The Complexity of Simplicity

By Sam Vaknin

"Everything is simpler than you think and at the same time more complex than
you imagine."
(Johann Wolfgang von Goethe)

Complexity rises spontaneously in nature through processes such as
self-organization. Emergent phenomena are common as are emergent traits, not
reducible to basic components, interactions, or properties.

Complexity does not, therefore, imply the existence of a designer or a
design. Complexity does not imply the existence of intelligence and sentient
beings. On the contrary, complexity usually points towards a natural source
and a random origin. Complexity and artificiality are often incompatible.

Artificial designs and objects are found only in unexpected ("unnatural")
contexts and environments. Natural objects are totally predictable and
expected. Artificial creations are efficient and, therefore, simple and
parsimonious. Natural objects and processes are not.

As Seth Shostak notes in his excellent essay, titled "SETI and Intelligent
Design", evolution experiments with numerous dead ends before it yields a
single adapted biological entity. DNA is far from optimized: it contains
inordinate amounts of junk. Our bodies come replete with dysfunctional
appendages and redundant organs. Lightning bolts emit energy all over the
electromagnetic spectrum. Pulsars and interstellar gas clouds spew radiation
over the entire radio spectrum. The energy of the Sun is ubiquitous over the
entire optical and thermal range. No intelligent engineer - human or not -
would be so wasteful.

Confusing artificiality with complexity is not the only terminological
conundrum.

Complexity and simplicity are often, and intuitively, regarded as two
extremes of the same continuum, or spectrum. Yet, this may be a simplistic
view, indeed.

Simple procedures (codes, programs), in nature as well as in computing,
often yield the most complex results. Where does the complexity reside, if
not in the simple program that created it? A minimal number of primitive
interactions occur in a primordial soup and, presto, life. Was life somehow
embedded in the primordial soup all along? Or in the interactions? Or in the
combination of substrate and interactions?

Complex processes yield simple products (think about products of thinking
such as a newspaper article, or a poem, or manufactured goods such as a
sewing thread). What happened to the complexity? Was it somehow reduced,
"absorbed, digested, or assimilated"? Is it a general rule that, given
sufficient time and resources, the simple can become complex and the complex
reduced to the simple? Is it only a matter of computation?

We can resolve these apparent contradictions by closely examining the
categories we use.

Perhaps simplicity and complexity are categorical illusions, the outcomes of
limitations inherent in our system of symbols (in our language).

We label something "complex" when we use a great number of symbols to
describe it. But, surely, the choices we make (regarding the number of
symbols we use) teach us nothing about complexity, a real phenomenon!

A straight line can be described with three symbols (A, B, and the distance
between them) - or with three billion symbols (a subset of the discrete
points which make up the line and their inter-relatedness, their function).
But whatever the number of symbols we choose to employ, however complex our
level of description, it has nothing to do with the straight line or with
its "real world" traits. The straight line is not rendered more (or less)
complex or orderly by our choice of level of (meta) description and language
elements.

The simple (and ordered) can be regarded as the tip of the complexity
iceberg, or as part of a complex, interconnected whole, or hologramically,
as encompassing the complex (the same way all particles are contained in all
other particles). Still, these models merely reflect choices of descriptive
language, with no bearing on reality.

Perhaps complexity and simplicity are not related at all, either
quantitatively, or qualitatively. Perhaps complexity is not simply more
simplicity. Perhaps there is no organizational principle tying them to one
another. Complexity is often an emergent phenomenon, not reducible to
simplicity.

The third possibility is that somehow, perhaps through human intervention,
complexity yields simplicity and simplicity yields complexity (via pattern
identification, the application of rules, classification, and other human
pursuits). This dependence on human input would explain the convergence of
the behaviors of all complex systems on to a tiny sliver of the state (or
phase) space (sort of a mega attractor basin). According to this view, Man
is the creator of simplicity and complexity alike but they do have a real
and independent existence thereafter (the Copenhagen interpretation of a
Quantum Mechanics).

Still, these twin notions of simplicity and complexity give rise to numerous
theoretical and philosophical complications.

Consider life.

In human (artificial and intelligent) technology, every thing and every
action has a function within a "scheme of things". Goals are set, plans
made, designs help to implement the plans.

