I wish that Dr. Dick was (if this be the case) not afraid of "losing" arguments; or of being found to have made a mistake; or of being found to have used a very complicated process to describe something actually much simpler!
I wish Dr. Dick would not evade or sidestep issues and challenges.
I wish Dr. Dick would not pre-judge so hastily, but allow argument to play out.
I wish Dr. Dick would define: "knowable"; "unknowable"; "explanation"; "senses"; "light"; "definition"; "Dirac function"; "data"; "add"; "subtract"; "number"; "set"; for example.
Note this: Dr. Dick wrote:
"I realised that our senses must be part of the explanation and should not be thought of as part of what the model is trying to explain".
This is very non-rigorous! I wonder what he means?
Let me see: how about imagine a coding machine in an environment?
"Data" is the environment that surrounds the coding machine. Generally: infinity minus the coding machine = data.
"Senses" is the coding procedure used by the coding machine.
"Explanation" is a a way of linking the sense-coded data in a non-contradictory way.
Well obviously the "senses" of the machine, being its initial coding of environmental inputs, are part of its overall attempt at linking up those inputs into a logical model of its environment.
However, it is a non-sequitur for Dr. Dick to claim "cannot attribute to reality anything which could be attributed to our senses" and that "any symmetry we find in the data submitted to us by our senses must be attributed to our senses and not reality".
Consider a coding machine has two steps: (1) juggling, coding, linking data from the environment (the job of its "senses") and (2) juggling, coding, linking this now pre-coded data into a logical model.
However, although symmetry found in this twice coded data MAY be a consequence of the coding process by the machine's senses; it is also possible that the machine's senses left UNDISTURBED some symmetries that were in the data in the environment itself.
It would be as wrong to insist that "any symmetry we find in the data submitted MUST be attributed to the senses (initial coding), as it would be to insist that those symmetries MUST be attributed to data-symmetries that survived the coding process intact.
Actually, SOME symmetries MUST survive the coding process intact, as "symmetry" according to www.emmynoether.com means "invariance of an object or system to a set of changes (transformations)". The process of CODING itself is a constant (invariant) between the environmental data and the coded (sensed) explained (linked together some way) model of that environment.
So we have three systems here, three networks or structures or "explanations":
(1) the patterns of data in the environment
(2) the patterns of coding in the sensing-system
(3) the patterns of coding in the linking up of (2)'s patterns as a logical network, that is as a proposed model or explanation of (1)
The apparant solid nature of your desk MAY be an artifact of the equipment you use to test your desk (e.g. your hand), but is NOT NECESSARILY so.
The apparant NON-solid nature of your desk MAY be an artifact of the equipment you use to test your desk (a neutrino beam), but is NOT NECESSARILY so.
In fact, the so-called nature (solid or non-solid) of your desk is derived from how you define "solid" and "not solid".
It's up to you to choose which patterns to connect with your desk's patterns to produce the definition "solid".
You may choose to not include the pattern "test with a neutrino beam" in your making up your definition of "solid" as regards your desk.
What does Dr. Dick mean by "scale invariance"?
Note this: when you DEFINE something, you bring together different things and say that when these things are combined in a certain way, there is your newly defined thing (e.g. bring together various tests and define "solid").
In a definition, the scale doesn't matter; no matter that a neutrino is tiny and a desk is big.
The MATCH of different patterns that occurs in a DEFINITION is a MATCH.
Take match A and B to form an "AB". No matter which direction you look at an "AB", it is, from an "AB" point of view, always an "AB". So rotational symmetry derives from the very act of conserving a definition.
No matter where you take the "AB", it is still an "AB" from an "AB" perspective; so translational symmetry derives from the very act of definition.
Imagine: you are handed a foreign language dictionary with all the meanings of the words explained in that foreign language. You don't know what any of it means. You learn everything in the dictionary. Now you at least know that some of these words appear only with others, and at various frequencies. How much could you understand an essay in that foreign language?
With say English dictionaries, you have a foundation for understanding "meaning" obtaining from outside the circularity of a dictionary. This comes from experience of the context of words used in the real world, from pictures of what the words denote, etc.
But just as "meanings" in the circularity of the dictionary involve matching patterns; foundations for those meanings taken from experience of seeing say a word next to a picture, also involve the matching of patterns.
So the circularity of the dictionary is replaced by the circularity of pattern-matching in real life? So does that mean that the "meaning" of anything in real-life is no better than the case of the person who learnt a whole foreign dictionary but knew only the frequencies and contexts and inclusivities and exclusivities of words?
Does that mean that nobody really has the foggiest notion of what anybody else is talking about; but only think they do?
Something does not seem right here. It seems like that in real life the trial-and-error process regarding making the correct matches of patterns within the margin of error, is very quickly very accurate. There seems to be a large overlap where guessing happens to be correct guessing.
One might construct a model that shows the minimum tautological structural framework of coding-options for connecting any two bundles of data in a closed circular dictionary.
As the basic operation is pattern matching; that gives you a 2-D (as minimum is to compare two patterns) perspective of a 3-D object (2 patterns + comparison). Example: a 2-D view (neutino-beam-test is 1, your desk is 2) of a 3-D object (the 3rd-D is the definition you make on bringing together the neutrino beam and your desk to define whatever you want to say about that interaction).