It's not an absurd reduction, it follows from the definition of a universal turing machine. This is how completely non-empirical theoretical models of computation are: they are devices of pure mathematics.
This is exactly my point.
If you want to use the formal machinery of computer science to say something empirical, you cant just hijack terminology and speak in this pseudoscientific way, ie., "the brain as a computational process" (etc.).
What is the empirical content of such a claim?
There might be some if you defined what algorithm the brain was computing, and what the empirical correspondance between the algorithm and the brain way (etc. etc.) -- but no one is doing this.
We are speaking as-if somehow "universal turing machines" had some empirical content, that there's something insightful about labelling the brain this way (vs. anything at all). There isnt.
Sure, it's merely an idea that is believed, like the Greeks believed that the night stars were heros, or Galileo that Jupiter had satellites, or Newton that F=ma everywhere and that God had set up the solar system.
Some of these theories work, others don't. Nobody had a truly solid reason to believe them before it was clear they worked (in the case of those that did). Scientists all believe things they have no strict reason to -- when they're wrong they're wrong, and when they're right it's a scientific discovery.
Planck had no reason to postulate the energy packets when he came up with them. He described it as a move of pure desperation. The explanation (such as it is) for why this worked wasn't developed until decades later.
I don't personally believe Turing machines reveal much about the human brain, but you're verging on a more general claim about how science should be performed. That to hypothesize, work within a model, or even get something out of it you need to already have a precise description of the phenomenon being described and "why" the model might work. None of that is required though.
To be clear this all applies much less to "bread and butter" science. What we're faced with here is a process that has no convincing description.
To convince people to give up on computational models of the brain you need to convince them that it doesn't work. Nothing has been revealed by it in 60+ years. It's never predicted anything. Neurobiology and pharmacology at least have some results to show about a real brain. What you're basically engaging in instead is philosophy -- "pure" math is distinct from the empirical world, what if the whole universe, science requires this specific method, ... But it's better if we can dismiss a scientific idea on scientific grounds, rather than philosophical considerations.
This is exactly my point.
If you want to use the formal machinery of computer science to say something empirical, you cant just hijack terminology and speak in this pseudoscientific way, ie., "the brain as a computational process" (etc.).
What is the empirical content of such a claim?
There might be some if you defined what algorithm the brain was computing, and what the empirical correspondance between the algorithm and the brain way (etc. etc.) -- but no one is doing this.
We are speaking as-if somehow "universal turing machines" had some empirical content, that there's something insightful about labelling the brain this way (vs. anything at all). There isnt.