My worry is when this gets used for something forensic.
I imagine this will tend to reproduce things in the dataset, e.g. up-scaling blurry text may look like fonts that it has memorized more than the original. Or upscaling a feather will provide details like the feather of more common birds. Or upscaling blured out numbers will pick some numbers at random [1].
We need to make sure people don't rely on these details, e.g. in courts, HR reviews, when reddit sleuths try and investigate an incident, when someone looks for cheating partners etc.
I imagine this will tend to reproduce things in the dataset, e.g. up-scaling blurry text may look like fonts that it has memorized more than the original. Or upscaling a feather will provide details like the feather of more common birds. Or upscaling blured out numbers will pick some numbers at random [1].
We need to make sure people don't rely on these details, e.g. in courts, HR reviews, when reddit sleuths try and investigate an incident, when someone looks for cheating partners etc.
[1] https://www.theregister.com/2013/08/06/xerox_copier_flaw_mea...