Training data, weights and model

I think that for most people, 3a (the model state) is the "preferred form of modification" anyway. Having all the training data is a nice idea, but useless in practice because you can't meaningfully review all the data anyway. And just retraining with the same data doesn't give you anything new. Just about anything you might want to do you can do with just the weights: fine tuning for the results you want.

The case for training on private datasets (like medical data) is a different issue. Obviously you can only train an AI to detect lung cancer if you have access to datasets with information about people who may have lung cancer. Ideally you'd like such datasets to be available on a Reasonable and Non-Discriminatory basis. This sort of access is already available for other purposes, I don't see how AI requires anything new here.

(Sometimes I wonder if in the future we'll have AI psychologists that specialise in diagnosing issues in AIs and recommend treatments i.e. new fine-tuning to reduce issues. Maybe the AI psychologist will also have an AI to help them.)