The ladder of abstractions
This article has been updated as of 08-10-2016 - here is the
previous version
Note: the arrows are the links.
The "ladder of
abstractions" or "abstraction ladder" is a concept taken from the field of
general semantics
, founded by Alfred Korzybski
, that has as its basis
the fact that what we have in our heads is not the real world, but a model
of the world, for which goes: "The map is not the territory" - see the illustration at the right.
The process of making this
model is executed mostly unconsciously, by our sensory organs and the large
number of neurological structures attached to them. The evolutional drive
behind developing this system is that it is advantageous to be able to
distinguish between preditory life forms and friendly or indifferent ones, i.e. to be able
to collect these into separate and distinguishable groups. These groups aren't
objects existing in the real world, thus creating a distinction
between objects in the model that are and those that aren't part of the real
world, the "abstractions" - the most obvious feature of the first illustration.
This capacity is present in
many species, amongst whom certainly those that are able to warn
each other for danger. It is developed the farthest in humankind, in a form known
as "speech". Which has led to more kinds of abstractions, known as "higher
abstractions".
The abstraction ladder
is an attempt to a systematic approach to the relations between the kinds of
groups of all sorts, including the "abstractions", when these are
expressed in words. This is the analagon in speech or language of the
neurological processes taking place in the brain when distinguishing
between species. This description starts by analyzing the different kinds of
words.
The first kind of word and also a prime candidate to be the
origin of the development of speech are here called "object words" - words
that denotes things that you can point to in the real world. They are an
necessity in order to be able to make a connection between a specific utterance of
sounds coming out of your mouth and the objects in de the real world. Even
"modern" kids start to learn language this way, for the example in the
illustration: Mama: "There is Bessie!".
The second kind of words are those of the
natural collections of these objects, in this case: all of the objects that
look like "Bessie": "Clare", "Mathilda" etc., where "Clare" and "Mathilda"
are the "object words" connected to two other "cows" that occupy the meadow
of the farm, where "cows" is the word for the collection of traits that
these three (and probably more) have in common. Whereby also a lot of the
individual traits of Bessie etc. have been lost. The fact that a lot of traits are lost while retaining certain others, is denoted by the
other word for this collection: "abstraction".
Tom's farm is also the residence of other objects besides "cows".
"Horses" and "pigs" are quite different from "cows", but to farmer Tom they
also have similarities: they all require feed, they all produce manure,
etc. These common traits are abbreviated into the word "livestock", which
can also be seen as a "collection of collections". Note there is in general no
natural way to associate a symbol with these "collections of collections"
.
Thereby one can distinguish them from the first kind of collections, which
were equivalently named "abstractions", as "higher order abstractions".
As part of the collection of "livestock", Bessie loses even more of her
specific traits: giving milk (at least: as a mass-producer), and also for
example her color: cows are frequently black-and-white, horses are brown and
pigs are pink. So note: one cannot have "the color of livestock".
It should be clear that this last addition to the kinds of words opens the
floodgates. For example: one can combine farmer Tom's "live stock" with all
of the machinery he needs for his work into "farm assets". Possible further
steps are "property", and "wealth" or "capital". Those are the steps used by
the originator of this version of "the ladder of abstractions", S.I.
Hayakawa
, in his book Language in Thought and Action
(click on the illustration for a larger version).
But other classifications are equally possible: farmer Tom's
property is part of the agricultural assets of the village, the village is
an element of the region, the regions make up the country, etc. So not
only are the floodgates opened as far as the depth of the abstractions is concerned, but this also applies to their width. In fact, the possibilities of making abstractions never end - the universe
is probably big enough for all of them. But this limitation never comes into
sight, because where it is possible to have any number of them, most of
them have little or no practical use: one can take cows together with peeling
knives, but it hardly seems to make any sense (of course: creative types
will have a go after such a statement).
This is the model as
developed in the field of general semantics. It is now going to be extended
with some new features. First of all the abstraction ladder is generalized,
and this generalization leads the way to what was also an ultimate goal of
Korzybski: the connection with neurology and psychology.
