Chapter 1 Creativity

Transcription

Chapter 1
Creativity
Creativity is a phenomenon whereby something new and
in some way valuable is created (such as an idea, a joke,
an artistic or literary work, a painting or musical composition, a solution, an invention etc). The range of scholarly
interest in creativity includes a multitude of definitions
and approaches involving several disciplines; psychology,
cognitive science, education, philosophy (particularly
philosophy of science), technology, theology, sociology,
linguistics, business studies, songwriting and economics,
taking in the relationship between creativity and general
intelligence, mental and neurological processes associated with creativity, the relationships between personality
type and creative ability and between creativity and mental health, the potential for fostering creativity through education and training, especially as augmented by technology, and the application of creative resources to improve
the effectiveness of learning and teaching processes.
cess is shown in cognitive approaches that try to describe
thought mechanisms and techniques for creative thinking. Theories invoking divergent rather than convergent
thinking (such as Guilford), or those describing the staging of the creative process (such as Wallas) are primarily
theories of creative process. A focus on creative product
usually appears in attempts to measure creativity (psychometrics, see below) and in creative ideas framed as
successful memes.[5] The psychometric approach to creativity reveals that it also involves the ability to produce
more.[6] A focus on the nature of the creative person considers more general intellectual habits, such as openness,
levels of ideation, autonomy, expertise, exploratory behavior and so on. A focus on place considers the circumstances in which creativity flourishes, such as degrees
of autonomy, access to resources and the nature of gatekeepers. Creative lifestyles are characterized by nonconforming attitudes and behaviors as well as flexibility.[6]
1.1 Definition
1.3 Etymology
In a summary of scientific research into creativity,
Michael Mumford suggested: “Over the course of the
last decade, however, we seem to have reached a general agreement that creativity involves the production of
novel, useful products” (Mumford, 2003, p. 110).[1]
Creativity can also be defined “as the process of producing something that is both original and worthwhile”
or “characterized by originality and expressiveness and
imaginative”.[2] What is produced can come in many
forms and is not specifically singled out in a subject or
area. Authors have diverged dramatically in their precise
definitions beyond these general commonalities: Peter
Meusburger reckons that over a hundred different analyses can be found in the literature.[3]
The lexeme in the English word creativity comes from the
Latin term creō “to create, make": its derivational suffixes
also come from Latin. The word “create” appeared in English as early as the 14th century, notably in Chaucer, to
indicate divine creation[7] (in The Parson’s Tale[8] ). However, its modern meaning as an act of human creation did
not emerge until after the Enlightenment.[7]
1.4 History of the concept
Main article: History of the concept of creativity
1.2 Aspects
1.4.1 Ancient views
Theories of creativity (particularly investigation of why
some people are more creative than others) have focused
on a variety of aspects. The dominant factors are usually
identified as “the four Ps” — process, product, person
and place (according to Mel Rhodes).[4] A focus on pro-
Most ancient cultures, including thinkers of Ancient
Greece,[9] Ancient China, and Ancient India,[10] lacked
the concept of creativity, seeing art as a form of discovery and not creation. The ancient Greeks had no terms
corresponding to “to create” or “creator” except for the
2
1.4. HISTORY OF THE CONCEPT
3
would dominate the West probably until the Renaissance
and even later.[13] The development of the modern concept of creativity begins in the Renaissance, when creation began to be perceived as having originated from
the abilities of the individual, and not God. However,
this shift was gradual and would not become immediately apparent until the Enlightenment.[15] By the 18th
century and the Age of Enlightenment, mention of creativity (notably in art theory), linked with the concept of
imagination, became more frequent.[16] In the writing of
Thomas Hobbes, imagination became a key element of
human cognition;[7] William Duff was one of the first to
identify imagination as a quality of genius, typifying the
separation being made between talent (productive, but
breaking no new ground) and genius.[14]
Greek philosophers like Plato rejected the concept of creativity,
preferring to see art as a form of discovery. Asked in The Republic, “Will we say, of a painter, that he makes something?",
Plato answers, “Certainly not, he merely imitates.”[9]
expression "poiein" (“to make”), which only applied to
poiesis (poetry) and to the poietes (poet, or “maker”) who
made it. Plato did not believe in art as a form of creation.
Asked in The Republic,[11] “Will we say, of a painter,
that he makes something?", he answers, “Certainly not,
he merely imitates.”[9]
It is commonly argued that the notion of “creativity”
originated in Western culture through Christianity, as a
matter of divine inspiration.[7] According to the historian Daniel J. Boorstin, “the early Western conception
of creativity was the Biblical story of creation given in
the Genesis.”[12] However, this is not creativity in the
modern sense, which did not arise until the Renaissance.
In the Judaeo-Christian tradition, creativity was the sole
province of God; humans were not considered to have
the ability to create something new except as an expression of God’s work.[13] A concept similar to that of Christianity existed in Greek culture, for instance, Muses were
seen as mediating inspiration from the Gods.[14] Romans
and Greeks invoked the concept of an external creative
"daemon" (Greek) or "genius" (Latin), linked to the sacred or the divine. However, none of these views are
similar to the modern concept of creativity, and the individual was not seen as the cause of creation until the
Renaissance.[15] It was during the Renaissance that creativity was first seen, not as a conduit for the divine, but
from the abilities of "great men".[15]
1.4.2
The Enlightenment and after
The rejection of creativity in favor of discovery and the
belief that individual creation was a conduit of the divine
As a direct and independent topic of study, creativity effectively received no attention until the 19th century.[14]
Runco and Albert argue that creativity as the subject of
proper study began seriously to emerge in the late 19th
century with the increased interest in individual differences inspired by the arrival of Darwinism. In particular
they refer to the work of Francis Galton, who through his
eugenicist outlook took a keen interest in the heritability of intelligence, with creativity taken as an aspect of
genius.[7]
In the late 19th and early 20th centuries, leading mathematicians and scientists such as Hermann von Helmholtz
(1896) and Henri Poincaré (1908) began to reflect on and
publicly discuss their creative processes.
1.4.3 Twentieth century to the present day
The insights of Poincaré and von Helmholtz were built
on in early accounts of the creative process by pioneering theorists such as Graham Wallas[17] and Max
Wertheimer. In his work Art of Thought, published in
1926, Wallas presented one of the first models of the creative process. In the Wallas stage model, creative insights
and illuminations may be explained by a process consisting of 5 stages:
(i) preparation (preparatory work on a problem
that focuses the individual’s mind on the problem and explores the problem’s dimensions),
(ii) incubation (where the problem is internalized into the unconscious mind and nothing appears externally to be happening),
(iii) intimation (the creative person gets a “feeling” that a solution is on its way),
(iv) illumination or insight (where the creative
idea bursts forth from its preconscious processing into conscious awareness);
(v) verification (where the idea is consciously
verified, elaborated, and then applied).
4
CHAPTER 1. CREATIVITY
Wallas’ model is often treated as four stages, with “inti- Robinson[26] and Anna Craft[27] have focused on creativmation” seen as a sub-stage.
ity in a general population, particularly with respect to eddistinction between “high”
Wallas considered creativity to be a legacy of the ucation. Craft makes a similar
[27]
and
cites Ken Robinson as
and
“little
c”
creativity.
evolutionary process, which allowed humans to quickly
referring
to
“high”
and
“democratic”
creativity. Mihály
[18]
adapt to rapidly changing environments. Simonton
[28]
Csíkszentmihályi
has
defined
creativity
in terms of
provides an updated perspective on this view in his book,
those
individuals
judged
to
have
made
significant
creOrigins of genius: Darwinian perspectives on creativity.
ative, perhaps domain-changing contributions. Simonton
In 1927, Alfred North Whitehead gave the Gifford Lec- has analysed the career trajectories of eminent creative
tures at the University of Edinburgh, later published as people in order to map patterns and predictors of creative
Process and Reality.[19] He is credited with having coined productivity.[29]
the term “creativity” to serve as the ultimate category
of his metaphysical scheme: “Whitehead actually coined
the term – our term, still the preferred currency of exchange among literature, science, and the arts. . . a
term that quickly became so popular, so omnipresent, that 1.5 Theories of creative processes
its invention within living memory, and by Alfred North
Whitehead of all people, quickly became occluded”.[20]
There has been much empirical study in psychology and
The formal psychometric measurement of creativity, cognitive science of the processes through which creativfrom the standpoint of orthodox psychological literature, ity occurs. Interpretation of the results of these studies
is usually considered to have begun with J. P. Guilford's has led to several possible explanations of the sources and
1950 address to the American Psychological Association, methods of creativity.
