As for actually using the model... personally I still find that unacceptable. Even if the risks are low, we have lots of works in the model, so the risk can still add up.
The idea you have in your head of training without regurgitation is likely not possible. The underlying technology treats the training set as gospel: the system is trained to regurgitate first, and generalization is a happy accident. Likewise, we can't look into a model to check and see what it's memorized, nor can we trace back an output to a particular training example. Which has ethical implications with the way that AI companies crawl the web to get training data; such models almost certainly hold someone's personal information and there's no way to get it out of there aside from curating your training set to begin with.