The optimization process adjusts the weights of a computational graph until the numeric outputs align with some baseline statistics of a large data set. There is no "punishment" or "reward", gradient descent isn't even necessary as there are methods for modifying the weights in other ways and the optimization still converges to a desired distribution which people claim is "intelligent".

The converse is that people are "just" statistical distributions of the signals produced by them but I don't know if there are people who claim they are nothing more than statistical distributions.

I think people are confused because they do not really understand how software and computers work. I'd say they should learn some computability theory to gain some clarity but I doubt they'd listen.