which helped popularize the topic[21] and focus attention
on a scientific approach to conceptualizing creativity. (It
should be noted that the London School of Psychology
had instigated psychometric studies of creativity as early
as 1927 with the work of H. L. Hargreaves into the Faculty of Imagination,[22] but it did not have the same impact.) Statistical analysis led to the recognition of creativity (as measured) as a separate aspect of human cognition to IQ-type intelligence, into which it had previously
been subsumed. Guilford’s work suggested that above a
threshold level of IQ, the relationship between creativity
and classically measured intelligence broke down.[23]
1.5.1 Incubation
Incubation is a temporary break from creative problem
solving that can result in insight.[30] There has been some
empirical research looking at whether, as the concept of
“incubation” in Wallas’ model implies, a period of interruption or rest from a problem may aid creative problemsolving. Ward[31] lists various hypotheses that have been
advanced to explain why incubation may aid creative
problem-solving, and notes how some empirical evidence
is consistent with the hypothesis that incubation aids creative problem-solving in that it enables “forgetting” of
1.4.4 “Four C” model
misleading clues. Absence of incubation may lead the
problem solver to become fixated on inappropriate strateJames C. Kaufman and Beghetto introduced a “four C” gies of solving the problem.[32] This work disputes the
model of creativity; mini-c (“transformative learning” in- earlier hypothesis that creative solutions to problems arise
volving “personally meaningful interpretations of expe- mysteriously from the unconscious mind while the conriences, actions and insights”), little-c (everyday prob- scious mind is occupied on other tasks.[33]
lem solving and creative expression), Pro-C (exhibited
by people who are professionally or vocationally creative though not necessarily eminent) and Big-C (creativity considered great in the given field). This model was 1.5.2 Convergent and divergent thinking
intended to help accommodate models and theories of
creativity that stressed competence as an essential com- J. P. Guilford[34] drew a distinction between convergent
ponent and the historical transformation of a creative do- and divergent production (commonly renamed convermain as the highest mark of creativity. It also, the authors gent and divergent thinking). Convergent thinking inargued, made a useful framework for analyzing creative volves aiming for a single, correct solution to a problem,
processes in individuals.[24]
whereas divergent thinking involves creative generation
The contrast of terms “Big C” and “Little c” has been
widely used. Kozbelt, Beghetto and Runco use a littlec/Big-C model to review major theories of creativity [23]
Margaret Boden distinguishes between h-creativity (historical) and p-creativity (personal).[25]
of multiple answers to a set problem. Divergent thinking
is sometimes used as a synonym for creativity in psychology literature. Other researchers have occasionally used
the terms flexible thinking or fluid intelligence, which are
roughly similar to (but not synonymous with) creativity.
1.5. THEORIES OF CREATIVE PROCESSES
1.5.3
Creative cognition approach
In 1992, Finke et al. proposed the “Geneplore” model, in
which creativity takes place in two phases: a generative
phase, where an individual constructs mental representations called preinventive structures, and an exploratory
phase where those structures are used to come up with
creative ideas. Some evidence shows that when people
use their imagination to develop new ideas, those ideas
are heavily structured in predictable ways by the properties of existing categories and concepts.[35] Weisberg[36]
argued, by contrast, that creativity only involves ordinary
cognitive processes yielding extraordinary results.
1.5.4
The Explicit–Implicit Interaction
(EII) theory
Helie and Sun[37] recently proposed a unified framework
for understanding creativity in problem solving, namely
the Explicit–Implicit Interaction (EII) theory of creativity. This new theory constitutes an attempt at providing a
more unified explanation of relevant phenomena (in part
by reinterpreting/integrating various fragmentary existing
theories of incubation and insight). The EII theory relies mainly on five basic principles, namely 1) The coexistence of and the difference between explicit and implicit knowledge; 2) The simultaneous involvement of implicit and explicit processes in most tasks; 3) The redundant representation of explicit and implicit knowledge;
4) The integration of the results of explicit and implicit
processing; and 5) The iterative (and possibly bidirectional) processing. A computational implementation of
the theory was developed based on the CLARION cognitive architecture and used to simulate relevant human
data. This work represents an initial step in the development of process-based theories of creativity encompassing incubation, insight, and various other related phenomena.
1.5.5
Conceptual blending
Main article: Conceptual blending
In The Act of Creation, Arthur Koestler introduced the
concept of bisociation—that creativity arises as a result of the intersection of two quite different frames of
reference.[38] This idea was later developed into conceptual blending. In the '90s, various approaches in cognitive
science that dealt with metaphor, analogy and structure
mapping have been converging, and a new integrative approach to the study of creativity in science, art and humor
has emerged under the label conceptual blending.
5
1.5.6 Honing theory
Honing theory posits that creativity arises due to the selforganizing, self-mending nature of a worldview, and that
it is by way of the creative process the individual hones
(and re-hones) an integrated worldview. Honing theory
places equal emphasis on the externally visible creative
outcome and the internal cognitive restructuring brought
about by the creative process. Indeed one factor that
distinguishes it from other theories of creativity is that
it focuses on not just restructuring as it pertains to the
conception of the task, but as it pertains to the worldview as a whole. When faced with a creatively demanding task, there is an interaction between the conception
of the task and the worldview. The conception of the
task changes through interaction with the worldview, and
the worldview changes through interaction with the task.
This interaction is reiterated until the task is complete, at
which point not only is the task conceived of differently,
but the worldview is subtly or drastically transformed.
Thus another distinguishing feature of honing theory is
that the creative process reflects the natural tendency of a
worldview to attempt to resolve dissonance and seek internal consistency amongst its components, whether they
be ideas, attitudes, or bits of knowledge; it mends itself
as does a body when it has been injured.
Yet another central, distinguishing feature of honing theory is the notion of a potentiality state.[39] Honing theory posits that creative thought proceeds not by searching
through and randomly ‘mutating’ predefined possibilities,
but by drawing upon associations that exist due to overlap
in the distributed neural cell assemblies that participate in
the encoding of experiences in memory. Midway through
the creative process one may have made associations between the current task and previous experiences, but not
yet disambiguated which aspects of those previous experiences are relevant to the current task. Thus the creative
idea may feel ‘half-baked’. It is at that point that it can
be said to be in a potentiality state, because how it will
actualize depends on the different internally or externally
generated contexts it interacts with.
Honing theory can account for many phenomena that are
not readily explained by other theories of creativity. For
example, creativity was commonly thought to be fostered
by a supportive, nurturing, trustworthy environment conducive to self-actualization. However, research shows
that creativity is actually associated with childhood adversity, which would stimulate honing. Honing theory also
makes several predictions that differ from what would be
predicted by other theories. For example, empirical support has been obtained using analogy problem solving experiments for the proposal that midway through the creative process one’s mind is in a potentiality state. Other
experiments show that different works by the same creator exhibit a recognizable style or 'voice', and that this
same recognizable quality even comes through in different creative outlets. This is not predicted by theories of
6
creativity that emphasize chance processes or the accumulation of expertise, but it is predicted by honing theory,
according to which personal style reflects the creator’s
uniquely structured worldview. This theory has been developed by Liane Gabora.
1.5.7
Everyday imaginative thought
In everyday thought, people often spontaneously imagine alternatives to reality when they think “if only...”.[40]
Their counterfactual thinking is viewed as an example
of everyday creative processes.[41] It has been proposed
that the creation of counterfactual alternatives to reality depends on similar cognitive processes to rational
thought.[42]
1.6 Measuring
1.6.1
Creativity quotient
• Unusual Uses is finding unusual uses for common
everyday objects such as bricks.
• Remote Associations, where participants are asked
to find a word between two given words (e.g. Hand
_____ Call)
• Remote Consequences, where participants are
asked to generate a list of consequences of unexpected events (e.g. loss of gravity)
Building on Guilford’s work, Torrance[45] developed the
Torrance Tests of Creative Thinking in 1966.[46] They
involved simple tests of divergent thinking and other
problem-solving skills, which were scored on:
• Fluency – The total number of interpretable, meaningful and relevant ideas generated in response to the
stimulus.
• Originality – The statistical rarity of the responses
among the test subjects.
• Elaboration – The amount of detail in the responses.
Several attempts have been made to develop a creativity
quotient of an individual similar to the intelligence quo- The Creativity Achievement Questionnaire, a self-report
tient (IQ), however these have been unsuccessful.[43]
test that measures creative achievement across 10 doIn Malcolm Gladwell's 2008 book Outliers: The Story mains, was described in 2005 and shown to be reliable
of Success,[44] there is mentioning of a “divergence test”. and valid when compared to other measures of creativity
As opposed to “convergence tests”, where a test taker is and to independent evaluation of creative output.[47]
asked to sort through a list of possibilities and converge Such tests, sometimes called Divergent Thinking (DT)
on the right answer, a divergence test requires one to use tests have been both supported[48] and criticized.[49]
imagination and take one’s mind in as many different directions as possible. “With a divergence test, obviously
there isn't a single right answer. What the test giver is 1.6.3 Social-personality approach
looking for are the number and uniqueness of your responses. And what the test is measuring isn't analytical Some researchers have taken a social-personality apintelligence but something profoundly different -- some- proach to the measurement of creativity. In these studthing much closer to creativity. Divergence tests are ev- ies, personality traits such as independence of judgeery bit as challenging as convergence tests.”
ment, self-confidence, attraction to complexity, aesthetic
orientation and risk-taking are used as measures of the
creativity of individuals.[21] A meta-analysis by Gregory
1.6.2 Psychometric approach
Feist showed that creative people tend to be “more open
to new experiences, less conventional and less conscienJ. P. Guilford's group,[34] which pioneered the modern tious, more self-confident, self-accepting, driven, ambipsychometric study of creativity, constructed several tests tious, dominant, hostile,and impulsive.” Openness, conto measure creativity in 1967:
scientiousness, self-acceptance, hostility and impulsivity
had the strongest effects of the traits listed.[50] Within the
of personality some
• Plot Titles, where participants are given the plot of framework of the Big Five model
[51]
consistent
traits
have
emerged.
