously, this will be viewed as a result of administrative training deficiencies rather than a flaw in the legal process itself.
Conclusion-
In the legal industry, the confluence of information and communication technologies (ICTs), machine learning (ML), and artificial intelligence (AI) is causing a major shift. Legal practitioners benefit from these technologies because they improve research, document review, case prediction, and decision-making. Lawyers are able to make data-driven choices and obtain pertinent information promptly thanks to AI-powered technologies like legal analytics and predictive coding, which are replacing hours of manual labour. Nonetheless, there is still unequal acceptance of these developments throughout India’s legal system.
The lower judiciary continues to face challenges with outmoded procedures, inadequate digital literacy, and inadequate infrastructure, despite the Supreme Court and other higher judicial institutions having made strides in using digital techniques. Digital processes like video conferencing and e-summons have been promoted by legislative initiatives like the BNSS 2023, but on-ground implementation is still behind. In rural and semi-urban courts, a lack of technology and skilled staff frequently causes delays rather than legal errors.
Administrative inefficiencies, such as the inability to serve digital summonses or the delayed transfer of bail orders, underscore the critical need for better resource allocation, awareness, and training. Furthermore, the accuracy of data and algorithmic fairness are critical to the success of AI in law. Human inspection is crucial since faulty datasets and biased programming might produce unreliable results.
Building a strong digital infrastructure, standardizing legal data, and educating court employees and legal experts are all important steps India has to take to fully utilize AI in judicial institutions. Furthermore, it is necessary to address ethical issues, including responsibility, algorithmic transparency, and data protection. AI should not be viewed as a substitute for human judgment, but rather as an aid that improves the administration of justice.
In the digital era, a judicial system that is more accessible, effective, and equitable might result from a well-balanced merger of technology and law.
