I'd be inclined to agree with this, but whenever a high profile leak of source code happens, reading that code can have dire consequences for reverse engineers. It turns clean room reverse engineering into something derivative, as if the code that was read had the ability to infected whatever the programmer wrote later.
A situation involving the above developed in the ReactOS project https://en.wikipedia.org/wiki/ReactOS#Internal_audit
Someone's going to have to audit the model the training and the data that does it. There's a documentary on black holes on Netflix that did something similar (no idea if it was AI) but each team wrote code to interpret the data independently and without collaboration or hints or information leakage, and they were all within a certain accuracy of one-another for interpreting the raw data at the end of it.
So, as an example, if I can't train something in parallel and get similar results to an already trained model, we know something is up and there is missing or altered data (at least I think that's how it works).
I hope you're actually reading those LICENSE files before using open source code in your projects.
It's perfectly fine for me to develop programming skills by reading any code regardless of the license. When a corp snatches an employee from competitors, they get to keep their skills even if they signed an NDA and can't talk about what they worked on. On the other hand there's the no-compete agreement, where you can't. Good luck making a no-compete agreement with a neural network.
Even if someone feeds stolen or illegal data as an input dataset to gain advantage in ML, how do we even prove it if we're only given the trained model and it generalizes well?