At least with an AI-based system, it's presumably consistent across performances & devices and can be used during training. While not "objective" per se, it's certainly better than an human judge that is none of these things.
LOL! I think the assumption that an ML system would be robust across these contexts is not well founded. Things as innocuous as the lighting, background, or placement of athletic tape could easily wreck a model like this.
The thing about human judges is that the modes of failure are pretty well known at this point; and human perception and visual processing is pretty robust to perturbation.
One that many people who would admit the possibility in a human judge will likely insist cannot be present.