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：被遗忘权首次确立于Google Spain SL、Google Inc.诉AEPD、Mario Costeja González案，后作为删除权被纳入欧盟《通用数据保护条例》，允许个人要求组织删除其个人数据。具体到搜索引擎，个人可向组织提出请求，要求将其信息从查询结果中排除。这项新兴权利是技术演进的重大成果。随着大型语言模型（LLMs）的最新发展及其在聊天机器人中的应用，基于LLM的软件系统已广泛普及，但此类系统并未被排除在被遗忘权的适用范围之外。与搜索引擎采用的索引技术不同，LLMs以完全不同的方式存储和处理信息，这对被遗忘权的合规性提出了全新挑战。本文深入探讨这些挑战，并就差分隐私、机器遗忘、模型编辑及提示工程等RTBF技术解决方案的实施路径提出见解。随着人工智能的飞速发展和监管这一强效技术的需求日益增长，从RTBF案例中汲取的经验可为技术从业者、法律专家、组织及监管机构提供宝贵启示。