On 10/9/24 12:33 PM, glen wrote:
Hm. I don't normally read the GPT output posted to the list. But I did
this time and am worse off for it. Your original is way better.
Anyway, I'd like to continue responding to Stephen's originalism and
your tangent into compression at the same time.
Because wrong or wrong-headed, or is that a false dichotomy?
The idea that models are abstract is what I think Jon was targeting
with the bisimulation reference. There's no requirement that models be
less detailed than their referents. In fact, I'd argue that many
models have more details than their referent (ignoring von Neumann's
interpretation of Goedel for a minute). A mathematical model of, say,
a toy airplane in a wind tunnel (especially such a model implemented
in code - with the whole stack from programming language down to
transistors) feels more packed with detail than the actual toy
airplane in the wind tunnel. There's detail upon detail in that model.
Were we to take assembly theory seriously, I think the implemented
model is way more detailed (complicated) than the referent. What makes
the model useful isn't the compression, but the determinism ... the
rational/mental control over the mechanism. We have less control over
the toy airplane and the wind than we have over the tech stack in
which the model is implemented.
I'm not sure what it means in this context for the model to be more
detailed than the referent? The toy airplane in a wind tunnel is likely
less detailed (or differently detailed?) than a real airplane in a real
airflow but if the (computer?) model of such is *more detailed* then I
think this invokes your "excess meaning" or "excess detail?" dismissal?
if the computer model/simulation has more detail than the
toy-airplane/wind-tunnel model of the fully elaborated "real" airplane
in "real airflow" then does it have *more* than the latter? If so, not
only excess but also "wrong"? If more detailed than the toy/wind-tunnel
then simply closer to referent?
Here's where aphorisms and "models" writ large differ drastically.
Aphorisms are purposely designed to have Barnum-Forer (heuristic)
power. Models often have that (especially in video games, movies,
etc.) power.
I appreciate this distinction/acknowledgment.
But Good Faith modelers work against that. A Good Faith modeler will
pepper their models' uses with screaming large print IT'S JUST A MODEL.
I agree there is virtue in acknowledging the implications of "IT"S JUST
A MODEL!!!!"
Aphorisms (and all psuedo-profound bullshit) are not used that way.
And are all aphorisms by definition "pseudo-profound bullshit"? Or do
they still retain some profoundish-utility? do they in any way represent
a (finessed?) useful compression?
They are used in much the same way *inductive* models are used to
trick you into thinking the inference from your big data is
categorically credible.
I agree with Stephen that Box is mostly referring to inductive
inference. But then again, with the demonstrative power of really
large inductively tuned models, we're starting to blur the lines
between induction, deduction, and abduction. That false trichotomy was
profound at some point. But these days, sticking to it like Gospel is
problematic.
I accept de-rigeur that "sticking to anything like Gospel" is
problematic. I'm a little slow at the switch here on the earlier part
of the paragraph.. I will study it. It reads at least mildly profound
and I trust not "pseudo-so".
On 10/9/24 10:49, steve smith wrote:
Now the original for the 0 or 2 people who might have endured this far:
The first clause (protasis?) seems to specifically invoke the
"dimension reduction" implications of "compression" but some of the
recent discussion here seems to invoke the "discretization" or more
aptly perhaps the "limited precision"? I think the stuff about
bisimulation is based on this difference?
The trigger for this flurry of "arguing about words" was Wilson's:
"We have Paleolithic emotions, medieval institutions, and
god-like technology."
to which there were varioius objections ranging from (paraphrasing):
"it is just wrong"
"this has been debunked"
to the ad-hominem:
"Wilson was once good at X but he should not be listened to
for Y"
The general uproar *against* this specific aphorism seemed to be
a proxy for:
"it is wrong-headed" and "aphorisms are wrong-headed" ?
then Glen's objection (meat on the bones of "aphorisms are
wrong-headed"?) that aphorisms are "too short" which is what lead me
to thinking about aphorisms as models, models as a form or expression
of compression and the types of compression (lossy/not) and how that
might reflect the "bisimulation" concept
https://en.wikipedia.org/wiki/Bisimulation . At first I had the
"gotcha" or "aha" response to learning more about bisimulation that
it applied exclusively/implicitly to finite-state systems but in fact
it seems that as long as there is an abstraction that obscures or
avoids any "precision" issues it applies to all state-transition
systems.
This lead me to think about the two types of compression that
models (or aphorisms?) offer. One breakdown of the features of
compression in modeling are: Abstraction; Dimension Reduction; Loss
of Detail; Pattern Recognition. The first and last (abstraction
and pattern recognition) seem to be features/goals of modeling, The
middle two seem to be utilitarian while the loss of detail is more of
a bug, an inconvenience nobody values (beyond the utility of keeping
the model small and in the way it facilitates "pattern recognition"
in a ?perverse? way)
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