I think this analogy doesn't hold water - horses aren't exactly a beacon of reliability (having owned one).
I've already seen tools that support workflows where you compose art by iteratively generating a piece of it, performing some correction, and repeating. So, I think there's room in the art world for less than perfectly generated art. That said, let's not kid ourselves that the typical failure modality of ML today (99% correct enough, 1% disastrously incorrect) doesn't either cause it to be entirely useless in many applications or end up wreaking havoc on end users in others.
It's only an analogy, but it serves to underscore the last point you make. Initial versions of the technology can make some genuine horrors but you're blinding yourself to progress if you can't see the potential in it.
