Machine unlearning is the process of modifying a trained model to reduce or remove the influence of specific data from its behavior. It is relevant to privacy, data deletion rights, and governance, although scalable and verifiable unlearning remains difficult for large generative models.
Adjusting a model's parameters to remove the influence of specific data, though current techniques are not scalable for large AI models like generative AI.