CC is rarely a good license to choose other than to make yourself feel good. It does a terrible job of dealing with the actual matters of importance to a license outside of photo sharing (and even there it's not a good choice, as many photographers have found because it explicitly grants rights to others that the photographer may not be able to to grant to them, leaving the photographer open to lawsuits as has happened).
In this case, imagine a student working on a class assignment. They use this data for purely academic purposes with no commercial intent in mind. After they train their system, they realize yow I could use this trained system and get rich. There was arguably no commercial use during the training. The use of the data was purely academic, like a person learning math or French. What you do after running the learning is a separate matter, just as using a CC licensed textbook to learn math doesn't prevent you from getting a job as a statistician.
Again, the tl;dr is instead of trying to divine how a court will deal with a poorly specified problem, it's much better to just not license your stuff using a CC license. There are almost always much better licenses to choose from.
I'm curious about what you (or anyone else) would recommend as better license choices for datasets that might be used in machine learning model training?
(With, I suppose, hints about what restrictions you might be wanting to grant or prohibit by particular license options?)
IANAL but my sense is that it will be a number of years before we really know what works with regards to this kind of licensing of DNN/ML training data sets. It's almost certainly going to be decided on the basis of what's called "case law", which really just means "a bunch of random judges who don't know anything about ML made decisions on a bunch of random lawsuits that probably were not good samples to pick and which were probably taken to court by pairs of parties with wildly different abilities to pay lawyers and now we are stuck with those decisions as precedent for future cases."
If that sounds like a crappy legal footing for the next 20 years of software development, yeah, it is. It's also why Mitch Kapor and a few others founded and funded the EFF to try to encourage better case law decisions around the early days of electronic privacy law. We definitely need an EFF like effort around ML/DNN/etc., but I'm not holding my breath.
I wish I had a better answer, I'm mostly hoping someone else here does.
In this case, imagine a student working on a class assignment. They use this data for purely academic purposes with no commercial intent in mind. After they train their system, they realize yow I could use this trained system and get rich. There was arguably no commercial use during the training. The use of the data was purely academic, like a person learning math or French. What you do after running the learning is a separate matter, just as using a CC licensed textbook to learn math doesn't prevent you from getting a job as a statistician.
Again, the tl;dr is instead of trying to divine how a court will deal with a poorly specified problem, it's much better to just not license your stuff using a CC license. There are almost always much better licenses to choose from.