Note: your first part skipped entirely the process of obtaining the data for and training of both of the above, which is a crucial part at least on par with what called which API.
I don’t think it’s unreasonable to expect people to build an intuition for it, though. It’s healthy when underlying processes are understood to at least a few layers of abstraction, especially in potentially problematic or morally grey areas.
As an analogy to your example, you could say that when people drink milk they usually don’t think “oh, so this cow was forced to reproduce 123 times with all her children taken away and murdered so that it makes more milk” and simply think “the cow gave this milk”.
However, like with milk, like with the ML tech, it is important to realize that 1) people do indeed learn the former and build the relevant intuitions, and 2) the industry is reliant on information asymmetry and mass ignorance of these matters (and we all know that information asymmetry is the #1 enemy of free market working as designed).