Is creativity a ‘natural’ process?
Abstract
This paper argues for an examination of creativity at a lower functional level than existing
cognitive-sociological models, drawing on the dynamics of self-organizing complex systems
and patterns. Current models focus on cycles or modes of behaviour; whereas dynamic, selforganising physical processes may be directly related to creativity.
Introduction
“We are a part of nature and one of our conceits is to feel apart from it”
- James Turrell (2009), land artist
Turrell’s statement highlights a key influence on human models of culture and aesthetics
which—like persistent dynamic patterns in nature—resist the two extremes of:
disorder–inertia;
rigidity–crystallization.
These are usually avoided during the creative process because dynamic equilibrium
between control and freedom produces a creative ‘goldilocks zone’—we disparage rigid or
formulaic work as much as the unstructured; precious and careless attract similar
opprobrium.
At a more fundamental level than the cultural (Jones 1999), is aesthetic sensibility shaped
by the very processes which sustain us? If so, creativity may actually be driven by the
dynamic complex equilibrium of our physiology in interaction with the same processes in
the natural world. Since recent work on dynamic patterns in human activity has already
yielded findings in neurology (Kelso 1995), notions about creativity invite reassessment.
Creativity as dynamic equilibrium
Much contemporary art practice owes little to the historical concept of ‘nature’, while
seeking a kind of dynamic equilibrium. The ‘too much’ or ‘too little’ inimical to this
equilibrium are—with the parameters of aesthetic judgements—evidence of the exacting
criteria employed iteratively during the creative process. Parameters, within the boundaries
of which a work is intended to emerge, are determined by the artist; with imprecise phrases
such as ‘almost’, ‘too much’ or ‘not quite’ expressing precise aesthetic evaluations shaping
the process (poets agonizing over the famous comma).
The self-organization examined in the many branches of complexity science also occurs in
regions between extremes, beyond which it ‘escapes’ from the intricacies of the complex
system or falls into predictable periodicities or patterns. Further (unlike chaotic models)
self-organization in the natural world is unrepeatable, yet the parameters hold (an oak tree
distinct from all other remains within the Subgenus Quercus, each cloud is unique…).
The natural world: inspiration or literal model?
To treat the living body as a mechanism was repugnant, and seemed even
ludicrous, to Pascal... Even now the zoologist has scarce begun to dream of defining
in mathematical language even the simplest organic forms. When he meets with a
simple geometrical construction, for instance in the honeycomb, he would fain
refer it to psychical instinct, or to skill and ingenuity, rather than to the operation
of physical forces or mathematical laws —‘On Growth and Form’ (Wentworth
2008)
At the original publication date (1917) it was necessary to assert that the beauty of natural
forms was not an unfathomable or religious mystery. With the advantage of almost 100
intervening years of knowledge, Philip Ball’s work covers similar territory for the 21 st
century (Ball 1999, 2009), documenting how identical pattern-forming processes are
common to a surprisingly diverse range of phenomena, for instance: branching trees, river
deltas, mineral dendrite patterns; even liquid ethane flows on Saturn’s moon Titan. Less
obviously, superficially unconnected phenomena such as zebra stripes, sand dunes,
chemical oscillations and heart defibrillation are revealed as manifestations of a group of
underlying processes that can be modeled consistently (with cellular automata and
formulae), revealing generic patterns across a diverse array of materials and scales.
At smaller scales, self-organization is apparent in the atomic structures underlying the
material from which large-scale patterns constituted; others apparent in processes as vast as
galaxy formation, are also observed in chemical interactions. Some patterns are temporal,
others spatial; some (like strange attractors) appear only when plotted multi-dimensionally.
When excited by increased energy, some oscillating systems double their periodic rate in
regular numerical sequences. Transitions between these sequences are unstable—
oscillations jump about within parameters but without stability, breaking the symmetry of
the periodic oscillations. This symmetry-breaking is also necessary for self-organizing
patterns to arise from a homogenous unity; embryonic cell division, required for the
development of specialized cells in complex living beings, is an example.
