Hi John,

It seems like the way you think about intercellular interactions has great utility.  I’m working to fully understand all this.  But when you bring the word “qualia” into this discussion the way you do, to me, you make it obvious that you don’t understand what the word “qualia” means.  You do use the word, with an abstract definition.  But to most people, the word qualia is not a word about anything abstract, in the way that you use it.

To better understand qualia, let us engineer 3 different robots that can each pick a strawberry, experience harm, wounding and injury, and so on all equally functionally well.

Let’s start with an easily falsifiable working hypothesis that the name for the neurotransmitter glutamate, and all of our abstract mathematical knowledge of how glutamate behaves in a synapse, are abstract mathematical descriptions of the causal physical stuff that is physical glutamate we can directly experience as having a redness quality.  The same for the objective name glycine and subjective name greenness, being abstract names for the same physical thing.

The first robot will represent its knowledge of the strawberry with glutamate, that has a redness quality.  Knowledge of leaves will be represented with glycine, which is directly experienced as greenness.  This redness knowledge will enable this robot to distinguish and pick out the “ripe” ones from the green ones.

The second robot will be a qualia invert.  It will represent its knowledge of the strawberry with the glycine.  So, this robot’s knowledge of the strawberry will be qualitatively like #1 robot’s knowledge of the leaves.  Functionally, these robots will both pick strawberries, indistinguishably well.  Actually, one and two can be identical, on just wears red green inverting glasses.

Finally, robot #3.  Let’s engineer this robot’s knowledge to be abstracted away from any physical qualities.  It will use the number “1” to represent knowledge of red things, and “0” for knowledge of green things.  This robot has multiple diverse kinds of interpreting mechanisms, so any different set of physics can represent that “1”.  For example, when a disc is magnetized one way, a specific interpretation mechanism will be able to get the “1” from that magnetized disk.  A different set of hardware will similarly get the “1” from +5 volts.  In other words, because of the additional abstracting hardware, it doesn’t matter what physics is representing its abstract binary knowledge.  An additional interpretation mechanism is required to interpret the “1” as ripe, and “0” as not ripe.  Without these interpretation mechanisms, this robot can not know what to pick and what to avoid.  Like the previous 2 robots, you can’t tell the external functional difference between this one, either.  The first 2 robots represent knowledge of the strawberry directly on physical qualities, so they are more efficient, since they do not require the additional abstracting hardware this 3rd one requires.

John defines words like qualia and red only functionally, with terms like: “Harm”, “Wounding?” and “Injury”.  There is no qualitative meaning in any of these definitions.  All of the above 3 robots can experience “Harm”, “Wounding”, and “Injury” in qualitatively very different ways, to which John is qualitatively blind to.  That is what “qualia blindness” means.