Artificial intelligence for the justice system will help reduce case times

SUVAS, a machine learning tool for processing language, is already being used to translate SC judgments into regional languages.

There are nearly 4.4 million cases pending in Indian courts at all levels – the Supreme Court, high courts and district / taluka courts. Most of these cases have been pending for over a year. As FE pointed out earlier, there are many underlying factors, from a chronic shortage of judges to poor infrastructure. But resolving these issues alone will not help, as the 2018-19 Economic Survey showed, as resolving outstanding cases by 2024 would require going beyond just meeting the workforce. sanctioned by lower courts, already nearly 20% less than the number of judges sanctioned. The pandemic which makes judging cases in person in the usual way a significant risk of transmission only exacerbates this problem. Thus, solutions that speed up litigation processes and work by increasing productivity, such as the deployment of artificial intelligence (AI), have become all the more vital. India has already started by deploying SUVAS (Supreme Court Vidhik Anuvaad Software) in November 2019 and SUPACE (Supreme Court Portal for Assistance in Courts Efficiency) earlier this month.

SUVAS, a machine learning tool for processing language, is already being used to translate SC judgments into regional languages. With rapid access to case law as defined by SC judgments, in a format understandable to all, it is likely that the judicial processes of higher courts and lower courts could be accelerated. SUPACE, an AI-assisted composite tool, can be used to increase the efficiency of legal researchers and judges; he will read the case files, extract the relevant information, write the case documents and manage the division of work. If the facts and arguments relevant to judging a particular case were intelligently presented in seconds – done manually, it would have taken months – judgment could become much faster. According to a report on, SUPACE is customizable, that is, it can behave uniquely as an individual user, learning and reflecting user behavior; to illustrate, imagine a system that learns to glean relevant data and present it in a structure that a judge / legal researcher finds easy to understand or present. As with any AI, as the system “learns”, efficiency jumps exponentially. The SUPACE system also includes a chatbot that can give an overview of a case, answer basic questions, while switching between documents and prompting other questions to refine the user’s understanding of a subject; the logical door on which the chatbot is based constantly captures elements of knowledge, thus refining the answers to factual and contextual questions.

While the Supreme Court has ordered higher courts to start using the system, the deployment of AI would also raise many questions about the reliability of these systems and the chances that human biases will continue or even increase. To that end, AI researchers will be faced with thorny questions, but nothing that cannot be resolved with the march of technology. To build trust, broad consultation processes need to be undertaken. Transparency on the selection of data / information by AI systems and their analysis would be vital.

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