A Study on Judicial System and Implementation of an AI-Driven Judicial Process in India

Abstract

India's judiciary is crucial for maintaining democracy, yet it faces significant challenges, particularly the overwhelming backlog of civil cases. This persistent issue not only delays justice but also undermines public trust in the legal system. This paper examines the Indian court system to identify inefficiencies and propose innovative solutions aimed at expediting justice delivery, focused on civil cases. The study introduces a new Case Management System that integrates a decentralised AI model with human oversight, utilising Retrieval-Augmented Generation (RAG), an AI technique that enhances the accuracy and relevance of generated content by retrieving pertinent information from an external knowledge base while leveraging the generative capabilities of language models. By automating initial case assessments based on legal memorials submitted by a panel of accredited legal officials, this system aims to streamline the judicial process, improve efficiency, and ensure human accountability.The open-source nature of the decentralised AI model fosters transparency and community collaboration, while RAG grounds the AI's decision-making in human-led processes. This innovative approach not only addresses the backlog of civil cases but also seeks to minimise human biases, promoting a more impartial and objective judicial experience. To implement this system effectively, several key considerations must be addressed, including compliance with existing laws and regulations, cultural acceptance among stakeholders, and a thorough analysis of the ethical implications of AI in judicial processes. By overcoming these challenges, this research aspires to establish a more efficient and accessible justice system, ultimately delivering speedy justice for civil cases in India.