Well I suppose that in some sense you are right. You can do deep learning without even knowing any math at all, by plugging together libraries and frameworks that other people wrote.
Also maybe you will say that "higher" math is by definition a curiosity and if it's practical then it's not "higher".
But if those aren't your arguments, then you can consider one example that the tensor 'differentiable programming' libraries used in deep learning use automatic differentiation and matrix calculus. Matrices are taught in high school, and calculus is taught in high school, but matrix calculus generally isn't as far as I know. Or at least not at my high school. https://en.wikipedia.org/wiki/Matrix_calculus
Also maybe you will say that "higher" math is by definition a curiosity and if it's practical then it's not "higher".
But if those aren't your arguments, then you can consider one example that the tensor 'differentiable programming' libraries used in deep learning use automatic differentiation and matrix calculus. Matrices are taught in high school, and calculus is taught in high school, but matrix calculus generally isn't as far as I know. Or at least not at my high school. https://en.wikipedia.org/wiki/Matrix_calculus