The
pivotal point in the abstraction ladder is that every step on it does two
things: like the one taken from cows to farm animals, it enlarges the scope
of the objects, and at the same time it takes away specific traits of the
objects. To further illustrate this point, an interactive model has been
made using the simplest objects: triangles, squares etc. - click on the
illustration (right) to start this. Which immediately introduces an aspect
that is not easy to incorporate into natural models: even the first kind of
collections are not an obvious choice. And it also illustrates that this
choice matters: taking color as an ordering criterium, ends the process
immediately. So besides that the making collections or abstractions is a
crucial step, the choice of which kind of collections i.e. the choice of
criteria is equally vital. It should be clear that the higher the
abstractions that can be build, the more able they will be to see higher
patterns in the environment and thereby to predict future events, leading to
better survivability. And since nature is variable, these criteria shoud not
be build in, but to be learned.
So having concluded that at least in humankind the process of building
abstractions is something that has to be learned, at least in some respects,
the next question is: where and how? The first question has already been
answered, in recent research
, the year of writing being 2016 and that of publication of the research being 2013. The location where the abstractions are made is the
hippocampus, a structure (green on the right) located between the centrally
laying structures that control the emotions, usually called the "limbic
system", and the (neo-)cortex,
the large outer layers of the brain. The (neo-)cortex is
well-known as the place where the "thinking" and "reasoning" using
abstractions takes place - the "cold" cubicles of the left hemipshere in the
first "brain inside" illustration. The central structures that can be called the
"emotion organs" are the neurological
euivalent of the other half, the
"happy, green, fields" of the right hemisphere.
So where the hippocampus is the
location where the impressions of the sensory organs are analyzed into
concepts, using them for "recognition" (note: to re-cognize: "to make sense
of again"), this probably also is the place where the abstractions are
learned. Thus the place where, say by starting with "trial and error", effective
abstractions are enhanced and made permanent and ineffective ones are
discouraged and discarded. And anybody knowing anything about neurology
knows how things are stimulated in the brain: by the use of dopamine.
Thereby almost coming to the essence of these new additions to the
ladder of abstractions: any process in the brain that involves dopamine is
subject to the potential of addiction. In this case: the higher a concept,
the more likely it is to lead to a hit, the more it is stimulated by the
freeing of dopamine, the more prominent the concept becomes in the
hippocampus, the more likely it leads to a hit, etc. Together: higher
concepts are potentially addictive. A large part of the book by Hayakawa is
devoted to describing and correcting errors made both verbally and in
the actual world that are the consequence of the erroneous use op abstractions, in
most cases due to the addictiveness of higher abstractions. Errors having
descriptive and colorful names like "dead level abstracting"
and "chasing each other in verbal circles"
.
With all this extra
knowledge gained, it is possible to further enhance the first illustration
that already showed so inventively the partitioning of the two basic
functionalities of the brain to this:
As a first step, to denote the extra predictive value of using abstractions, the
left hemisphere has been lifted slightly, going further upwards to the left
(as good a possible).
And
the pitfalls are displayed as follows (these are more numerous beacause
something has to be learned from of all of this): - the number of
cubicles is made to correspond (approximately) to the number of concepts,
getting less going to the left and getting further away from reality. - the "persons"
controlling the concept cubicles have their heads turned away from reality
(as before). -
the number of figures crossing over from reality and towards abstractions
is made considerably larger than those going from abstractions back towards
reality.
The crucial lesson to be learned from this all
is of course this: if reasonings or arguments are intended to lead to
something having sense, then always take care that their outcome says
something about reality. The world outside of the model in your head. This
is the step that breaks the inward spiral that leads to addictions.
This sounds really simple, but the number of cases that abide by it
relative to those that don't, is extremely low - outside of the world of the
natural sciences where this step is encoded (
, see the pictures). As an overall guess for all fields outside science, the
maximum percentage is probably lower than twenty. And in all cases where
any kind of ideology is involved, and all cases where retorical fallacies and similar
falsifications of language are used, this percentage tends towards zero with
almost the speed of light.
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