Openness
to experia story and asked to write original titles.
ence has been shown to be consistently related to a whole
[52]
Among
• Quick Responses is a word-association test scored host of different assessments of creativity.
the other Big Five traits, research has demonstrated subfor uncommonness.
tle differences between different domains of creativity.
• Figure Concepts, where participants were given sim- Compared to non-artists, artists tend to have higher levels
ple drawings of objects and individuals and asked to of openness to experience and lower levels of conscienfind qualities or features that are common by two or tiousness, while scientists are more open to experience,
more drawings; these were scored for uncommon- conscientious, and higher in the confidence-dominance
facets of extraversion compared to non-scientists.[50]
ness.
1.9. NEUROBIOLOGY
1.7 Declining U.S. creativity?
Creativity as measured by the Torrance Tests of Creative
Thinking increased until 1990 in the United States, an
effect similar to the Flynn effect. Thereafter scores have
been declining. Possible causes include increased time
spent watching TV, increased time spent playing computer games, or lacking nurturing of creativity in schools.
There may also be a mistaken assumption that encouraging creativity in schools necessarily involve the arts when
it also can be encouraged in other subjects.[53]
A growing global educational reform movement commonly known as 21st Century Learning aims to promote
creativity across the curriculum. In general, it advocates
teaching lifelong skills such as critical thinking, problem
solving, collaboration and communication for core academic subjects including Science, Technology, Engineering and Math (STEM), as well as the arts. Insofar as
the movement promotes a new focus on teaching/learning
creativity and innovation skills through activities that promote higher-order thinking skills, it also requires the development of additional metrics to score originality and
innovation, as well as technical correctness. Odyssey of
the Mind is a non-profit educational program that provides challenging divergent problems to foster original
thinking across the curriculum, and has effectively promoted creativity education worldwide since the 1970s.[54]
Odyssey of the Mind World Finals[55] is the pinnacle international team-based creative problem-solving competition, and an annual festival to celebrate creativity education. Odyssey of the Mind helps educators easily implement 21st Century Learning Skills[56] at every learning level, and has been sponsored by NASA to encourage
creativity education in the United States.[57]
1.8 Intelligence
There has been debate in the psychological literature
about whether intelligence (as measured by IQ) and creativity are part of the same process (the conjoint hypothesis) or represent distinct mental processes (the disjoint
hypothesis). Evidence from attempts to look at correlations between intelligence and creativity from the 1950s
onwards, by authors such as Barron, Guilford or Wallach
and Kogan, regularly suggested that correlations between
these concepts were low enough to justify treating them
as distinct concepts.[51]
Some researchers believe that creativity is the outcome
of the same cognitive processes as intelligence, and is
only judged as creativity in terms of its consequences, i.e.
when the outcome of cognitive processes happens to produce something novel, a view which Perkins has termed
the “nothing special” hypothesis.[58]
An often cited model is what has come to be known as
“the threshold hypothesis,” proposed by Ellis Paul Tor-
7
rance, which holds that a high degree of intelligence
appears to be a necessary but not sufficient condition
for high creativity.[34] That is, while there is a positive
correlation between creativity and intelligence, this correlation disappears for IQs above a threshold of around
120. Such a model has found acceptance by many researchers, although it has not gone unchallenged.[59] A
study in 1962 by Getzels and Jackson among high school
students concluded that high IQ and high creativity tend
to be mutually exclusive with a majority of the highest
scoring students being either highly creative or highly intelligent, but not both. While this explains the threshold,
the exact interaction between creativity and IQ remains
unexplained.[60] A 2005 meta-Analysis found only small
correlations between IQ and creativity tests and did not
support the threshold theory.[61]
An alternative perspective, Renzulli’s three-rings hypothesis, sees giftedness as based on both intelligence and creativity.
Many experts have suggested a relationship between associative memory and creativity.[62][63][64]
1.9 Neurobiology
The neurobiology of creativity has been addressed[65] in
the article “Creative Innovation: Possible Brain Mechanisms.” The authors write that “creative innovation might
require coactivation and communication between regions
of the brain that ordinarily are not strongly connected.”
Highly creative people who excel at creative innovation
tend to differ from others in three ways:
• they have a high level of specialized knowledge,
• they are capable of divergent thinking mediated by
the frontal lobe.
• and they are able to modulate neurotransmitters such
as norepinephrine in their frontal lobe.
Thus, the frontal lobe appears to be the part of the cortex
that is most important for creativity.
This article also explored the links between creativity and
sleep, mood and addiction disorders, and depression.
In 2005, Alice Flaherty presented a three-factor model
of the creative drive. Drawing from evidence in brain
imaging, drug studies and lesion analysis, she described
the creative drive as resulting from an interaction of the
frontal lobes, the temporal lobes, and dopamine from the
limbic system. The frontal lobes can be seen as responsible for idea generation, and the temporal lobes for idea
editing and evaluation. Abnormalities in the frontal lobe
(such as depression or anxiety) generally decrease creativity, while abnormalities in the temporal lobe often increase creativity. High activity in the temporal lobe typically inhibits activity in the frontal lobe, and vice versa.
8
High dopamine levels increase general arousal and goal itself. Further, Vandervert and Vandervert-Weathers bedirected behaviors and reduce latent inhibition, and all lieve that this repetitive “mental prototyping” or mental
three effects increase the drive to generate ideas.[66]
rehearsal involving the cerebellum and the cerebral cortex explains the success of the self-driven, individualized
patterning of repetitions initiated by the teaching meth1.9.1 Working memory and the cerebellum ods of the Khan Academy. The model proposed by Vandervert has however received incisive critique from sevVandervert[67] described how the brain’s frontal lobes eral authors.[79][80]
and the cognitive functions of the cerebellum collaborate to produce creativity and innovation. Vandervert’s
explanation rests on considerable evidence that all pro- 1.9.2 REM sleep
cesses of working memory (responsible for processing
all thought[68] ) are adaptively modeled for increased efCreativity involves the forming of associative elements
ficiency by the cerebellum.[69] The cerebellum (consistinto new combinations that are useful or meet some reing of 100 billion neurons, which is more than the enquirement. Sleep aids this process.[81] REM rather than
tirety of the rest of the brain[70] ) is also widely known to
NREM sleep appears to be responsible.[82][83] This has
adaptively model all bodily movement for efficiency. The
been suggested to be due to changes in cholinergic and
cerebellum’s adaptive models of working memory pronoradrenergic neuromodulation that occurs during REM
cessing are then fed back to especially frontal lobe work[82]
sleep.
During this period of sleep, high levels of acetyling memory control processes[71] where creative and incholine
in
the hippocampus suppress feedback from the
novative thoughts arise.[72] (Apparently, creative insight
hippocampus to the neocortex, and lower levels of acetylor the “aha” experience is then triggered in the temporal
choline and norepinephrine in the neocortex encourage
lobe.[73] )
the spread of associational activity within neocortical arAccording to Vandervert, the details of creative adapta- eas without control from the hippocampus.[84] This is in
tion begin in “forward” cerebellar models which are antic- contrast to waking consciousness, where higher levels of
ipatory/exploratory controls for movement and thought. norepinephrine and acetylcholine inhibit recurrent conThese cerebellar processing and control architectures nections in the neocortex. It is proposed that REM sleep
have been termed Hierarchical Modular Selection and adds creativity by allowing “neocortical structures to reorIdentification for Control (HMOSAIC).[74] New, hierar- ganize associative hierarchies, in which information from
chically arranged levels of the cerebellar control architec- the hippocampus would be reinterpreted in relation to
ture (HMOSAIC) develop as mental mulling in working previous semantic representations or nodes.”[82]
memory is extended over time. These new levels of the
control architecture are fed forward to the frontal lobes.
Since the cerebellum adaptively models all movement and
1.10 Affect
all levels of thought and emotion,[75] Vandervert’s approach helps explain creativity and innovation in sports,
art, music, the design of video games, technology, math- Some theories suggest that creativity may be particularly
susceptible to affective influence. As noted in voting beematics, the child prodigy, and thought in general.
havior the term “affect” in this context can refer to liking
Essentially, Vandervert has argued that when a person is
or disliking key aspects of the subject in question. This
confronted with a challenging new situation, visual-spatial
work largely follows from findings in psychology regardworking memory and speech-related working memory
ing the ways in which affective states are involved in huare decomposed and re-composed (fractionated) by the
man judgment and decision-making.[85]
cerebellum and then blended in the cerebral cortex in an
attempt to deal with the new situation. With repeated
attempts to deal with challenging situations, the cerebro1.10.1 Positive affect relations
cerebellar blending process continues to optimize the efficiency of how working memory deals with the situation or problem.[76] Most recently, he has argued that this According to Alice Isen, positive affect has three primary
is the same process (only involving visual-spatial work- effects on cognitive activity:
ing memory and pre-language vocalization) that led to
the evolution of language in humans.[77] Vandervert and
1. Positive affect makes additional cognitive material
Vandervert-Weathers have pointed out that this blendavailable for processing, increasing the number of
ing process, because it continuously optimizes efficiencognitive elements available for association;
cies, constantly improves prototyping attempts toward
2. Positive affect leads to defocused attention and
the invention or innovation of new ideas, music, art, or
a more complex cognitive context, increasing the
technology.[78] Prototyping, they argue, not only produces new products, it trains the cerebro-cerebellar pathbreadth of those elements that are treated as releways involved to become more efficient at prototyping
vant to the problem;
1.11. FORMAL THEORY
3. Positive affect increases cognitive flexibility, increasing the probability that diverse cognitive elements will in fact become associated. Together,
these processes lead positive affect to have a positive influence on creativity.