As with ‘On Growth and Form’, self-organizing patterns appeal to aesthetic sensibilities. Yet
even where such findings have been employed as deep analogy (see DeLanda 2002, pp94-95
on bifurcation), they cannot prove a literal connection. So let us suppose they actually
determine the creative process as homology, where phenomenal similarity is due to
common origin or shared dynamic.
Analogies and homologies
Patterns integral to the creative process have their labels: blockages, flow, rhythm and
destabilization, and a periodic need to break the symmetry of stable but stagnant states. Our
recognition of such states may betray an underlying homology with dynamic patterns—in
which case our attraction to those patterns in the natural world cannot be dissociated from
those within our own being.
Patterns ‘outside ourselves’ evoke a sense of beauty, awe or connection perhaps only
because of our self-conscious separation from them:
the history of aesthetics… in the work of Kant [‘Critique of Judgement’] and others
in the eighteenth- and nineteenth-centuries, is a story about one of the last covertly
theological attempts to bridge the seemingly unsurpassable chasm between “man”
and “nature,” inside and outside, subject and object. (Jones 1999)
As observers, our aesthetic appreciation of the natural world can only be enhanced by
accepting the intimate connection between our individuality and the dynamic patterns of
the natural world, since these exist within our physiology and even consciousness (see
Kirilyuk 2004 for machine consciousness; Jordan and Ghin 2006 for a psychological
overview). Perhaps aesthetics formalises an unconscious appreciation of this connection, as
some works express this relationship. The land-art of Nancy Holt (Holt 1973), illustrates the
cyclic rhythms of the phenomenal world. The music of Sonic Youth (1994) popularized a
kind of symmetry-breaking, with chaotic detuned passages breaking up melodic structures.
More directly, composer David Burraston (2009) uses complex dynamic systems to
generate work, employing ‘cellular automata and nature’ in the form of a ‘long wire
instrument’.
Scientific terminology is regularly misused to lend credence to popular analogies
masquerading as literal models: New Age ‘energies’, ‘right-left brain’ misconceptions, ‘phase
shift’ or ‘quantum leap’ to describe radical change, or even ‘strange attractor’ because of its
poetic appeal. Models of human behaviour based on complex dynamic systems can only be
validated by evidence that such patterns emerge in a quantifiable manner, not by analogy.
Such validation would break that persistent barrier between ‘human’ and ‘natural’.
However, the leap from analogy to homology can only be made if patterns already
documented in complex phenomena also emerge consistently when creativity is studied.
The central issue therefore revolves around whether these parallels are analogy or
homology; does the creative process actually share the same structure, origin and patterns
as these phenomena but have a different function, or is the similarity phenomenal?
Towards finer-grained models of creativity
Research into creativity via the interdisciplinary fields and complexity and dynamic patterns
is preceded by social science research that reveals such systems operating at human scales
(e.g. Klemm et al 2003, or Holyst 2000). As a contrast to this established work, Ben
Goertzel (1996) explains the tentative nature of his thinking about consciousness, creativity
and complexity:
Some readers may be disturbed by my heady mixture of “finished” research
projects, raw philosophical speculations, and promising scientific beginnings.
However, my feeling is that his mixture is entirely appropriate to the subject
matter.
Other work on creativity and complexity appears diverse, covering areas beyond the scope
of creativity, although terms from dynamic systems are apparent:
a creative idea may be classified simply as a conceptual change. When viewed
through the lens of complexity thinking, conceptual changes bear intriguing
similarities to the behaviours of complex phenomena. (Roy 2007)
Yet ‘intriguing similarities’ are still analogies. If homologies between creative processes and
complex dynamics exist, how do established approaches to creativity measure up (e.g. those
reviewed in Schunn et al 2006 and Plsek 1996)? For instance, the view:
that creative ideas emerge from a largely uncontrollable Darwinian process of
random variation and natural selection (Plsek 1996)
is countered by the observations of Ball (1999, pp77-78) and Alexander (2001) that natural
selection cannot account for patterns generated by the properties of matter itself.
