Brain Surgery: Ensuring GDPR Compliance in Large Language Models via Concept Erasure
About
As large-scale AI systems proliferate, ensuring compliance with data privacy laws such as the General Data Protection Regulation (GDPR) has become critical. This paper introduces Brain Surgery, a transformative methodology for making every local AI model GDPR-ready by enabling real-time privacy management and targeted unlearning. Building on advanced techniques such as Embedding-Corrupted Prompts (ECO Prompts), blockchain-based privacy management, and privacy-aware continual learning, Brain Surgery provides a modular solution that can be deployed across various AI architectures. This tool not only ensures compliance with privacy regulations but also empowers users to define their own privacy limits, creating a new paradigm in AI ethics and governance.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| LLM Unlearning | RWKU | USR69.5 | 16 | |
| Machine Unlearning | MUSE | -- | 16 | |
| Machine Unlearning | WMDP | MIA0.034 | 8 | |
| Relearning Attack | RWKU | RAP36.4 | 8 | |
| Relearning Attack | WMDP | RAP40.2 | 8 | |
| Relearning Attack | MUSE | RAP41.5 | 8 | |
| Relearning Attack | WaterDrum | RAP38.1 | 8 | |
| Machine Unlearning | WaterDrum | USR65.2 | 8 |