用AI生成欧盟隐私法条款，人类把关确保准确
GDPR Auto-Formalization with AI Agents and Human Verification
- AI多代理协作生成法律场景、规则和事实
- 人类审核确保表述、逻辑和法律正确性
- 适合法律科技研究者与合规系统开发者
我们研究在人机协同验证框架下，利用大语言模型实现欧盟《通用数据保护条例》（GDPR）条款的自动形式化。采用角色分工的工作流，由基于LLM的AI组件在多智能体迭代反馈机制中生成法律情境、形式化规则和原子事实；同时配备独立的验证模块，由人类评审员评估其表征、逻辑与法律正确性。该方法构建了一个高质量的数据集，用于后续的GDPR自动形式化研究，并分析了成功与失败案例。结果表明，结构化验证与针对性人工监督对保障法律形式化的可靠性至关重要，尤其在涉及法律细节和上下文敏感推理时。
原文摘要 · Abstract (English)
We study the overall process of automatic formalization of GDPR provisions using large language models, within a human-in-the-loop verification framework. Rather than aiming for full autonomy, we adopt a role-specialized workflow in which LLM-based AI components, operating in a multi-agent setting with iterative feedback, generate legal scenarios, formal rules, and atomic facts. This is coupled with independent verification modules which include human reviewers' assessment of representational, logical, and legal correctness. Using this approach, we construct a high-quality dataset to be used for GDPR auto-formalization, and analyze both successful and problematic cases. Our results show that structured verification and targeted human oversight are essential for reliable legal formalization, especially in the presence of legal nuance and context-sensitive reasoning.
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