Psychological and philosophical approaches to creativity gloss over this subtle energetic
dynamism inherent in form; they do not even take it for granted but often ignore its
implications entirely, as noted by Kelso (1995):
when eminent physicists and biologists... consider [...] properties of living things
such as consciousness and creativity, they completely ignore (or are ignorant of)
theories of cooperative phenomena far from equilibrium
Linearity, circularity and iteration
Wallas (quoted in Plsek 1996) proposed one of the earliest models of the creative process:
preparation, incubation, illumination, verification. Successive models generally build on
this, yet fail to detail the iterative judgements driving a satisfactory creative outcome any
further than the ‘adjust, learn, evaluate, adjust’ of Fritz (1991). There is even a certain
clunkiness to the metaphors:
these… models […] are complex scripts for higher-order thinking. Regardless of the
specific model we chose, we are called to engage in an intricate mental dance over
an extended period of time. The complexity implied by this balancing act is
probably the reason why creative ideas are so rare. Even though we all possess the
underlying mental building blocks for creative thinking, stacking the blocks just
right is very difficult work! (Plsek 1996)
Linearity is also a recognized inadequacy in models of behaviour, as pointed out by
Stenmark (2002) while critiquing knowledge management models:
The problem with the oversimplified figure [Data -> Information -> Knowledge] is
that it holds three tacitly understood assumptions, which all can be questioned.
Firstly… that the relationship between data, information, and knowledge is linear.
The distance between data and information is the same as the distance between
information and knowledge, implying that the effort required moving from one
entity to another is the same. Though it may not be possible to correctly state the
true relationship between these entities, there is nothing that indicates that it
should be linear.
Instead of ‘building blocks’ and ‘stages’, models of creativity might benefit from the iterative
nature of equations describing dynamic processes:
…circularity can be represented by an equation representing how some
phenomenon or variable y is mapped, by a transformation or process f, onto itself:
y = f(y)
[...] Such equations have been extensively studied as iterated maps, and are the
basis of chaotic dynamics and fractal geometry. —Heylighen and Joslyn (2001)
This simplified example illustrates a point—that creative output is fed back into the process
to generate the next output, until a satisfactory result emerges. An actual homology is given
by Kelso (1995 pp122-123) in his work on tapping rhythms, that reveals why musicians must
‘break the symmetry’ of ‘easy’ ratios in order to express more intricate patterns. The
implication is that parameters of creative activity are determined at a very fine-grained level
by natural patterns, since human transitions from one pattern to another reveal the same
processes observed in non-human complex dynamic systems.
Work in this field often highlights the ‘attractor’ concept:
Once a system has entered an attractor, it can no longer reach states outside the
attractor. This means that our uncertainty […] about the system's state has
decreased: we now know for sure that it is not in any state that is not part of the
attractor. This spontaneous reduction of entropy or, equivalently, increase in order
or constraint, can be viewed as a most general model of self-organization.
(Heylighen and Joslyn 2001)
Elements of cultural, environmental and personal influence then become valuable ‘noise’,
influencing the outcome:
...self-organization can be enhanced by random perturbations (“noise”) of the
system’s state, which speed up… descent… through the basin, and makes it leave
shallow attractors so that it can reach deeper ones. This is the order from noise
principle. (Heylighen and Joslyn 2001)
A complex dynamic approach to creativity raises many questions. For instance, does
Csikszentmihalyi’s (1996) state of ‘flow’ begin with a phase shift, or does a bifurcation
herald dynamic stability? What incremental processes occur during the ‘working’ phase of
Galenson’s planning-working-stopping model? Seurat stated “I apply my method and that is
all there is to it” (in Galenson 2006). How do we map the incremental judgments that keep
creative practice both within bounds and producing variety? Linear models derived from
Wallas (Plsek 1996) cannot capture every adjustment made during the creative process, but
we know that the complex dynamics of perception and physical motion reveal homologies
between human capability and dynamic patterns (Kelso 1995). The conceptual gap between
human and natural is apparently closing, and with it the distance between analogy and
homology.
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