人工智能从法律文件中提取关键见解,以预测亲密伴侣的女性杀戮
Esperanza Garcia-Vergara1, Nerea Almeda2, Francisco Fernández-Navarro3
1Department of Quantitative Methods, Universidad Loyola Andalucía, Sevilla, Spain. egvergara@uloyola.es.
Scientific reports
|October 24, 2023
概括
人工智能 (AI) 可以分析法律文件,预测亲密伴侣杀害女性 (IPF). 犯罪史和暴力特征等关键细节使致命和非致命病例的检测准确度超过75%.
科学领域:
- 计算机犯罪学 计算机犯罪学
- 法律信息学 法律信息学
- 人工智能在执法部门中的应用
背景情况:
- 法律文件包含有关犯罪行为和法律程序的丰富信息.
- 现有的研究还没有利用人工智能 (AI) 来分析法律文件以了解或预测犯罪.
- 亲密伴侣杀害女性 (IPF) 是一个关键领域,预测性见解可以增强预防策略.
研究的目的:
- 通过将AI应用于犯罪预测的法律文件来弥合研究差距.
- 在法律文件中识别相关的特定信息,以预测亲密伴侣杀害女性 (IPF).
- 探索人工智能驱动的法律文本分析对更广泛的犯罪预测应用的潜力.
主要方法:
- 从Vlex数据库中提取与男性对女性亲密伴侣暴力有关的491份法律文件.
- 使用各种AI算法分析文档信息:贝叶斯式,基于函数的,基于实例的,基于树的和基于规则的分类器.
- 专注于识别预测特征,如过去的犯罪行为,制裁,暴力特征和情境背景.
主要成果:
- 人工智能分析成功地确定了法律文件中的关键信息,用于犯罪预测.
- 包括犯罪史,制裁,暴力严重程度/频率和情境背景在内的特定数据点使致命和非致命IPF病例的准确检测率超过75%.
- 这项研究证实了法律文件作为人工智能驱动犯罪预测数据源的实用性.
结论:
- 人工智能可以有效地利用法律文件中的信息来预测亲密伴侣杀害女性 (IPF).
- 这种方法为识别高风险IPF病例提供了一种新的方法,有助于预防犯罪.
- 法律文件的AI驱动分析显示了在各种犯罪类型中应用的潜力,增强了法律信息学和法医科学.
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