Brain Surgery: Ensuring GDPR Compliance in Large Language Models via Concept Erasure
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 7 references that are in the map. First posted on arXiv 22 Sep 2024.
Builds on
5 of 7 references.
References · 5
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
- 2022Locating and Editing Factual Associations in GPTcited by 2,609
- 2021Editing Factual Knowledge in Language Modelscited by 548
- 2021Fast Model Editing at Scalecited by 491
- 2023Unveiling the Pitfalls of Knowledge Editing for Large Language Modelscited by 43
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