I feel the same way, that researchers should stop trying to mimic the brain, but not because we don't understand the brain. While I think there are still several decades before we'll be able to have mind uploads, I also think a lot of people underestimate the quality of modern brain science. In any case, I have the same reason as Dijkstra for why I think mimicking the brain isn't that great an idea.
In http://www.cs.utexas.edu/~EWD/transcriptions/EWD10xx/EWD1036... (really a great read to branch all sorts of thoughts off of) Dijkstra said, "The effort of using machines to mimic the human mind has always struck me as rather silly: I'd rather use them to mimic something better."
It's probably a harder problem, creating smarter-than-human intelligence on a machine, but research isn't as constrained by laws and ethics (they don't have to bemoan not being able to experiment with living human brains). I wish more people were active in the area.
They are trying to find THE ONE ALGORITHM that solves all A.I. problems. The brain has an implementation of it, but it is in wetware, hard to extract. Deep learning makes some pretty good approximations of the visual areas, though.
You assume that human cognition has an algorithmic component. Maybe you are right, but we still have a pretty shaky understanding of how Neurons work, let alone how the brain works on a large scale. Who knows, lets investigate by trying possibilities but lets understand that we are still in a position of ignorance.
We have some probabilistic models of that successfully predict various future states of the brain from past states or stimuli. This is not the same as understanding it or even approximating it.
It's probably a harder problem, creating smarter-than-human intelligence on a machine, but research isn't as constrained by laws and ethics (they don't have to bemoan not being able to experiment with living human brains). I wish more people were active in the area.