That's the natural intuition yes. But I believe Sutton's point is that this very intuition seems to prove itself wrong in the long term.
The way I see it, the problem with the high level is that we don't actually know shit. If we knew so completely what it took to model language or vision in the first place, we wouldn't need deep learning at all.
It seems intuitive that trying to bake in some basic grammar rules might speed things up along.
Problem with that is that we often end up overfitting the models to those specific rules and constraints, limiting its ability to generalize and learn more complex and underlying patterns and structures in language. Patterns that we don't actually know of.
The low level processes result in the high level performance but not vice versa.
It's said that the one human neuron is equivalent to a CNN. I wouldn't really call the operations of neurons high level though.
