Human Centered AI for Indian Legal Text Analytics

TL;DR

This paper discusses the integration of human expertise with large language models in legal text analytics for Indian legal texts, proposing a novel dataset and a human-centered AI system to improve trustworthiness and performance.

Contribution

It introduces a new dataset and a human-centered AI framework that combines human inputs with LLMs for enhanced legal text analytics in India.

Findings

Proposed a human-centered AI system for legal text analysis.

Created a novel dataset for Indian legal texts.

Highlighted the importance of human-AI collaboration in legal applications.

Abstract

Legal research is a crucial task in the practice of law. It requires intense human effort and intellectual prudence to research a legal case and prepare arguments. Recent boom in generative AI has not translated to proportionate rise in impactful legal applications, because of low trustworthiness and and the scarcity of specialized datasets for training Large Language Models (LLMs). This position paper explores the potential of LLMs within Legal Text Analytics (LTA), highlighting specific areas where the integration of human expertise can significantly enhance their performance to match that of experts. We introduce a novel dataset and describe a human centered, compound AI system that principally incorporates human inputs for performing LTA tasks with LLMs.