人工智能与真实决策:预测系统和生成式人工智能与情感认知法律审议。

IF 2 Q2 SOCIOLOGY
Frontiers in Sociology Pub Date : 2024-10-30 eCollection Date: 2024-01-01 DOI:10.3389/fsoc.2024.1417766
Francesco Contini, Alessandra Minissale, Stina Bergman Blix
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引用次数: 0

摘要

人工智能在法律中的应用是不同法律体系面临的最大挑战之一。预测系统的支持者认为,使用人工智能可以提高决策的效率、一致性和可预测性。然而,欧洲立法和法律学者指出了人工智能发展的高风险领域,或者说在司法程序中使用人工智能过于危险。在本文中,我们将对基于以往判决的预测系统以及在司法程序中越来越多地使用生成式人工智能提出质疑,从而为这一辩论做出贡献。通过对意大利法院和检察院真实刑事案件的举例说明,我们展示了人工智能系统的功能与法律决策基本特征之间的错位,并确定了可能的合法用途。我们认为,当前的预测性系统和生成式人工智能会削弱司法程序的复杂性、事实调查和法律编码的动态性。它们将司法交付简化为数据或元数据之间的统计联系,切断了作为法律决策核心的情感认知过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence and real decisions: predictive systems and generative AI vs. emotive-cognitive legal deliberations.

The use of artificial intelligence in law represents one of the biggest challenges across different legal systems. Supporters of predictive systems believe that decisionmaking could be more efficient, consistent and predictable by using AI. European legislation and legal scholars, however, identify areas where AI developments are at high risk or too dangerous to be used in judicial proceedings. In this article, we contribute to this debate by problematizing predictive systems based on previous judgments and the growing use of Generative AI in judicial proceedings. Through illustrations from real criminal cases in Italian courts and prosecution offices, we show misalignments between the functions of AI systems and the essential features of legal decision-making and identify possible legitimate usages. We argue that current predictive systems and Generative AI crunch the complexity of judicial proceedings, the dynamics of fact-finding and legal encoding. They reduce the delivery of justice to statistical connections between data or metadata, cutting off the emotive-cognitive process that lies at the core of legal decision-making.

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来源期刊
Frontiers in Sociology
Frontiers in Sociology Social Sciences-Social Sciences (all)
CiteScore
3.40
自引率
4.00%
发文量
198
审稿时长
14 weeks
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