9
In general, affective events provoke immediate and relatively fleeting emotional reactions. Thus, if creative performance at work is an affective event for the individual
doing the creative work, such an effect would likely be
evident only in same-day data.
Another longitudinal research found several insights regarding the relations between creativity and emotion at
work. Firstly, evidence shows a positive correlation between positive affect and creativity. The more positive a
person’s affect on a given day, the more creative thinking they evidenced that day and the next day—even conAccording to these researchers, positive emotions introlling for that next day’s mood. There was even some
crease the number of cognitive elements available for asevidence of an effect two days later.
sociation (attention scope) and the number of elements
In addition, the researchers found no evidence that people
that are relevant to the problem (cognitive scope).
were more creative when they experienced both positive
Various meta-analyses, such as Baas et al. (2008) of 66
and negative affect on the same day. The weight of evistudies about creativity and affect support the link bedence supports a purely linear form of the affect-creativity
tween creativity and positive affect[86][87]
relationship, at least over the range of affect and creativity
covered in our study: the more positive a person’s affect,
the higher their creativity in a work setting.
Barbara Fredrickson in her broaden-and-build model suggests that positive emotions such as joy and love broaden
a person’s available repertoire of cognitions and actions,
thus enhancing creativity.
1.10.2
Negative affect relations
On the other hand, some theorists have suggested that
negative affect leads to greater creativity. A cornerstone
of this perspective is empirical evidence of a relationship between affective illness and creativity. In a study
of 1,005 prominent 20th century individuals from over
45 different professions, the University of Kentucky’s
Arnold Ludwig found a slight but significant correlation
between depression and level of creative achievement. In
addition, several systematic studies of highly creative individuals and their relatives have uncovered a higher incidence of affective disorders (primarily bipolar disorder
and depression) than that found in the general population.
1.10.3
Affect at work
Three patterns may exist between affect and creativity at
work: positive (or negative) mood, or change in mood,
predictably precedes creativity; creativity predictably precedes mood; and whether affect and creativity occur simultaneously.
It was found that not only might affect precede creativity, but creative outcomes might provoke affect as well.
At its simplest level, the experience of creativity is itself
a work event, and like other events in the organizational
context, it could evoke emotion. Qualitative research and
anecdotal accounts of creative achievement in the arts and
sciences suggest that creative insight is often followed by
feelings of elation. For example, Albert Einstein called
his 1907 general theory of relativity “the happiest thought
of my life.” Empirical evidence on this matter is still very
tentative.
In contrast to the possible incubation effects of affective
state on subsequent creativity, the affective consequences
of creativity are likely to be more direct and immediate.
Finally, they found four patterns of affect and creativity:
affect can operate as an antecedent to creativity; as a direct consequence of creativity; as an indirect consequence
of creativity; and affect can occur simultaneously with
creative activity. Thus, it appears that people’s feelings
and creative cognitions are interwoven in several distinct
ways within the complex fabric of their daily work lives.
1.11 Formal theory
Jürgen Schmidhuber's formal theory of creativity[88][89]
postulates that creativity, curiosity and interestingness
are by-products of a simple computational principle for
measuring and optimizing learning progress. Consider
an agent able to manipulate its environment and thus its
own sensory inputs. The agent can use a black box optimization method such as reinforcement learning to learn
(through informed trial and error) sequences of actions
that maximize the expected sum of its future reward signals. There are extrinsic reward signals for achieving externally given goals, such as finding food when hungry.
But Schmidhuber’s objective function to be maximized
also includes an additional, intrinsic term to model “woweffects.” This non-standard term motivates purely creative
behavior of the agent even when there are no external
goals. A wow-effect is formally defined as follows. As
the agent is creating and predicting and encoding the continually growing history of actions and sensory inputs,
it keeps improving the predictor or encoder, which can
be implemented as an artificial neural network or some
other machine learning device that can exploit regularities in the data to improve its performance over time. The
improvements can be measured precisely, by computing
the difference in computational costs (storage size, number of required synapses, errors, time) needed to encode
10
new observations before and after learning. This difference depends on the encoder’s present subjective knowledge, which changes over time, but the theory formally
takes this into account. The cost difference measures the
strength of the present “wow-effect” due to sudden improvements in data compression or computational speed.
It becomes an intrinsic reward signal for the action selector. The objective function thus motivates the action
optimizer to create action sequences causing more woweffects. Irregular, random data (or noise) do not permit
any wow-effects or learning progress, and thus are “boring” by nature (providing no reward). Already known
and predictable regularities also are boring. Temporarily
interesting are only the initially unknown, novel, regular
patterns in both actions and observations. This motivates
the agent to perform continual, open-ended, active, creative exploration.
According to Schmidhuber, his objective function explains the activities of scientists, artists and
comedians.[90][91] For example, physicists are motivated
to create experiments leading to observations obeying
previously unpublished physical laws permitting better
data compression. Likewise, composers receive intrinsic
reward for creating non-arbitrary melodies with unexpected but regular harmonies that permit wow-effects
through data compression improvements. Similarly, a
comedian gets intrinsic reward for “inventing a novel
joke with an unexpected punch line, related to the beginning of the story in an initially unexpected but quickly
learnable way that also allows for better compression of
the perceived data.”[92] Schmidhuber argues that that
ongoing computer hardware advances will greatly scale
up rudimentary artificial scientists and artists based on
simple implementations of the basic principle since
1990.[93] He used the theory to create low-complexity
art[94] and an attractive human face.[95]
1.12 Mental health
Main article: Creativity and mental illness
A study by psychologist J. Philippe Rushton found creativity to correlate with intelligence and psychoticism.[96]
Another study found creativity to be greater in
schizotypal than in either normal or schizophrenic
individuals. While divergent thinking was associated
with bilateral activation of the prefrontal cortex, schizotypal individuals were found to have much greater
activation of their right prefrontal cortex.[97] This study
hypothesizes that such individuals are better at accessing
both hemispheres, allowing them to make novel associations at a faster rate. In agreement with this hypothesis,
ambidexterity is also associated with schizotypal and
schizophrenic individuals. Three recent studies by Mark
Batey and Adrian Furnham have demonstrated the
relationships between schizotypal[98][99] and hypomanic
personality
creativity.
[100]
and several different measures of
Particularly strong links have been identified between creativity and mood disorders, particularly manic-depressive
disorder (a.k.a. bipolar disorder) and depressive disorder
(a.k.a. unipolar disorder). In Touched with Fire: ManicDepressive Illness and the Artistic Temperament, Kay Redfield Jamison summarizes studies of mood-disorder rates
in writers, poets and artists. She also explores research that identifies mood disorders in such famous writers and artists as Ernest Hemingway (who shot himself after electroconvulsive treatment), Virginia Woolf
(who drowned herself when she felt a depressive episode
coming on), composer Robert Schumann (who died in
a mental institution), and even the famed visual artist
Michelangelo.
A study looking at 300,000 persons with schizophrenia,
bipolar disorder or unipolar depression, and their relatives, found overrepresentation in creative professions for
those with bipolar disorder as well as for undiagnosed
siblings of those with schizophrenia or bipolar disorder.
