Not entirely sure but here is an hunch , a single memory is really hard to remove, and presuming they're not training it again. Here are some solutions 1) Bloc

Not entirely sure but here is an hunch , a single memory is really hard to remove, and presuming they're not training it again. Here are some solutions 1) Block Personally Identifiable info to get into training data : Maybe have a redact such info before passing it to model . Just having a layer between I/O and the processing . 2) Have a sort of VCS for models and rewind and retrain if such is needed to be done . ( Seems quite unfeasible ) 3) If it is not an info but rather an opinion , train the model to counter biases until a netural or agreed stance is reached