Human Centered AI for Indian Legal Text Analytics
This addresses the need for more reliable and effective AI tools in legal research, which is crucial for legal professionals, but it appears incremental as it builds on existing LLM methods with human integration.
The paper tackles the problem of low trustworthiness and data scarcity in applying generative AI to legal text analytics by proposing a human-centered compound AI system that integrates human expertise to enhance performance, introducing a novel dataset for this purpose.
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.