  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 guardrails. 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.