Not so with life. Living things seem to be prone to disorientated thoughts,
or the absorption and processing of absolutely irrelevant and
inconsequential data. Moreover, these laboriously accumulated databases
vanish instantaneously with death. The organism is akin to a computer which
processes data using elaborate software and then turns itself off after
15-80 years, erasing all its work.

Most of us believe that what appears to be meaningless and functionless
supports the meaningful and functional and leads to them. The complex and
the meaningless (or at least the incomprehensible) always seem to resolve to
the simple and the meaningful. Thus, if the complex is meaningless and
disordered then order must somehow be connected to meaning and to simplicity
(through the principles of organization and interaction).

Moreover, complex systems are inseparable from their environment whose
feedback induces their self-organization. Our discrete, observer-observed,
approach to the Universe is, thus, deeply inadequate when applied to complex
systems. These systems cannot be defined, described, or understood in
isolation from their environment. They are one with their surroundings.

Many complex systems display emergent properties. These cannot be predicted
even with perfect knowledge about said systems. We can say that the complex
systems are creative and intuitive, even when not sentient, or intelligent.
Must intuition and creativity be predicated on intelligence, consciousness,
or sentience?

Thus, ultimately, complexity touches upon very essential questions of who
we, what are we for, how we create, and how we evolve. It is not a simple
matter, that...

TECHNICAL NOTE - Complexity Theory and Ambiguity or Vagueness

A Glossary of the terms used here

Ambiguity (or indeterminacy, in deconstructivist parlance) is when a
statement or string (word, sentence, theorem, or expression) has two or more
distinct meanings either lexically (e.g., homonyms), or because of its
grammar or syntax (e.g., amphiboly). It is the context, which helps us to
choose the right or intended meaning ("contextual disambiguating" which
often leads to a focal meaning).

Vagueness arises when there are "borderline cases" of the existing
application of a concept (or a predicate). When is a person tall? When does
a collection of sand grains become a heap (the sorites or heap paradox)?,
etc. Fuzzy logic truth values do not eliminate vagueness - they only assign
continuous values ("fuzzy sets") to concepts ("prototypes").

Open texture is when there may be "borderline cases" in the future
application of a concept (or a predicate). While vagueness can be minimized
by specifying rules (through precisifaction, or supervaluation) - open
texture cannot because we cannot predict future "borderline cases".

It would seem that a complexity theory formalism can accurately describe
both ambiguity and vagueness:

Language can be construed as a self-organizing network, replete with
self-organized criticality.

Language can also be viewed as a Production System (Iterated Function
Systems coupled with Lindenmeyer L-Systems and Schemas to yield Classifiers
Systems). To use Holland's vocabulary, language is a set of Constrained
Generating Procedures.

"Vague objects" (with vague spatial or temporal boundaries) are, actually,
best represented by fractals. They are not indeterminate (only their
boundaries are). Moreover, self-similarity is maintained. Consider a
mountain - where does it start or end and what, precisely, does it include?
A fractal curve (boundary) is an apt mathematical treatment of this
question.

Indeterminacy can be described as the result of bifurcation leading to
competing, distinct, but equally valid, meanings.

Borderline cases (and vagueness) arise at the "edge of chaos" - in concepts
and predicates with co-evolving static and chaotic elements.

(Focal) meanings can be thought of as attractors.

Contexts can be thought of as attractor landscapes in the phase space of
language. They can also be described as fitness landscapes with optimum
epistasis (interdependence of values assigned to meanings).

The process of deriving meaning (or disambiguating) is akin to tracing a
basin of attraction. It can be described as a perturbation in a transient,
leading to a stable state.



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AUTHOR BIO (must be included with the article)



Sam Vaknin ( http://samvak.tripod.com ) is the author of Malignant Self
Love - Narcissism Revisited and After the Rain - How the West Lost the East.
He served as a columnist for Global Politician, Central Europe Review,
PopMatters, Bellaonline, and eBookWeb, a United Press International (UPI)
Senior Business Correspondent, and the editor of mental health and Central
East Europe categories in The Open Directory and Suite101.

Visit Sam's Web site at http://samvak.tripod.com