You're dancing around the fundamental point: Can abstraction layers be 
closures?  And that's the essence of complexity theory, the study of what and 
how some thing is reducible to the inner layers (or what and how expands to the 
outer layers).  Can you really understand Go just by knowing the rules?  Or can 
you understand it without knowing the rules, just knowing possible 
configurations?  The bias in Western culture seems to lie in the forward map.  
We tend to have a deep desire to build everything from 1st principles, axioms.  
(And even when we're fundamentally ignorant, we pretend at understanding the 
principles.)  It's not enough to be an artisan.  You have to be a scientist.

So, your qualifier, without regard to coherence or extension, is 
over-simplification.  What's actually happening is specialization, 
niche-filling ... the same thing that's been happening the whole time.  And it 
is definitely _not_ without regard.  It may be systemic or evolutionary (so 
that no single mind understands what's happening).  But to assert that there is 
no order or pattern to specialization seems wrong (at least too strong).


On 05/09/2016 03:37 PM, Marcus Daniels wrote:
One can learn to program in, say, Python without understanding a given machine 
instruction set.    One can even learn a subset, and have a correct understanding of some 
of its syntax and semantics and little or no understanding of other parts.   That doesn't 
mean that learning the rest is pointless, or that learning a machine language couldn't 
give a Python programmer deeper and useful insight into why some constructs are slow and 
others are fast.   Or that learning about digital circuit design couldn't give insight 
into what makes a machine instruction set energy efficient.  Or that learning quantum 
mechanics couldn't give some insight into what makes circuits work the way they do.   All 
these tools can be useful and the connections between them are some of the most 
interesting and useful things to know.   This trend toward "industry relevant" 
knowledge is just to say the graph should be chopped up into consumable sound bites 
without regard to their coherence or utility for learnin
g other things.

--
⛧ glen

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