There was no overall overrepresenation, but overrepresentation for artistic occupations, among those diagnosed
with schizophrenia. There was no association for those
with unipolar depression or their relatives. [101]
Another study involving more than one million people,
conducted by Swedish researchers at the Karolinska Institute, reported a number of correlations between creative occupations and mental illnesses. Writers had a
higher risk of anxiety and bipolar disorders, schizophrenia, unipolar depression, and substance abuse, and were
almost twice as likely as the general population to kill
themselves. Dancers and photographers were also more
likely to have bipolar disorder.[102]
However, as a group, those in the creative professions
were no more likely to suffer from psychiatric disorders
than other people, although they were more likely to have
a close relative with a disorder, including anorexia and, to
some extent, autism, the Journal of Psychiatric Research
reports.[102]
According to psychologist Robert Epstein, PhD, creativity can be obstructed through stress.[103]
1.13 Some types of creativity according to R.J. Sternberg
An article by R. J. Sternberg in the Creativity Research
Journal reviewed the “investment” theory of creativity as
well as the “propulsion” theory of creative contribution,
suggesting that there are eight types of creative contribution; replication — confirming that the given field is in
the correct place — redefinition — the attempt to redefine where the field is and how it is viewed — forward
incrementation — a creative contribution that moves the
1.14. IN VARIOUS CONTEXTS
11
field forward in the direction in which it is already mov- four primary creativity traits with narrow facets within
ing — advance forward movement — which advances the each
field past the point where others are ready for it to go —
redirection — which moves the field in a new, different
(i) “Idea Generation” (Fluency, Originality, Indirection — redirection from a point in the past — which
cubation and Illumination)
moves the field back to a previous point to advance in a
(ii) “Personality” (Curiosity and Tolerance for
different direction — starting over/ re-initiation — movAmbiguity)
ing the field to a different starting point — and integration
(iii) “Motivation” (Intrinsic, Extrinsic and
— combining two or more diverse ways of thinking about
Achievement)
the field into a single way of thinking.[104]
(iv) “Confidence” (Producing, Sharing and Implementing)
1.14 In various contexts
This model was developed in a sample of 1000 working
adults using the statistical techniques of Exploratory Factor Analysis followed by Confirmatory Factor Analysis by
Structural Equation Modelling.[106]
An important aspect of the creativity profiling approach
is to account for the tension between predicting the creative profile of an individual, as characterised by the
psychometric approach, and the evidence that team creativity is founded on diversity and difference.[107]
One characteristic of creative people, as measured by
some psychologists, is what is called divergent production. divergent production is the ability of a person to
generate a diverse assortment, yet an appropriate amount
[108]
One way of meaAn electric wire reel reused as a center table in a Rio de Janeiro of responses to a given situation.
decoration fair. The creativity of this designer in reusing this suring divergent production is by administering the Torrance Tests of Creative Thinking.[109] The Torrance Tests
waste was used with good effects to the environment.
of Creative Thinking assesses the diversity, quantity, and
Creativity has been studied from a variety of perspectives appropriateness of participants responses to a variety of
and is important in numerous contexts. Most of these open-ended questions.
approaches are undisciplinary, and it is therefore difficult Other researchers of creativity see the difference in creto form a coherent overall view.[21] The following sections ative people as a cognitive process of dedication to probexamine some of the areas in which creativity is seen as lem solving and developing expertise in the field of their
being important.
creative expression. Hard working people study the work
of people before them and within their current area, become experts in their fields, and then have the ability to
1.14.1 Creativity profiles
add to and build upon previous information in innovative
and creative ways. In a study of projects by design stuCreativity can be expresses in a number of different
dents, students who had more knowledge on their subject
forms, depending on the unique people and environments
on average had greater creativity within their projects.[110]
it exists. A number of different theorists have suggested
models of the creative person. One model suggests that The aspect of motivation within a person’s personality
there are kinds to produce growth, innovation, speed, etc. may predict creativity levels in the person. Motivation
These are referred to as the four “Creativity Profiles” that stems from two different sources, intrinsic and extrinsic motivation. Intrinsic motivation is an internal drive
can help achieve such goals.[105]
within a person to participate or invest as a result of personal interest, desires, hopes, goals, etc. Extrinsic mo(i) Incubate (Long-term Development)
tivation is a drive from outside of a person and might
(ii) Imagine (Breakthrough Ideas)
take the form of payment, rewards, fame, approval from
(iii) Improve (Incremental Adjustments)
others, etc. Although extrinsic motivation and intrinsic
motivation can both increase creativity in certain cases,
(iv) Invest (Short-term Goals)
strictly extrinsic motivation often impedes creativity in
[111]
Research by Dr Mark Batey of the Psychometrics at people.
Work Research Group at Manchester Business School has From a personality-traits perspective, there are a number
suggested that the creative profile can be explained by of traits that are associated with creativity in people.[112]
12
Creative people tend to be more open to new experiences, are more self-confident, are more ambitious, selfaccepting, impulsive, driven, dominant, and hostile, compared to people with less creativity.
From an evolutionary perspective, creativity may be a result of the outcome of years of generating ideas. As ideas
are continuously generated, the need to evolve produces a
need for new ideas and developments. As a result, people
have been creating and developing new, innovative, and
creative ideas to build our progress as a society.[113]
that the lack of an equivalent word for 'creativity' may affect the views of creativity among speakers of such languages. However, more research would be needed to establish this, and there is certainly no suggestion that this
linguistic difference makes people any less (or more) creative; Africa has a rich heritage of creative pursuits such
as music, art, and storytelling. Nevertheless, it is true
that there has been very little research on creativity in
Africa,[119] and there has also been very little research
on creativity in Latin America.[120] Creativity has been
more thoroughly researched in the northern hemisphere,
but here again there are cultural differences, even between countries or groups of countries in close proximity. For example, in Scandinavian countries, creativity
is seen as an individual attitude which helps in coping
with life’s challenges,[121] while in Germany, creativity is
seen more as a process that can be applied to help solve
problems.[122]
In studying exceptionally creative people in history, some
common traits in lifestyle and environment are often
found. Creative people in history usually had supportive
parents, but rigid and non-nurturing. Most had an interest
in their field at an early age, and most had a highly supportive and skilled mentor in their field of interest. Often the field they chose was relatively uncharted, allowing
for their creativity to be expressed more in a field with
less previous information. Most exceptionally creative
people devoted almost all of their time and energy into 1.14.3
their craft, and after about a decade had a creative breakthrough of fame. Their lives were marked with extreme
dedication and a cycle of hard-work and breakthroughs
as a result of their determination [114]
Another theory of creative people is the investment theory of creativity. This approach suggest that there are
many individual and environmental factors that must exist in precise ways for extremelly high levels of creativity opposed to average levels of creativity. In the investment sense, a person with their particular characteristics
in their particular environment may see an opportunity
to devote their time and energy into something that has
been overlooked by others. The creative person develops
an undervalued or underrecognized idea to the point that
it is established as a new and creative idea. Just like in
the financial world, some investments are worth the buy
in, while others are less productive and do not build to the
extent that the investor expected. This investment theory
of creativity views creativity in a unique perspective compared to others, by asserting that creativity might rely to
some extent on the right investment of effort being added
to a field at the right time in the right way.[115]
In art and literature
Henry Moore's Reclining Figure
Most people associate creativity with the fields of art
and literature. In these fields, originality is considered to be a sufficient condition for creativity, unlike
other fields where both originality and appropriateness are
necessary.[123]
Within the different modes of artistic expression, one can
postulate a continuum extending from "interpretation" to
“innovation”. Established artistic movements and genres
pull practitioners to the “interpretation” end of the scale,
whereas original thinkers strive towards the “innovation”
pole. Note that we conventionally expect some “creative”
1.14.2 In diverse cultures
people (dancers, actors, orchestral members, etc.) to perform (interpret) while allowing others (writers, painters,
[116]
Creativity is viewed differently in different countries.
For example, cross-cultural research centred on Hong composers, etc.) more freedom to express the new and
Kong found that Westerners view creativity more in terms the different.
of the individual attributes of a creative person, such as Contrast alternative theories, for example:
their aesthetic taste, while Chinese people view creativity more in terms of the social influence of creative peo• artistic inspiration, which provides the transmission
ple e.g. what they can contribute to society.[117] Mpofu
of visions from divine sources such as the Muses; a
et al. surveyed 28 African languages and found that 27
taste of the Divine.[124] Compare with invention.
had no word which directly translated to 'creativity' (the
• artistic evolution, which stresses obeying established
exception being Arabic).[118] The principle of linguistic
relativity, i.e. that language can affect thought, suggests
(“classical”) rules and imitating or appropriating to
1.14. IN VARIOUS CONTEXTS
13
produce subtly different but unshockingly under- ... manifest themselves only through their ability to orgastandable work. Compare with crafts.
nize images and ideas, and this is always an unconscious
process which cannot be detected until afterwards.”[134]
• artistic conversation, as in Surrealism, which
stresses the depth of communication when the cre1.14.5 Creative industries and services
ative product is the language.
In the art practice and theory of Davor Dzalto, human
creativity is taken as a basic feature of both the personal
existence of human being and art production. For this
thinker, creativity is a basic cultural and anthropological category, since it enables human manifestation in the
world as a “real presence” in contrast to the progressive
“virtualization” of the world.
1.14.4
Today, creativity forms the core activity of a growing
section of the global economy—the so-called "creative
industries"—capitalistically generating (generally nontangible) wealth through the creation and exploitation of
intellectual property or through the provision of creative
services. The Creative Industries Mapping Document
2001 provides an overview of the creative industries in
the UK. The creative professional workforce is becoming
a more integral part of industrialized nations’ economies.
Psychological examples from sci- Creative professions include writing, art, design, theater,
television, radio, motion pictures, related crafts, as well
ence and mathematics
Jacques Hadamard, in his book Psychology of Invention
in the Mathematical Field, uses introspection to describe
mathematical thought processes. In contrast to authors
who identify language and cognition, he describes his own
mathematical thinking as largely wordless, often accompanied by mental images that represent the entire solution
to a problem. He surveyed 100 of the leading physicists
of his day (ca. 1900), asking them how they did their
work. Many of the responses mirrored his own.
as marketing, strategy, some aspects of scientific research
and development, product development, some types of
teaching and curriculum design, and more. Since many
creative professionals (actors and writers, for example)
are also employed in secondary professions, estimates of
creative professionals are often inaccurate. By some estimates, approximately 10 million US workers are creative
professionals; depending upon the depth and breadth of
the definition, this estimate may be double.
