Bridging The Vernacular Divide: An Empirical Study of AIAssisted Legal Access in Jammu and Kashmir, India

Abstract

Access to justice entails not only availability of the court of laws and the avenues of justice but also that individuals can access and understand the legal information from which their rights and obligations arise. This becomes more important in linguistically diverse societies where understanding of the legal information becomes difficult. This could be also because of limited proficiency in legal English or due to the user other languages. This study examines the role of artificial intelligence (AI), including multilingual Large Language Models (LLMs) in improving access to legal information in the Union Territory of Jammu and Kashmir. The study adopts a descriptive, cross-sectional survey design involving 113 respondents - 31 legal educators and 82 law students. Though, the current study does not involve any benchmarking of AI technology; hence cannot be taken as means by which AI improves access to justice. Nevertheless, this study attempts to find out the conditions under which AI assisted legal accessibility may be pursued. The empirical findings are examined alongside constitutional provisions. The paper proposes an 'assistive bridge' model in which AI acts as an interface between individuals and legal materials rather than a source of the same or a substitute for human legal judgment.