Data Deletion

Data deletion, or "machine unlearning," focuses on efficiently removing a user's data from trained machine learning models, addressing legal requirements like the right to be forgotten. Current research emphasizes developing algorithms for various model architectures, including gradient boosting decision trees and generative models, that minimize performance degradation after data removal while ensuring privacy. This field is crucial for responsible AI development, balancing individual data rights with the need for effective machine learning, and is actively exploring the interplay between data deletion and other crucial aspects like model explainability and fairness.