Equitable Access to Justice: Logical LLMs Show Promise
Keywords: Access to justice, OpenAI o1-preview, reasoning, computable contracts, LLMs
TL;DR: Advances in System 2 reasoning for foundation models (i.e. OpenAI o1-preview) have increased the scope for LLM (indeterministic) + logic programming (deterministic) legal solutions in expanding access to justice.
Abstract: 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.
Submission Number: 48
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