I hear this argument a lot and I think that it's fallacious. Let's go ahead and extend it to another AI tool - in this case let's talk about stable diffusion.
Let's say you teach a class on fine Art and painting, if you allow your students to use stable diffusion for all their drawings, would you make the case that they have learned how to paint?
Likewise you can't really make the case that somebody understands how to do recursion, if all they're capable of doing is typing the following prompt into chat GPT, "change my forloop into a recursive method".
And in my experience going through calculus, the usage of graphing calculators was heavily. We still had to understand how to calculate derivatives and integrals by hand.
> would you make the case that they have learned how to paint
Well, you’re assuming that “painting” is the physical act of moving a brush on canvas.
But that’s already not true. Plenty of people graduate art school with degrees, despite doing everything on a computer. Are they “painters”? Well, no, but they are artists.
And if you’re talking about a program for artists, where the work is judged on artistic merit (composition, concept, etc), I don’t think it matters what mediums are used.
But if we’re narrowly focused on something more like sign painting, where what matters is brush technique and conforming to customer expectations, sure, AI will reduce the need for such people and will allow those who exist to “cheat”. But who cares?
Let's say you teach a class on fine Art and painting, if you allow your students to use stable diffusion for all their drawings, would you make the case that they have learned how to paint?
Likewise you can't really make the case that somebody understands how to do recursion, if all they're capable of doing is typing the following prompt into chat GPT, "change my forloop into a recursive method".
And in my experience going through calculus, the usage of graphing calculators was heavily. We still had to understand how to calculate derivatives and integrals by hand.