This doesn't feel like a convincing argument. If you wanted to multiply uint8 * uint8, you'd naturally use an unsigned multiply with a uint16 result. That doesn't overflow either.

I believe a better argument is to appeal to the structure of neural networks. Activation inputs into a matrix multiply come out of a non-linear function, and ReLU is a popular function which causes activation inputs to be unsigned. Weights then need to be signed so that the matrix multiplication can have negative outputs -- without negative outputs, you would lose the non-linearity of ReLU.