Hadamard described the experiences of the 1.14.6
mathematicians/theoretical physicists Carl Friedrich
Gauss, Hermann von Helmholtz, Henri Poincaré
and others as viewing entire solutions with “sudden
spontaneity.”[125]
In other professions
The same has been reported in literature by many others, such as Denis Brian,[126] G. H. Hardy,[127] Walter
Heitler,[128] B. L. van der Waerden,[129] and Harold
Ruegg.[130]
To elaborate on one example, Einstein, after years of
fruitless calculations, suddenly had the solution to the
general theory of relativity revealed in a dream “like a
giant die making an indelible impress, a huge map of the
universe outlined itself in one clear vision.”[126]
Hadamard described the process as having steps (i)
preparation, (ii) incubation, (iv) illumination, and (v) verification of the five-step Graham Wallas creative-process
model, leaving out (iii) intimation, with the first three
cited by Hadamard as also having been put forth by
Helmholtz:[131]
Marie-Louise von Franz, a colleague of the eminent psychiatrist Carl Jung, noted that in these unconscious scientific discoveries the “always recurring and important
factor ... is the simultaneity with which the complete solution is intuitively perceived and which can be checked
later by discursive reasoning.” She attributes the solution
presented “as an archetypal pattern or image.”[132] As
cited by von Franz,[133] according to Jung, “Archetypes
Isaac Newton's law of gravity is popularly attributed to a creative
leap he experienced when observing a falling apple.
Creativity is also seen as being increasingly important in a
variety of other professions. Architecture and industrial
design are the fields most often associated with creativity, and more generally the fields of design and design research. These fields explicitly value creativity, and journals such as Design Studies have published many studies
on creativity and creative problem solving.[135]
Fields such as science and engineering have, by contrast,
experienced a less explicit (but arguably no less important) relation to creativity. Simonton[18] shows how some
of the major scientific advances of the 20th century can
14
be attributed to the creativity of individuals. This ability
• and Motivation (especially intrinsic motivation).
will also be seen as increasingly important for engineers
in years to come.[136]
There are two types of motivation:
Accounting has also been associated with creativity with
• extrinsic motivation – external factors, for example
the popular euphemism creative accounting. Although
threats of being fired or money as a reward,
this term often implies unethical practices, Amabile[123]
has suggested that even this profession can benefit from
• intrinsic motivation – comes from inside an individthe (ethical) application of creative thinking.
ual, satisfaction, enjoyment of work etc.
In a recent global survey of approximately 1600 CEO’s,
the leadership trait that was considered to be most cruSix managerial practices to encourage motivation are:
cial for success was creativity.[137] This suggests that the
world of business is beginning to accept that creativity
• Challenge – matching people with the right assignis of value in a diversity of industries, rather than bements;
ing simply the preserve of the creative industries. For
instance, the civil service (opularly derided as wholly op• Freedom – giving people autonomy choosing means
posite to the creative), has benefitted from employing creto achieve goals;
ative writers, from John Milton, to Anthony Trollope, to
• Resources – such as time, money, space etc. There
'Flann O'Brien', who are capable of analysing the workmust be balance fit among resources and people;
ings of their own institutions.[138]
1.14.7
In organizations
• Work group features – diverse, supportive teams,
where members share the excitement, willingness to
help and recognize each other’s talents;
• Supervisory encouragement – recognitions, cheering, praising;
• Organizational support – value emphasis, information sharing, collaboration.
Nonaka, who examined several successful Japanese companies, similarly saw creativity and knowledge creation
as being important to the success of organizations.[139] In
particular, he emphasized the role that tacit knowledge
has to play in the creative process.
In business, originality is not enough. The idea must also
be appropriate—useful and actionable.[140][141] Creative
Training meeting in an eco-design stainless steel company in
Brazil. The leaders among other things wish to cheer and encour- competitive intelligence is a new solution to solve this
problem. According to Reijo Siltala it links creativity
age the workers in order to achieve a higher level of creativity.
to innovation process and competitive intelligence to creIt has been the topic of various research studies to es- ative workers.
tablish that organizational effectiveness depends on the Creativity can be encouraged in people and professionals
creativity of the workforce to a large extent. For any and in the workplace. It is essential for innovation, and
given organization, measures of effectiveness vary, de- is a factor affecting economic growth and businesses. In
pending upon its mission, environmental context, nature 2013 the sociologist Silvia Leal Martín, using the Innova
of work, the product or service it produces, and customer 3DX method, suggested measuring the various paramedemands. Thus, the first step in evaluating organizational ters that encourage creativity and innovation: corporate
effectiveness is to understand the organization itself — culture, work environment, leadership and management,
how it functions, how it is structured, and what it empha- creativity, self-esteem and optimism, locus of control and
sizes.
learning orientation, motivation and fear.[142]
Amabile[123] argued that to enhance creativity in business,
three components were needed:
1.14.8 Economic views of creativity
• Expertise (technical, procedural and intellectual
Economic approaches to creativity have focussed on three
knowledge),
aspects — the impact of creativity on economic growth,
• Creative thinking skills (how flexibly and imagina- methods of modelling markets for creativity, and the
tively people approach problems),
maximisation of economic creativity (innovation).
1.15. FOSTERING CREATIVITY
In the early 20th century, Joseph Schumpeter introduced the economic theory of creative destruction, to describe the way in which old ways of doing things are endogenously destroyed and replaced by the new. Some
economists (such as Paul Romer) view creativity as an important element in the recombination of elements to produce new technologies and products and, consequently,
economic growth. Creativity leads to capital, and creative
products are protected by intellectual property laws.
Mark A. Runco and Daniel Rubenson have tried to describe a "psychoeconomic" model of creativity.[143] In
such a model, creativity is the product of endowments and
active investments in creativity; the costs and benefits of
bringing creative activity to market determine the supply
of creativity. Such an approach has been criticised for
its view of creativity consumption as always having positive utility, and for the way it analyses the value of future
innovations.[144]
The creative class is seen by some to be an important
driver of modern economies. In his 2002 book, The Rise
of the Creative Class, economist Richard Florida popularized the notion that regions with “3 T’s of economic development: Technology, Talent and Tolerance” also have
high concentrations of creative professionals and tend to
have a higher level of economic development.
The creative industries in Europe — including the audiovisual sector — make a significant contribution to the EU
economy, creating about 3% of EU GDP — corresponding to an annual market value of €500 billion — and employing about 6 million people. In addition, the sector
plays a crucial role in fostering innovation, in particular
for devices and networks.[145] The EU records the second
highest TV viewing figures globally, producing more films
than any other region in the world. In that respect, the
newly proposed 'Creative Europe' programme will help
preserve cultural heritage while increasing the circulation of creative works inside and outside the EU.[146] The
programme will play a consequential role in stimulating
cross border co-operation, promoting peer learning and
making these sectors more professional. The Commission will then propose a financial instrument run by the
European Investment Bank to provide debt and equity finance for cultural and creative industries. The role of the
non-state actors within the governance regarding Medias
will not be neglected anymore due to a holistic approach.
1.14.9
Social network view of creativity
Creativity research has long been polarized between the
‘romantic’ view that major creative achievements are
sparked by imaginative and uniquely gifted individuals
at the margin of an intellectual field. Although this remains the dominant approach when examining individual creativity, an increasingly large number of studies
have stressed the importance of also looking at social factors. Following this line of thought and drawing more ex-
15
plicitly from research by sociologists and sociopsychologists, organizational scholars have increasingly recognized the importance of the network side of individual
creativity.[147]
The key idea of this perspective is that a deeper understanding of how creative outputs are generated and become accepted can be achieved only by placing the individual within a network of interpersonal relationships.
The influence of the social context in which individuals
are embedded determines the range of information and
opportunities available to them during the creative process. Several studies have begun to expose the network
mechanisms that underlie the genesis and legitimacy of
creative work.[148]
1.15 Fostering creativity
Main article: Creativity techniques
Daniel Pink, in his 2005 book A Whole New Mind, repeating arguments posed throughout the 20th century, argues that we are entering a new age where creativity is becoming increasingly important. In this conceptual age, we
will need to foster and encourage right-directed thinking
(representing creativity and emotion) over left-directed
thinking (representing logical, analytical thought). However, this simplification of 'right' versus 'left' brain thinking is not supported by the research data.[149]
Nickerson[150] provides a summary of the various creativity techniques that have been proposed. These include
approaches that have been developed by both academia
and industry:
1. Establishing purpose and intention
2. Building basic skills
3. Encouraging acquisitions of domain-specific knowledge
4. Stimulating and rewarding curiosity and exploration
5. Building motivation, especially internal motivation
6. Encouraging confidence and a willingness to take
risks
7. Focusing on mastery and self-competition
8. Promoting supportable beliefs about creativity
9. Providing opportunities for choice and discovery
10. Developing self-management (metacognitive skills)
11. Teaching techniques and strategies for facilitating
creative performance
12. Providing balance
16
Some see the conventional system of schooling as “stifling” of creativity and attempt (particularly in the preschool/kindergarten and early school years) to provide
a creativity-friendly, rich, imagination-fostering environment for young children.[150][151][152] Researchers have
seen this as important because technology is advancing
our society at an unprecedented rate and creative problem
solving will be needed to cope with these challenges as
they arise.[152] In addition to helping with problem solving, creativity also helps students identify problems where
others have failed to do so.[150][151][153] See the Waldorf
School as an example of an education program that promotes creative thought.
