The tags could be added by a model rather than the user submitting the image. Maybe do both and verify the tags with a model? Users could get a rating based on how reliably they tag their pictures and are trusted to add more niche tags at higher ratings. You could even help tag other pictures to improve your rating.
If I include the tag "floor", do I get some (tiny) percentage of every image that uses "floor" in the prompt, even if the bits from my image did not end up affecting model weights much at all in training?
Worse, for tags like "dramatic lighting", it's likely that the important source images will depend on the other words in the prompt; "sunset, dramatic lighting" will probably not use the rely on the same weights or source images as "theater interior, dramatic lighting".
And then you get the perverse incentives to tag every image with every possible tag :)
I'd love to be convinced otherwise, but I'm not seeing prompt-to-tag association working.