Assuming consciousness comes directly from an event at dendrites, some acoustic properties of the cytoskeleton or something, is this just totally incidental or does this actually matter for humans to do things, aka is it an evolutional adaptation or a coincidence. AI has none of this structure - just transistors - so can't be conscious in this model, but appears to functionally be able to do everything that a human would need to do, so the consciousness can't be that important.
As usual, let's follow Gottfried. He assumes that action and perception are two sides of the same coin in every event in the universe. To happen is both to receive information and to put out information. Receiving information is perception. Putting out information is action (you can cut this at different joints but this is what it boils down to). But human consciousness is not merely perception. It is apperception, implying that it includes concepts that relate to
events elsewhere in time or space including a narrative of 'self events' very often but that is not critical.
An electron mode in a semiconductor in this model will have a rich experience of the complex coulomb field provided by the metal nuclei. We can have no idea how this might 'seem' to the mode or what it might 'mean' to it, but it will not have a referent meaning about dogs barking in the passageway.
The evolutionary value of our experiences is not that they are unique or richer than others but that the natural richness of field events has been harnessed to a network of rather computer-like units that feed intricate representations of
distant events into dendritic trees. The experience can mean that hyenas are shuffling in the trees. In the semiconductor the field pattern, however rich, is only ever of two types, one for on and one for off. The pattern itself does not affect the computing.
I can only speculate but I have a strong hunch that this is also why humans can do certain things, and in particular generate new connecting ideas, better than computers. In a computer gate the answer follows simple qualitative rules. You can describe it in terms of numbers but these numbers
do not in any sense indicate quantities. The 1s are not the same size, nor bigger than 0s. They are just two qualitative alternatives.
In real physical interactions quantities matter. We live in a real quantitative spacetime world. Neurons integrate signals within a real quantitative spacetime structure and quantity matters. Most obviously, when signals are sent to a bank of neurons the one that fires quickest inhibits all the others. Neurons compute the
best answer, not the right answer.
I have a suspicion that acoustics fits this well because when acoustic modes fit their filed context well you have resonance. Blow across a flute moutpiece and you get white noise. Blow with the skill of James Galway and press the keys for E flat and you will get a pure E flat tone. Moreover, over the centuries musciains have found that unusual combinations of fingers on keys produce unexpected notes because resonance is not just a matter of tube length. Half open holes a little bit along can transform the 'best' answer. Oscar Peterson discovered that new combinations of ten notes at once on the piano produced music of a sort nobody had ever dreamt of before.
I use to think that the secret of human computation was that it used geometry rather than algebra to model a world that used geometry rather than algebra and that this required interactions across more than one dimension. However, dendrites are essentially one dimensional, so that argument seems weak. I now think that it is simply quantity that is the difference (in a way the true root of geometry I guess).
And to get back to Gottfried. Early in his career he tried to develop a way of cataloguing all ideas on the basis that all ideas could be assigned a ratio of two numbers. It sounds crazy but it is actually the essence of set theory, which has work on logic made possible. He wanted it to be more than that and for quantity to be relevant, so that it mattered that 3x7=21 (which assumes that every 1 is the same amount). If you think about it the implication of the model I favour is that all our ideas are based on ratios and their resonance dispositions - extraordinarily complicated ratios but just quantity ratios. A compute can write out those ratios but never discover that there is a
better answer to what fits than the answers it is programmed to look for because it never actually checks the fitting quantitatively anywhere. If you programme it with math that predicts unusual resonances maybe it will be as good as us but it will use up all the water in Loch Lomond to do the computation.