Promoting intrinsic motivation and problem solving are
two areas where educators can foster creativity in students. Students are more creative when they see
a task as intrinsically motivating, valued for its own
sake.[151][152][154][155] To promote creative thinking educators need to identify what motivates their students
and structure teaching around it. Providing students with
a choice of activities to complete allows them to become more intrinsically motivated and therefore creative
in completing the tasks.[150][156]
ity rather than the prevailing individual one. Creativity
Research on Global Virtual Teams is showing that the
creative process is affected by the national identities, cognitive and conative profiles, anonymous interactions at
times and many other factors affecting the teams members, depending on the early or later stages of the cooperative creative process. They are also showing how
NGO’s cross-cultural virtual team’s innovation in Africa
would also benefit from the pooling of best global practices online. Such tools enhancing cooperative creativity
may have a great impact on society and as such should be
tested while they are built following the Motto: “Build the
Camera while shooting the film”. Some European FP7
scientific programs like Paradiso are answering a need for
advanced experimentally driven research including largescale experimentation test-beds to discover the technical,
societal and economic implications of such groupware
and collaborative tools to the Internet.
On the other hand, creativity research may one day be
pooled with a computable metalanguage like IEML from
the University of Ottawa Collective Intelligence Chair,
Pierre Levy. It might be a good tool to provide an interdisciplinary definition and a rather unified theory of
creativity. The creative processes being highly fuzzy, the
programming of cooperative tools for creativity and innovation should be adaptive and flexible. Empirical Modelling seems to be a good choice for Humanities Computing.
Teaching students to solve problems that do not have well
defined answers is another way to foster their creativity. This is accomplished by allowing students to explore
problems and redefine them, possibly drawing on knowledge that at first may seem unrelated to the problem in
order to solve it.[150][151][152][154]
If all the activity of the universe could be traced with apSeveral different researchers have proposed methods of propriate captors, it is likely that one could see the creincreasing the creativity of an individual. Such ideas ative nature of the universe to which humans are active
range from the psychological-cognitive, such as Osborn- contributors. After the web of documents, the Web of
Parnes Creative Problem Solving Process, Synectics, Things might shed some light on such a universal creative
Science-based creative thinking, Purdue Creative Think- phenomenon which should not be restricted to humans. In
ing Program, and Edward de Bono's lateral thinking; order to trace and enhance cooperative and collective creto the highly structured, such as TRIZ (the Theory of ativity, Metis Reflexive Global Virtual Team has worked
Inventive Problem-Solving) and its variant Algorithm for the last few years on the development of a Trace Comof Inventive Problem Solving (developed by the Rus- poser at the intersection of personal experience and social
sian scientist Genrich Altshuller), and Computer-Aided knowledge.
Morphological analysis.
1.16 Understanding and enhancing
the creative process with new
technologies
A simple but accurate review on this new HumanComputer Interactions (HCI) angle for promoting creativity has been written by Todd Lubart, an invitation full
of creative ideas to develop further this new field.
Metis Reflexive Team has also identified a paradigm for
the study of creativity to bridge European theory of “useless” and non-instrumentalized creativity, North American more pragmatic creativity and Chinese culture stressing more creativity as a holistic process of continuity
rather than radical change and originality. This paradigm
is mostly based on the work of the German philosopher
Hans Joas, one that emphasizes the creative character of
human action. This model allows also for a more comprehensive theory of action. Joas elaborates some implications of his model for theories of social movements and
social change. The connection between concepts like creation, innovation, production and expression is facilitated
by the creativity of action as a metaphore but also as a
scientific concept.
Groupware and other Computer Supported Collaborative
Work (CSCW) platforms are now the stage of Network
Creativity on the web or on other private networks. These The Creativity and Cognition conference series, spontools have made more obvious the existence of a more sored by the ACM and running since 1993, has been an
connective, cooperative and collective nature of creativ-
1.19. NOTES
important venue for publishing research on the intersection between technology and creativity. The conference
now runs biennially, next taking place in 2011.
17
• Multiple discovery
• Music therapy
• Musical improvisation
1.17 Social attitudes
Although the benefits of creativity to society as a whole
have been noted,[157] social attitudes about this topic remain divided. The wealth of literature regarding the development of creativity[158] and the profusion of creativity
techniques indicate wide acceptance, at least among academics, that creativity is desirable.
There is, however, a dark side to creativity, in that it represents a “quest for a radical autonomy apart from the
constraints of social responsibility”.[159] In other words,
by encouraging creativity we are encouraging a departure
from society’s existing norms and values. Expectation of
conformity runs contrary to the spirit of creativity. Ken
Robinson argues that the current education system is “educating people out of their creativity”. [160][161]
Nevertheless, employers are increasingly valuing creative
skills. A report by the Business Council of Australia,
for example, has called for a higher level of creativity in
graduates.[162] The ability to "think outside the box" is
highly sought after. However, the above-mentioned paradox may well imply that firms pay lip service to thinking
outside the box while maintaining traditional, hierarchical organization structures in which individual creativity
is condemned.
1.18 See also
• Adaptive performance
• Brainstorming
• Computational creativity
• Confabulation (neural networks)
• Why Man Creates (film)
1.19 Notes
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[8] “And eke Job saith, that in hell is no order of rule. And
albeit that God hath created all things in right order, and
nothing without order, but all things be ordered and numbered, yet nevertheless they that be damned be not in order, nor hold no order.”
[9] Władysław Tatarkiewicz, A History of Six Ideas: an Essay
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[146] http://www.ec.europa.eu/culture/news/news3311_en.
1.20 References
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22
• Amabile, T. M. (1998). “How to kill creativity”.
Harvard Business Review 76 (5).
• Helmholtz, H. v. L. (1896). Vorträge und Reden
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• Amabile, T. M. (1996). Creativity in context. Westview Press.
• Isen A. M., Daubman K. A., Nowicki G. P. (1987).
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• BCA (2006). New Concepts in Innovation: The Keys
to a Growing Australia. Business Council of Australia.
• Brian, Denis, Einstein: A Life (John Wiley and Sons,
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• Byrne, R. M. J. (2005). The Rational Imagination: How People Create Counterfactual Alternatives
to Reality. MIT Press.
• Carson, S. H.; Peterson, J. B.; Higgins, D.
M. (2005). “Reliability, Validity, and Factor
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• Craft, A. (2005). Creativity in Schools: tensions and
dilemmas. Routledge. ISBN 0-415-32414-9.
• Dorst, K.; Cross, N. (2001).
“Creativity in
the design process: co-evolution of problem–
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• Feldman, D. H. (1999). “The Development of Creativity”. In ed. Sternberg, R.J. Handbook of Creativity. Cambridge University Press.
• Finke, R.; Ward, T. B. & Smith, S. M. (1992). Creative cognition: Theory, research, and applications.
MIT Press. ISBN 0-262-06150-3.
• Flaherty, A. W. (2005). “Frontotemporal and
dopaminergic control of idea generation and creative drive”. Journal of Comparative Neurology
493 (1): 147–153. doi:10.1002/cne.20768. PMC
2571074. PMID 16254989.
• Florida, R. (2002). The Rise of the Creative Class:
And How It’s Transforming Work, Leisure, Community and Everyday Life. Basic Books. ISBN 0-46502476-9.
• Fredrickson B. L. (2001). “The role of positive
emotions in positive psychology: The broadenand-build theory of positive emotions”. American
Psychologist 56 (3): 218–26. doi:10.1037/0003066X.56.3.218. PMC 3122271. PMID 11315248.
• Hadamard, Jacques, The Psychology of Invention in
the Mathematical Field (Dover, 1954) ISBN 0-48620107-4
• Jeffery, G. (2005). The Creative College: building
a successful learning culture in the arts. Trentham
Books.
• Johnson, D. M. (1972). Systematic introduction to
the psychology of thinking. Harper & Row.
• Jullien, F.; Paula M. Varsano (translator) (2004).
In Praise of Blandness: Proceeding from Chinese
Thought and Aesthetics. Zone Books, U.S. ISBN 1890951-41-2; ISBN 978-1-890951-41-2
• Jung, C. G., The Collected Works of C. G. Jung. Volume 8. The Structure and Dynamics of the Psyche.
(Princeton, 1981) ISBN 0-691-09774-7
• Kanigel, Robert, The Man Who Knew Infinity: A
Life of the Genius Ramanujan (Washington Square
Press, 1992) ISBN 0-671-75061-5
• Kraft, U. (2005). “Unleashing Creativity”. Scientific
American Mind. April: 16–23.
• Kolp, P., Lammé, A., Regnard, Fr., Rens, J. M.
