I think all of those are great, but don't think that has much to do with AI tbh. How you get to the outcome, and the standards that it meets, should be all that matters
Just look at the diverse and haphazard way AI has been used in autonomous driving. I would argue it’s a misplacement of the “move fast and break things” (in some cases at least) that has no place in public-facing safety critical applications.
It brings up some difficult questions regarding adequacy of testing at the very least when the underpinnings are not very interpretable.
Using LLMs or other ML as components in systems themselves is a whole other thing, and I agree with you wholeheartedly.