I don't disagree with any of that, but I still think a responsible, clear-thinking ML practitioner can avoid having to assume the form of the data-generating process, depending on their application.
In some cases if you care about PAC generalization bounds, it's even the case that the bounds do actually hold for all possible distributions.
