在犯罪风险评估中的人类专家和人工智能模型:使用HCR-20V3进行比较试点研究
1Department of Law, The Academic College of Law and Science, Yezreel Valley, Israel.
Behavioral sciences & the law
|November 12, 2025
概括
这项研究比较了犯罪者风险评估中的人类专家和AI (大型语言模型). 人工智能显示出更高的可靠性和风险得分,而人类更关注康复潜力.
科学领域:
- 法医心理学 法医心理学
- 人工智能的人工智能
- 临床风险评估临床风险评估
背景情况:
- 犯罪者风险评估对于公共安全和指导干预至关重要.
- 传统方法依赖于人类的临床判断,这可能是主观的.
- 大型语言模型 (LLM) 为客观,数据驱动的分析提供了潜力.
研究的目的:
- 为了比较基于LLM的风险评估与人类专家评估的准确性和可靠性.
- 使用HCR-20V3框架识别人工智能和人类评估者之间的推理模式的差异.
主要方法:
- 一项试点研究使用合成法医病例片段.
- 评估由人类专家和高级法学士进行.
- 应用了HCR-20V3风险评估框架.
主要成果:
- 人工智能模型的整体风险分数比人类专家更高.
- 与人类评估者相比,LLM表现出优越的评估者之间的可靠性.
- 人工智能专注于静态因素,而人类则强调动态的,康复的方面.
结论:
- 将人工智能与人类专业知识相结合,可以提高风险评估的一致性和透明度.
- 人工智能的优势在于模式识别和可靠性;人类判断提供了上下文和道德见解.
- 将人工智能驱动的数据与临床专业知识相平衡,是有效的法医决策的关键.
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