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  • Writer's pictureRitik Agrawal


Updated: Jan 16

Author: Riya Arora

Vivekananda Institute of Professional Studies

What is AI?

Computer programs that aim to imitate human cognitive processes are referred to as "artificial intelligence." This includes "machine learning," in which algorithms find new patterns in data and use them to automate certain operations.

Along with these methods, artificial intelligence also includes neural networks (systems fashioned after the structure of the brain), natural language processing (the capacity to speak informally, as in the well-known Test), and the central idea of machine learning. The word "AI" is used throughout this work in its broadest definition. Reasoning, knowledge, planning, communication, and perception are among the long-term objectives of AI research; at the moment, we are a long away from fully fulfilling these objectives.

"General AI," which mimics human intellect such that any work may be completed, is a longer-term goal. Theoretically, this might result in "The Singularity," a time when computers will surpass human intelligence. Bill Gates and Stephen Hawking are two pundits who are worried about the possible negative effects of general artificial intelligence. However, a lot of well-known pundits think that General AI is at least theoretically viable.

AI will advance due to both the creation of new algorithms and the growing computing capacity of computers themselves. With the transition from serial to parallel processing in computing, more computations may now be completed simultaneously.


Document analysis: The University of Cambridge, Slaughter and May, and other researchers developed a technology called Luminance that is predicted to revolutionize this field. The whole transaction process will be improved for law firms and their clients by modeling how lawyers think to create important findings without having to be instructed on what to search for. Former Autonomy CEO Mike Lynch is supporting the system. It was recognized as the "Best AI product in Legal" at the first CogX AI Innovation Awards in June, and 26 organizations in 12 countries are presently using it.

Support for legal advisers: US law firm Baker Hostetler has partnered with ROSS, a business that builds on IBM Watson, to create a legal adviser (ROSS Intelligence 2016). ROSS analyses the pertinent law stored in its system, gathers evidence, develops conclusions, and then offers highly relevant, fact-based candidate solutions. Lawyers ask ROSS their research query in plain language, just as they would a human. Additionally, ROSS continuously analyses the law to alert users to fresh court rulings that can influence a case. The software continuously picks up knowledge from the attorneys who utilise it, resulting in consistently improved results.

Case result prediction: University College London, University of Sheffield, and University of Pennsylvania researchers used an AI system to find commonalities in the language of the court rulings in 584 cases that were heard by the European Court of Human Rights.

The programme was able to predict the result of subsequent cases with 79% accuracy after learning from these cases. It concluded that non-legal characteristics, such as language employed, themes addressed, and situations stated in the case text, were more dependable predictors of case outcomes than legal argument.

Public legal education: The University of Cambridge also contributed to LawBot with the goal of assisting regular citizens in understanding the legally complex issues associated with 26 major criminal offenses under English and Welsh law and in selecting which legal options to pursue with an experienced attorney (Connelly 2016). Recently, the initiative has emphasized divorce law (Divorce Bot)


These advancements imply that there will be several chances for the application of artificial intelligence in the legal field, which might have significant ramifications.

The following are the most likely effects:

• A decrease in the number of legal positions, first at lower levels of staff

• Modifications to legal education and training as a result of changes in the nature of legal occupations, which emphasise human abilities (LET)

• Modifying organisational and business paradigms

• Lower prices and evolving charge schedules.


Judicial delays are evident when we examine the Indian court system. Justice delayed is justice denied, and the judiciary is overwhelmed with more than 3 Cr. outstanding cases, which causes undesirable delays in providing justice to the people. As a result, several initiatives are being made to better the present state of affairs, such as shortening vacation times and strengthening judgement, but more has to be done, which is where artificial intelligence comes into play.

Few actions have been done to aid judges in case management. Each year, thousands of cases with mostly comparable facts are filed. Analyzing how these instances are developing at each step is rarely attempted. To facilitate a swift resolution of the case, judges must be well-versed on the potential directions it may go. As was already noted, judges can be helped by data science and artificial intelligence (AI), which can forecast crucial information about an ongoing case based on precedents of a similar kind.

For this analysis, a number of case details that are recorded in the daily orders and the final judgement can be used, including the number of accused in a case, the date the charge sheet was filed, the number of witnesses questioned during the evidence stage, the number of hostile witnesses, the reasons for adjournments, the specifics of the First Information Report (FIR), the severity of the punishment, the amount of compensation awarded, etc. Judges can make better strategic judgements by analysing these elements, which can assist shorten case delays.

AI is extremely helpful for gathering evidence. According to research, the evidence stage occupies a significant amount of the court's time and is crucial in the progression of a case. For a variety of reasons, including extra time requested by the parties or attorneys, delay caused by the investigation officer, the unavailability of witnesses, etc., many adjournments are requested during the evidence stage. Artificial intelligence systems would be useful in anticipating future delays since judges might list items and manage their workload more effectively if they were aware of the main reasons for delays for a certain kind of cases at a given stage in advance. Judges may use it to anticipate issues that will lengthen the trial.


Artificial intelligence in law is still in its infancy when we look at India. Because they think it would harm employment, lawyers are unwilling to accept this technology. They worry that technology will replace the main source of income for a lawyer or a legal assistant, leading to a rise in unemployment across the nation. The majority of seasoned attorneys are reluctant to alter their daily routines and prefer to practice law the old-fashioned manner, without the aid of artificial intelligence.

AI machines require a considerable financial investment since they are complex machine systems that are able to learn and react on their own. Only large legal firms can purchase AI-driven machines since they are mostly produced by foreign businesses, making it even more challenging for small and midsized law firms to acquire them.

It's crucial that AI-driven machine learning robots are constructed in a way that protects the parties' private information. It is even more crucial that the legal framework ensures that the data is not exploited, that confidentiality is maintained, that a fair due process is followed, and that a security layer to avoid privacy breaches is provided since machine learning uses vast volumes of data.

AI: A substitute for lawyers?

In the world of law, several cutting-edge innovations have been launched, increasing lawyer productivity through contract analysis, trademark search software, legal research software, and other means. But none of the AI-based software aspires to displace attorneys; rather, it works to increase the veracity and precision of research and analysis.

The legal industry in India is still developing, and more AI-based and automated software and tools are on the way. The analysis, stratification, and decision-making required by the legal profession will not be replaced by these AI-based automated assistance programmes; rather, they will improve lawyers' efficiency and competence while automating many clerical tasks.


We must adopt a balanced strategy to make sure AI is included. Here are some recommendations:

1) It is essential to establish a strong legal framework outlining the responsibilities and liabilities of this intelligent machine.

2) In order to control its behaviour, the accountability component must be taken into account.

3) Stricter data protection laws are needed to preserve privacy. Therefore, the solution is to welcome technological advancements rather than resist them and use AI to our advantage by putting the required laws in place to safeguard its users' interests.


  1. Thomas, Sachu Saji. "AI and Revolution to Judicial System." Indian JL & Legal Rsch. 3 (2021): 1.

  2. Sharma, Mohit. "India's courts and artificial intelligence: A future outlook." LeXonomica 15.1 (2023): 99-120.

  3. Srivastava, Sunil Kumar. "AI for Improving Justice Delivery: International Scenario, Potential Applications & Way Forward for India." Informatica 47.5 (2023).

  4. Sil, Riya, Alpana, and Abhishek Roy. "A review on applications of artificial intelligence over Indian legal system." IETE Journal of Research (2021): 1-10.

  5. Manvee. "Predictive Justice with Artificial Intelligence: Enhancing Efficiency and Accuracy of Judiciary." Legal Spectrum J. 3 (2023): 1.

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