用大模型帮孟加拉人解决法律难问题
Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modeling
- 构建孟加拉法律英文语料库，微调GPT-2模型
- 专家评估显示模型在案例分析中表现良好
- 适合想低成本获取法律帮助的普通民众
孟加拉国法律体系面临延误、复杂、成本高及数百万案件积压等问题，导致民众因缺乏知识或经济能力而不敢诉诸法律。本研究旨在开发专用大语言模型以支持该国法律系统。通过收集和抓取各类法律文件，构建了英国法律文档英文语料库UKIL-DB-EN。在此基础上，对GPT-2模型进行微调，得到专注提供英文法律援助的GPT2-UKIL-EN模型。通过语义评估与专家意见支持的案例研究对模型进行严格测试，结果表明其具备辅助处理孟加拉法律事务的潜力。本工作是首次系统性尝试为孟加拉国构建基于AI的法律助手。尽管结果令人鼓舞，但仍需进一步优化模型准确性、可信度与安全性。这是迈向服务1.8亿人口法律需求的一步。
原文摘要 · Abstract (English)
Purpose: Bangladesh's legal system struggles with major challenges like delays, complexity, high costs, and millions of unresolved cases, which deter many from pursuing legal action due to lack of knowledge or financial constraints. This research seeks to develop a specialized Large Language Model (LLM) to assist in the Bangladeshi legal system. Methods: We created UKIL-DB-EN, an English corpus of Bangladeshi legal documents, by collecting and scraping data on various legal acts. We fine-tuned the GPT-2 model on this dataset to develop GPT2-UKIL-EN, an LLM focused on providing legal assistance in English. Results: The model was rigorously evaluated using semantic assessments, including case studies supported by expert opinions. The evaluation provided promising results, demonstrating the potential for the model to assist in legal matters within Bangladesh. Conclusion: Our work represents the first structured effort toward building an AI-based legal assistant for Bangladesh. While the results are encouraging, further refinements are necessary to improve the model's accuracy, credibility, and safety. This is a significant step toward creating a legal AI capable of serving the needs of a population of 180 million.
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