False functional inference:what does it mean to understand the brain?A few days ago Eric Jonas andKonrad Kording [pictured here] (J&K) posted a thought-provoking paper on bioRxiv entitled “Could a neuroscientist understand a microprocessor?” It’s been circling round my head for most of the weekend, and prompted some soul searching about what we’re trying to achieve in cognitive neuroscience.
The paper reports on a mischievous set of experiments in which J&K took a simulation of the MOS 6502 microchip (which ran the Apple I computer, and which has been the subject of some fascinating digital archaeology by the http://www.visual6502.org/team), and then analysed the link between it’s function and behaviour much as we might do for the brain in cognitive and systems neuroscience. The chip’s “behaviour” was its ability to boot and run three different sets of instructions for different games:
so what did they discover?
By treating the chip like a mini-brain, albeit one in which the ground truth was fully known, J&K could apply some canonical analysis techniques and see what they revealed. The bottom line is that for most of these analyses, they were either downright misleading or ended up producing trivial results…
and IR links to a similar article on why the brain doesn't function like a computer.
the idea that humans must be information processors just because computers are information processors is just plain silly, and when, some day, the IP metaphor is finally abandoned, it will almost certainly be seen that way by historians, just as we now view the hydraulic and mechanical metaphors to be silly.
If the IP metaphor is so silly, why is it so sticky? What is stopping us from brushing it aside, just as we might brush aside a branch that was blocking our path? Is there a way to understand human intelligence without leaning on a flimsy intellectual crutch? And what price have we paid for leaning so heavily on this particular crutch for so long? The IP metaphor, after all, has been guiding the writing and thinking of a large number of researchers in multiple fields for decades. At what cost?
Kurzweil is wrong?
I'll have to read this later and think about it.