Quantum-Ledger Trust Protocol (QLTP): A Next-Generation Legal Framework for Cross-Border Digital Contracts

Abstract

The Indian judicial system is based upon constitutional principles of fairness and equality, the Indian judicial system has been criticized on account of probable biases in legal rulings, regarding caste, gender, and socio-economic factors. Manual reviews that are subject to human subjectivity also take quite some time, leading to difficulties in detecting systemic discrepancies. The focus of this thesis is to propose the use of an AI using Natural Language Processing (NLP) and Machine Learning (ML) technologies to perform the purpose of a Legal Sentiment Analysis System to analyze judicial rulings, courtroom transcripts, and legal documents. Deep learning models such as BERT and LLMs trained on Indian legal data are used to detect sentimental pattern, emotional tone, and potential bias on Indian legal texts that include judges' verdicts, Supreme Court opinions, case law entries in Hindu Law, Indian civil and criminal codes, Indian Income Tax judgements, etc. Also, there is an Automatic Speech Recognition (ASR) enabled to monitor courtroom discourse to abide by what happens in the court proceedings. Additionally, the proposed framework ushers in blockchain technology to utilize it to boost transparency by using these sentiments recorded within a blockchain. The experimental evaluations on Indian Supreme Court and High Court case datasets show its capability to identify the degree of disparity in the pattern of sentencing with high accuracy. This AI-based approach provides policymakers and legal professionals with time and data-driven insights to ensure judicial fairness as well as unbiased legal decision-making in India through a scalable, transparent, and efficient means.