The Right to be Forgotten (RTBF) was first established as the result of the ruling of Google Spain SL, Google Inc. v AEPD, Mario Costeja Gonz\'alez, and was later included as the Right to Erasure under the General Data Protection Regulation (GDPR) of European Union to allow individuals the right to request personal data be deleted by organizations. Specifically for search engines, individuals can send requests to organizations to exclude their information from the query results. It was a significant emergent right as the result of the evolution of technology. With the recent development of Large Language Models (LLMs) and their use in chatbots, LLM-enabled software systems have become popular. But they are not excluded from the RTBF. Compared with the indexing approach used by search engines, LLMs store, and process information in a completely different way. This poses new challenges for compliance with the RTBF. In this paper, we explore these challenges and provide our insights on how to implement technical solutions for the RTBF, including the use of differential privacy, machine unlearning, model editing, and prompt engineering. With the rapid advancement of AI and the increasing need of regulating this powerful technology, learning from the case of RTBF can provide valuable lessons for technical practitioners, legal experts, organizations, and authorities.

翻译：被遗忘权（RTBF）最初源于谷歌西班牙公司、谷歌公司诉西班牙数据保护局及马里奥·科斯特哈·冈萨雷斯案的裁决，随后被纳入欧盟《通用数据保护条例》（GDPR）中作为删除权，允许个人要求组织删除其个人数据。具体而言，在搜索引擎场景下，个人可向组织提出申请，要求将其信息排除在查询结果之外。这一权利是技术进化催生的重要新兴权利。随着近期大语言模型（LLM）的发展及其在聊天机器人中的应用，基于LLM的软件系统已日趋普及，但并未被排除在RTBF适用范围之外。相较于搜索引擎采用的索引方式，LLM以完全不同的方式存储和处理信息，这为遵守RTBF带来了新的挑战。本文探讨了这些挑战，并就如何实施RTBF技术解决方案提出见解，包括使用差分隐私、机器遗忘、模型编辑及提示工程等方案。随着人工智能的快速发展及对此强大技术监管需求的日益增加，借鉴RTBF案例可为技术从业者、法律专家、组织及监管机构提供宝贵经验。