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THE USE OF ARTIFICIAL INTELLIGENCE IN JUDICIAL DECISION MAKING: AN ASSET TO THE JUDICIARY

Introduction

The emergence of newer technology is continuing to change the way in which the world functions and works. There is a shred of significant evidence that such technologies could replace or support human activities and the judiciary is not an exception. In decision making the role of a judge comprises interactions with the public interactions with the public, activism, case management, and dispute settlement. Such activities vary across judges and jurisdictions. In India, there exists an enormous amount of pending cases in the court that puts the judiciary under more pressure. As of January 2021 there were over 67,279 pending cases in the Supreme Court and 57,53 lakh cases pending in the High Court’s. This is due to the shortage of judges. The system's inefficiencies obviates that human judgment alone cannot be relied on for a solution. However, a question remains - should judicial functioning concerning specific disputes must remain a human activity?. There is no doubt that with the use of technology an immediate transformation of judicial conduct might not be seen, but certain functions will see an improvement. The article through the following sections will address the use of artificial intelligence in law, the incorporation of artificial intelligence in the judiciary and also discusses the challenges that will exist with such an incorporation.

The Meaning of Artificial Intelligence

In recent times, of the term ‘artificial intelligence’ has been loaded with different assumptions and preconceptions. Therefore in this article, the term artificial intelligence will be an autonomous non-biological entity with the ability to give rules. It can be also understood as certain algorithms which supplement decision-making of judges. Hence, artificial intelligence can be defined as making computer machinery carry out certain activities in an intelligent way that is similar to human beings, where they replicate the cognitive function of humans such as learning and problem-solving.

Artificial Intelligence and the Law

AI has influenced lives across branches ranging from healthcare to education and even to transportation, , paving way for some revolutionary changes. The legal system has also similarly been influenced by AI. Legal work contains a great deal of activities that are monotonous in nature, this includes searching for irregulates in data, analysis, and most importantly documentation. In many places in the US, legal reviews assisted by software such as CaseCrunch have already received stamps of approval by the judiciary. In India, the Supreme Court has tried to embrace AI by developing the SCI software in order to make paperless benches, but the use is limited due to the lack of enthusiasm by judges. The emergence of AI in the judicial process in India shall help in solving the bias and lack of transparency in the judicial system by ensuring that the system is more accountable and transparent. By incorporating AI, A judge can either chose to ignore the opinion provided by the AI or cite the reasoned submission given by it, thereby allowing the AI software system to function as an assistive tool to the judiciary. For example, in China, Wusong Technology is working on a way to digitize the functions of court by using “FaXiaotao” an AI-enabled robot which aids in locating lawyers and providing a case analysis. In India, Cyril Amarchannd Mangaldas has partnered with the Canadian AI assistance Kira systems and used the power of AI for contract analysis. Lawyers rely on AI software’s for speedy disposal of a case. AI systems can be used to review contracts and documents, it also can assist in analyzing the quality of the relevant evidence and legal claims. This would organize the cases and detect cases with a similar pattern which automatically reduces the pendency Hence, if judges incorporate aspects of AI system in decision making it will provide for an overall lesser time in deciding a case.

Incorporation of AI in the Judicial System

There exist certain challenges to AI which means that they are intentionally or unintentionally vulnerable to hacking or attacks. Certain studies believe that AI systems reduce the decision making efforts and it increases the quality of the decision by a person, This can lead to the judges not applying their own mind due to the insufficient resources and the higher caseload. Hence, it is believed that using such computer systems worsen the condition of the adjudication processes rather than improving it. However, this can be remedied by the inclusion of technology training at the university level itself. For instance, the Melbourne law school provides a course that allows students to explore potential AI applications in the legal field. This will provide for an understanding at the grass-root level itself and hence, further challenges could be avoided.

Regardless, AI as a tool has proved to be efficient in assisting legal practice. The Pendency of cases is one of the biggest drawbacks of the judicial system. The reasons identified for such a drawback were the insufficiency of staff in courts, the incorporation of AI systems will help this issue as it can act as an aid to the Indian courts by managing issues concerning filing cases, investigation and collection. By using predative analytics for settlement and visualization, AI can help the court in providing the parties with a probable result which will compel them into an out of court settlement which will reduce the pendency of cases in the court. Reading, analyzing and summarizing the contents of a document can also be done by AI systems in Courts. AI can reduce inaccuracy in cases. Human errors have existed from time immemorial; however, when a program is incorporated, the potential of a computer making errors is null. AI systems follow the principle of making decisions based on algorithms which therefore provide accuracy and helps in cutting off errors. Although, using AI systems can lead to a lack of creativity and be an exorbitant system for Indian courts the pros are greater than the cons in this case.

Further, judicial data can be used for AI by granting access to the available judicial statistics which will result in innovation. Such statistics include quantitative figures which are published by the National Data Judicial Grid that portrays different facets of the judicial system. Providing such judicial statistics can result in better analytics of data by AI systems. Further, under common law precedents are binding law. Therefore, having an understanding of such precedents by using the pool of already existing judgments and cases, this will improve the access to justice and it greatly would benefit the common litigant and such a system can be facilitated by AI software. Hence, if the judiciary needs to utilize the potential of AI systems it needs to utilize the current and existing data. ‘SUVAS’ is an example of a machine that is used by the Supreme court to translate judgments to regional languages and a comprehensible format but it is not widely used, due to the question of reliability. Such a software increases accountability as it easier for judgements to reach the public in their vernacular language.

Conclusion

A clear separation of AI adjudication and human-generated decisions will allow a smooth function of AI software if incorporated in courts. This is because for certain cases which are difficult to decide, a human-generated judgment would provide adequate justification while an AI-generated decision would not provide for the same as it lacks explanation even if it is the more accurate. Even though introducing AI into the judiciary is a delicate matter it would be highly efficient if done with patience and precaution. It will assist judges in various tasks during the proceedings and shall reduce the time it would normally take to render a judgment.


Title Image: The Conversation


This article has been written by Arya Kumar & Netra Vasudevan. They are both 4th year law students studying at School of Law, Christ (Deemed to be University).