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确定法律领域采用人工智能时面临的挑战的优先级:一项系统综述和专家驱动的层次分析法分析

Prioritizing challenges in AI adoption for the legal domain: A systematic review and expert-driven AHP analysis.

作者信息

Kim Sihyun, Yi Sangyoon, Park Sung-Pil

机构信息

Graduate School of Future Strategy, KAIST, Daejeon, Republic of Korea.

出版信息

PLoS One. 2025 Jun 24;20(6):e0326028. doi: 10.1371/journal.pone.0326028. eCollection 2025.

DOI:10.1371/journal.pone.0326028
PMID:40554557
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12186909/
Abstract

This research explores the crucial challenges influencing the adoption of Artificial Intelligence (AI) in the legal domain, a field facing escalating challenges due to rapid technological advancements. We have comprehensively identified, extracted, and evaluated 11 pivotal factors across legal, technical, and socio-ethical dimensions through a systematic review based on the PRISMA guideline. These factors are categorized into three principal groups. Utilizing an analytic hierarchy process (AHP), our innovative approach assesses the relative importance of these challenges based on data meticulously gathered from eight domain experts in law and AI. Our findings pinpoint legal aspects as the paramount category, with liability as the foremost concern among the analyzed factors. These insights offer robust and actionable guidelines for integrating AI into legal practices and underscore this study's unique contribution to bridging the gap between legal professionals and technology developers. By highlighting the practical applications of our results, this paper facilitates a deeper understanding and proactive engagement with the essential considerations pivotal for the future adoption and evolution of AI within the legal domain.

摘要

本研究探讨了影响人工智能(AI)在法律领域应用的关键挑战,由于技术的快速进步,该领域正面临着不断升级的挑战。我们依据PRISMA指南,通过系统综述,全面识别、提取并评估了法律、技术和社会伦理维度的11个关键因素。这些因素分为三个主要类别。利用层次分析法(AHP),我们的创新方法基于从八位法律和人工智能领域专家精心收集的数据,评估这些挑战的相对重要性。我们的研究结果指出,法律方面是最重要的类别,在所分析的因素中,责任是首要关注点。这些见解为将人工智能融入法律实践提供了有力且可操作的指导方针,并强调了本研究在弥合法律专业人员与技术开发者之间差距方面的独特贡献。通过突出我们研究结果的实际应用,本文有助于更深入地理解并积极参与对法律领域未来采用和发展人工智能至关重要的基本考量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/e01a8892520e/pone.0326028.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/c73f4c97401b/pone.0326028.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/1c9e95fb04d1/pone.0326028.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/579bafdefab8/pone.0326028.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/e01a8892520e/pone.0326028.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/c73f4c97401b/pone.0326028.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/1c9e95fb04d1/pone.0326028.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/579bafdefab8/pone.0326028.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/072c/12186909/e01a8892520e/pone.0326028.g004.jpg

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本文引用的文献

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Ethical, legal, and social considerations of AI-based medical decision-support tools: A scoping review.基于人工智能的医疗决策支持工具的伦理、法律和社会考虑因素:范围综述。
Int J Med Inform. 2022 May;161:104738. doi: 10.1016/j.ijmedinf.2022.104738. Epub 2022 Mar 14.
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A governance model for the application of AI in health care.人工智能在医疗保健领域应用的治理模型。
J Am Med Inform Assoc. 2020 Mar 1;27(3):491-497. doi: 10.1093/jamia/ocz192.
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Governing artificial intelligence: ethical, legal and technical opportunities and challenges.
治理人工智能:伦理、法律及技术方面的机遇与挑战。
Philos Trans A Math Phys Eng Sci. 2018 Oct 15;376(2133):20180080. doi: 10.1098/rsta.2018.0080.
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Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting.层次分析法在医疗保健研究中的应用:系统文献综述与报告评估
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