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Computer Science > Computers and Society

arXiv:2401.16212 (cs)
[Submitted on 24 Jan 2024]

Title:Better Call GPT, Comparing Large Language Models Against
Lawyers

Authors:Lauren Martin, Nick Whitehouse, Stephanie Yiu, Lizzie
Catterson, Rivindu Perera (Onit AI Centre of Excellence)
Download a PDF of the paper titled Better Call GPT, Comparing Large
Language Models Against Lawyers, by Lauren Martin and 4 other authors
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    Abstract:This paper presents a groundbreaking comparison between
    Large Language Models and traditional legal contract reviewers,
    Junior Lawyers and Legal Process Outsourcers. We dissect whether
    LLMs can outperform humans in accuracy, speed, and cost
    efficiency during contract review. Our empirical analysis
    benchmarks LLMs against a ground truth set by Senior Lawyers,
    uncovering that advanced models match or exceed human accuracy in
    determining legal issues. In speed, LLMs complete reviews in mere
    seconds, eclipsing the hours required by their human
    counterparts. Cost wise, LLMs operate at a fraction of the price,
    offering a staggering 99.97 percent reduction in cost over
    traditional methods. These results are not just statistics, they
    signal a seismic shift in legal practice. LLMs stand poised to
    disrupt the legal industry, enhancing accessibility and
    efficiency of legal services. Our research asserts that the era
    of LLM dominance in legal contract review is upon us, challenging
    the status quo and calling for a reimagined future of legal
    workflows.

Comments: 16 pages
Subjects: Computers and Society (cs.CY); Computation and Language
          (cs.CL)
Cite as:  arXiv:2401.16212 [cs.CY]
          (or arXiv:2401.16212v1 [cs.CY] for this version)
          https://doi.org/10.48550/arXiv.2401.16212
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Rivindu Perera [view email]
[v1] Wed, 24 Jan 2024 03:53:28 UTC (695 KB)
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