公平获取司法：逻辑LLM展现潜力
Equitable Access to Justice: Logical LLMs Show Promise
AI总结：
本文探讨将LLMs与逻辑编程结合以增强法律推理能力，证明OpenAI o1-preview能成功编码保险合同为逻辑程序，从而提升司法可及性。
摘要：
美国司法系统的成本和复杂性限制了许多美国人获得法律解决方案的途径。大型语言模型（LLMs）在改善司法获取方面具有巨大潜力。然而，在一致性和可靠性至关重要的法律语境中应用AI和LLMs，一个主要挑战是需要System 2推理。本文探讨了将LLMs与逻辑编程相结合以增强其推理能力，使其战略能力接近熟练律师。我们的目标是将法律和合同转化为可应用于特定法律案件的逻辑程序，重点关注保险合同。我们证明，尽管GPT-4o未能将简单的健康保险合同编码为逻辑代码，但最近发布的OpenAI o1-preview模型成功了，展示了具备先进System 2推理能力的LLMs如何扩大司法获取。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
