2024/10/13 by Manuj Kant, Manav Kant, Kant, Manuj +7 · 2 citations
Social Sciences · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Judicial and Constitutional Studies #Legal Education and Practice Innovations #Legal Systems and Judicial Processes #Logic in Computer Science (cs.LO)
paper · pdf · doi:10.48550/arxiv.2410.09904
openalex publication_date 2024/10/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The costs and complexity of the American judicial system limit access to legal solutions for many Americans. Large language models (LLMs) hold great potential to improve access to justice. However, a major challenge in applying AI and LLMs in legal contexts, where consistency and reliability are crucial, is the need for System 2 reasoning. In this paper, we explore the integration of LLMs with logic programming to enhance their ability to reason, bringing their strategic capabilities closer to that of a skilled lawyer. Our objective is to translate laws and contracts into logic programs that can be applied to specific legal cases, with a focus on insurance contracts. We demonstrate that while GPT-4o fails to encode a simple health insurance contract into logical code, the recently released OpenAI o1-preview model succeeds, exemplifying how LLMs with advanced System 2 reasoning capabilities can expand access to justice.