While I technically agree, I can't help but ask: What if it's not true? How would we go 
about demonstrating that it's not true? What if animals actually "relax into" 
their envinronments in a computationally universal way? I.e. although it seems like we 
learn by analogy, maybe we're actually universal algorithms that are *fitted* to reality?

As "models" of reality, then, we would be over-fitted to past (or elsewhere) 
contexts and ill-fitted to new contexts. The steepness of the learning curve would 
explain well enough the registration error McGilchrist describes as model choice error. 
So the mere ill-fittedness wouldn't be enough to test the hypothesis. We'd need something 
more, perhaps a *type* of ill-fitedness? What type of ill-fittedness comes from bad 
analogies versus the types that result from over-fitting to prior (or other) contexts?

Of course, the hypothetical dichotomy (between analogical fallacy versus in-context 
training) is probably a false one. We most likely do *some* analogical learning and some 
in-context learning. But using the (false) dichotomy to test conditions/contexts will 
help us anyway, in categorizing which situations exhibit analogical learning versus 
in-context learning. And, of course, someone convicted by their confidence in 
"metaphors everywhere" will claim that in-context learning reduces to 
analogical learning. Maybe. But mere assertion is sophomoric. How can we test the 
assertion? That's where the work (and credibility) lives.

It's just a bit galling to assert one's stance without also providing a way to think 
clearly about the assertion and methods to falsify/test it. So the kids get it right, yet 
again, by asking "Is it, though?"

On 4/30/22 16:43, Prof David West wrote:
 From Iain McGilchrist, /The Matter of Things, vol I, Our Brains, Our 
Delusions, and the Unmaking of the World/. (Top 5 most important books I have 
read.)

"Explanation, science's forte, is a subset — an explicit, rigorous, disciplined 
subset, but still a subset — of understanding. All understanding depends on 
metaphor. What we mean when we say we understand something is that we see it is like 
something else of which we are already prepared to say 'I understand that'. That, in 
turn, we will have understood because we have likened it to something else we had 
previously understood, and so on. It's metaphors all the way down.

In science this inescapable role of metaphor is manifest in the model the 
science uses in order to seek an explanation of the phenomenon it is 
investigating. Models are simply extended metaphors. The choice of model is 
crucial here because the problem for seekers after truth is that that choice 
governs what we find. We find more or less according to what we put there. 
Since a model always highlights those aspects of what it is modelling that fit 
the model, any model soon begins to seem like an uncannily good fit, which 
means we espouse it with still greater confidence.

Even the sense data that go into selecting the model are not innocent. Perceptions 
are laden with theory. We never just see something without seeing it *as* a 
something. We may think that our theories are shaped by observations, but it is as 
true that our observations are shaped by theories. This means we can be blind to 
some very obvious things in our immediate environment. We don't look where we don't 
expect to see so that our expecations come to govern what we *can see*. This is why 
the model is crucial. In the past such a model was often something in the natural 
world — a tree, a river, a family. Nowadays, unless otherwise specified, it is the 
machine."

Quotation of Evelyn Underhill:

"It is notorious that the operations of the average human consciousness unite the 
self, not with things that really are, but with images, notions, and aspects of things. 
The verb 'to be', which he uses so lightly, does not truly apply to any of the objects 
amongst which the practical man supposes himself to dwell. For him, t/he hare of Reality 
is always ready-jugged/: he conceives not the living, lovely, wild, swift-moving creature 
which has been sacrificed in order that he may be fed on the deplorable dish which he 
calls 'things as they really are'."

Quotation from /The Function of Reason/, by Alfred North Whitehead:

"The man with a method good for purposes of his dominant interests is a pathological 
case in respect to his wider judgement on the coordination of this method with a more 
complete experience. Priests, scientists, statesmen and men of business, philosophers and 
mathematicians, are all alike in this respect. We all start by being empiricists. But our 
empircism is confined within our immediate interests. The more clearly we grasp the 
intellectual analysis of a way [of?] regulating procedure for the sake of those 
interests, the more decidedly we reject the inclusion of evidence which refuses to be 
immediately harmonized with the method before us. /Some of the major disasters of mankind 
have been produced by the narrowness of men with a good methodology./"

BTW— jugged hare is an English country dish: hare marinated in red wine and 
juniper berries, then slow cooked with some of the hare's blood. AKA /civet de 
lievre/.

I find McGilchrist's books exhilarating—2,000 plus pages of rich empirical 
evidence and densely reasoned argument that supports almost all of the essays, 
books, and ideas I have been espousing for 25 years. Including, a path for 
incorporation of all the hallucinogenic experiences.

davew


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