I mean sure, maybe humans aren't "just" doing sophisticated pattern matching, but there are good reasons to suspect this is some part of what we are doing. (Even if its not implemented with back-prop).
e.g) consider the work of people like Anil Seth, who propose that our brain is basically a generative model of the world, which aims to minimize the likelihood of perceptual data. (see also: Karl Friston's free energy principle). What's up for debate is how it is structured, what priors are built in, what is the learning algorithm etc.
Anyway, for all their limitations, it seems clear that current artificial generative models can: 1. learn hierarchies of abstractions, which 2. explain the observed data in the fewest possible number of bits, and 3. generate new, novel data based on the patterns that have been learned
If you want to describe this as "just sophisticated pattern matching".. then sure I guess? But I think there's a clear qualitative difference between this and searching for code in a discrete database (which imo would not be okay).