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

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arxiv 2404.12349 v1 pith:DTTT5P2B submitted 2024-04-18 cs.AI cs.HC

Rohan Bhambhoria , Samuel Dahan , Jonathan Li , Xiaodan Zhu This is my paper
classification cs.AIcs.HC
keywords legalopen-sourceaccuracyaddressingadvocatesbridgingchatgptclients
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. How Can AI Augment Access to Justice? Public Defenders' Perspectives on AI Adoption

    cs.CY 2025-10 conditional novelty 7.0 of 10

    Public defenders view AI as most useful for evidence investigation but limited in courtroom work and strategy, with adoption blocked by costs, confidentiality risks, and norms, requiring human oversight and open development.

  2. A Conceptual Framework for AI Capability Evaluations

    cs.AI 2025-06 conditional novelty 5.0 of 10

    A descriptive conceptual framework with seven elements (target, task, subject, inputs, instance, measurement, result analysis) for systematizing analysis of AI capability evaluations.

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