GDPR Auto-Formalization with AI Agents and Human Verification
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 t...
| Authors | Ha Thanh Nguyen, Wachara Fungwacharakorn, Sabine Wehnert et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 April 2026 |
| Last updated at source | 2 May 2026 |
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