RE: On naturalism and consciousness
August 26, 2014 at 6:58 pm
(This post was last modified: August 26, 2014 at 7:00 pm by bennyboy.)
(August 26, 2014 at 1:16 pm)Surgenator Wrote: There is no reason why different subsets would have similiar experiences unless the subsets are similiar. In your monism world view, what guarantee's similiar subsets?I don't think I understand what you're saying. There's a large idealistic universe, and it has minds in it. Basically, it's the same as the physical universe you imagine, except it doesn't reduce down to mechanical elements-- it reduces down only to concepts: mathematical concepts, for example.
Quote:Lets me you ask you this, where does the mind store its experiences in your world view?If it's a human mind, in the brain (at least as far as I can tell).
Quote:Great, you agree that neural networks can pass the Turning test in the future. So they are a viable candidate for the explanation of the mind from pure physicsal processes.The Turing test isn't a test of consciousness. It's a test of the ability of a machine to simulate the behaviors of a conscious person. To claim otherwise wouldn't be a conclusion based on observation, it would be an assumption-- one most people probably aren't willing to make.
Quote:We have subjective minds because everybodies experiences are slightly different. Using the ANN example, you should know that for the same training tasks the hidden nodes values would be different (if your neural network is complex enough) if the starting conditions are slightly different. Nevertheless, the end result would be very very similiar.That's a narrative, not a mechanical explanation.
Quote:That's like saying "The Father, the Son, the Holy Ghost, ta da." You've just put a bunch of words from your world view together. It neither confirms the validity of your model, nor explains how in your model, mind exists.Quote:... if you want a physical model to be a sufficient account of human experience, you must be able to explain why there is more than zero.Abiogenesis + evolution + biological neural networks, ta da.