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This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It suggests leveraging foundational models enhanced by domain-specific knowledge to overcome these issues. The paper advocates for creating open-source legal AI systems to improve accuracy, transparency, and narrative diversity, addressing general AI’s shortcomings in legal contexts.

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Evaluating AI for Law: Bridging the Gap with Open-Source Solutions

  • 章节

  • 发表日期：

    2026年

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  • Rohan Bhambhoria,
  • Samuel Dahan,
  • Jonathan Li,
  • Xiaodan Zhu

摘要

This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It suggests leveraging foundational models enhanced by domain-specific knowledge to overcome these issues. The paper advocates for creating open-source legal AI systems to improve accuracy, transparency, and narrative diversity, addressing general AI’s shortcomings in legal contexts.