(ed.) (2009). “Musique et créativité". Orphée
Apprenti (Conseil de la Musique) NS (1): 9–119.
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• *Lehrer, Jonah (2012), Imagine: How Creativity
Works.
• McLaren, R. B. (1999). “Dark Side of Creativity”.
In ed. Runco, M. A. & Pritzker, S. R. Encyclopedia
of Creativity. Academic Press.
• McCrae, R. R. (1987). “Creativity, Divergent
Thinking, and Openness to Experience”. Journal
of Personality and Social Psychology 52 (6): 1258–
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• Michalko, M. (1998). Cracking Creativity: The
Secrets of Creative Genius. Berkeley, Calif.: Ten
Speed Press. ISBN 0-89815-913-X.
• Nachmanovitch, Stephen (1990). Free Play: Improvisation in Life and Art. Penguin-Putnam. ISBN
0-87477-578-7.
• National Academy of Engineering (2005). Educating the engineer of 2020: adapting engineering
education to the new century. National Academies
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• Nonaka, I. (1991). “The Knowledge-Creating Company”. Harvard Business Review 69 (6): 96–104.
1.20. REFERENCES
• O'Hara, L. A. & Sternberg, R. J. (1999). “Creativity
and Intelligence”. In ed. Sternberg, R. J. Handbook
of Creativity. Cambridge University Press.
• Pink, D. H. (2005). A Whole New Mind: Moving
from the information age into the conceptual age.
Allen & Unwin.
• Poincaré, H. (1908/1952). “Mathematical creation”. In ed. Ghiselin, B. The Creative Process: A
Symposium. Mentor. Check date values in: |date=
(help)
• Rhodes, M. (1961). “An analysis of creativity”. Phi
Delta Kappan 42: 305–311.
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• Miller E., Cohen J. (2001). “An integrative
theory of prefrontal cortex function”.
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• Miyake, A., & Shah, P. (Eds.). (1999). Models
of working memory: Mechanisms of active maintenance and executive control. New York: Cambridge
University Press.
• Schmahmann, J. (Ed.). (1997). The cerebellum and
cognition. New York: Academic Press.
• Rushton, J. P. (1990). “Creativity, intelligence,
and psychoticism”. Personality and Individual
Differences 11: 1291–1298. doi:10.1016/01918869(90)90156-L.
• Schmahmann J (2004). “Disorders of the cerebellum: Ataxia, dysmetria of thought, and the cerebellar cognitive affective syndrome”. Journal of
Neuropsychiatry and Clinical Neuroscience 16: 367–
378. doi:10.1176/appi.neuropsych.16.3.367.
• Runco, M. A. (2004).
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• Sullivan, Ceri and Graeme Harper, ed., The Creative
Environment: Authors at Work (Cambridge: English
Association/Boydell and Brewer, 2009)
• Sabaneev, Leonid. The Psychology of the MusicoCreative Process // Psyche. - Vol. 9 (July 1928). pp. 37–54.
• Vandervert, L. (2003a). How working memory and
cognitive modeling functions of the cerebellum contribute to discoveries in mathematics. New Ideas in
Psychology, 21, 159-175.
• Smith, S. M. & Blakenship, S.E. (1 April 1991).
“Incubation and the persistence of fixation in problem solving”. American Journal of Psychology 104
(1): 61–87. doi:10.2307/1422851. ISSN 00029556. JSTOR 1422851. PMID 2058758.
• Taylor, C. W. (1988). “Various approaches to and
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The nature of creativity: Contemporary psychological perspectives. Cambridge University Press.
• Torrance, E. P. (1974). Torrance Tests of Creative
Thinking. Personnel Press.
• von Franz, Marie-Louise, Psyche and Matter
(Shambhala, 1992) ISBN 0-87773-902-1
• Andersen B., Korbo L., Pakkenberg B. (1992).
“A quantitative study of the human cerebellum
with unbiased stereological techniques”. The Journal of Comparative Neurology 326 (4): 549–560.
doi:10.1002/cne.903260405. PMID 1484123.
• Imamizu H., Kuroda T., Miyauchi S., Yoshioka T.,
Kawato M. (2003). “Modular organization of internal models of tools in the cerebellum”. Proceedings
of the National Academy of Sciences 100 (9): 5461–
5466. doi:10.1073/pnas.0835746100.
• Jung-Beeman, M., Bowden, E., Haberman, J.,
Frymiare, J., Arambel-Liu, S., Greenblatt, R., Reber, P., & Kounios, J. (2004). Neural activity when
people solve verbal problems with insight. PLOS
Biology, 2, 500-510.
• Vandervert, L. (2003b). The neurophysiological basis of innovation. In L. V. Shavinina (Ed.) The
international handbook on innovation (pp. 17–30).
Oxford, England: Elsevier Science.
• Vandervert, L. (2011). The evolution of language:
The cerebro-cerebellar blending of visual-spatial
working memory with vocalizations. The Journal of
Mind and Behavior, 32, 317-334.
• Vandervert, L. (in press). How the blending of cerebellar internal models can explain the evolution of
thought and language. Cerebellum.
• Vandervert, L., Schimpf, P., & Liu, H. (2007). How
working memory and the cerebellum collaborate to
produce creativity and innovation [Special Issue].
Creativity Research Journal, 19(1), 1-19.
• Vandervert, L., & Vandervert-Weathers, K. (in
press). New brain-imaging studies indicate how prototyping is related to entrepreneurial giftedness and
innovation education in children. In L. Shavinina
(Ed.), The International Handbook of Innovation
Education. London: Routlage.
• DeGraff, J.; Lawrence, K. (2002). Creativity at
Work. Jossey-Bass. ISBN 0-7879-5725-9.
• Gielen, P. (2013). Creativity and other Fundamentalisms. Mondriaan: Amsterdam.
24
1.21 Further reading
• Chung-yuan, Chang (1970). Creativity and Taoism,
A Study of Chinese Philosophy, Art, and Poetry. New
York: Harper Torchbooks. ISBN 0-06-131968-6.
• Cropley, David H.; Cropley, Arthur J.; Kaufman,
James C. et al., eds. (2010). The Dark Side
of Creativity. Cambridge: Cambridge University
Press. ISBN 978-0-521-13960-1. Lay summary
(24 November 2010).
• Robinson, Andrew (2010). Sudden Genius?: The
Gradual Path to Creative Breakthroughs. Oxford:
Oxford University Press. ISBN 978-0-19-9569953. Lay summary (24 November 2010).
• The Roots of Human Genius Are Deeper Than Expected March 10, 2013 Scientific American
1.22 External links
Videos
• John Cleese:
2012.03.23
On How to Foster Creativity,
• Raphael DiLuzio: 7 Steps of Creative Thinking,
2012.06.28
Articles
• Isaac Asimov: On How to Cultivate Creativity,
2014.10.20
Chapter 2
Computational creativity
Computational creativity (also known as artificial creativity, mechanical creativity or creative computation) is a multidisciplinary endeavour that is located at
the intersection of the fields of artificial intelligence,
cognitive psychology, philosophy, and the arts.
of the system or that of the system’s programmer or
designer?
• How do we evaluate computational creativity? What
counts as creativity in a computational system? Are
natural language generation systems creative? Are
machine translation systems creative? What distinguishes research in computational creativity from research in artificial intelligence generally?
The goal of computational creativity is to model, simulate
or replicate creativity using a computer, to achieve one of
several ends:
• If eminent creativity is about rule-breaking or the
disavowal of convention, how is it possible for an
algorithmic system to be creative? In essence, this
is a variant of the Ada Lovelace's objection to machine intelligence, as recapitulated by modern theorists such as Teresa Amabile:[1] If a machine can
do only what it was programmed to do, how can its
behavior ever be called creative?
• To construct a program or computer capable of
human-level creativity.
• To better understand human creativity and to formulate an algorithmic perspective on creative behavior
in humans.
• To design programs that can enhance human creativity without necessarily being creative themselves.
Indeed, not all computer theorists would agree with the
The field of computational creativity concerns itself with premise that computers can only do what they are protheoretical and practical issues in the study of creativ- grammed to do[2] —a key point in favor of computational
ity. Theoretical work on the nature and proper definition creativity.
of creativity is performed in parallel with practical work
on the implementation of systems that exhibit creativity,
with one strand of work informing the other.
2.2 Defining creativity in computa-
tional terms
2.1 Theoretical issues
As measured by the amount of activity in the field (e.g.,
publications, conferences and workshops), computational
creativity is a growing area of research. But the field is
still hampered by a number of fundamental problems.
Creativity is very difficult, perhaps even impossible, to
define in objective terms. Is it a state of mind, a talent
or ability, or a process? Creativity takes many forms in
human activity, some eminent (sometimes referred to as
“Creativity” with a capital C) and some mundane.
Since no single perspective or definition seems to offer a
complete picture of creativity, the AI researchers Newell,
Shaw and Simon[3] developed the combination of novelty
and usefulness into the cornerstone of a multi-pronged
view of creativity, one that uses the following four criteria
to categorize a given answer or solution as creative:
These are problems that complicate the study of creativity
in general, but certain problems attach themselves specifically to computational creativity:
• Can creativity be hard-wired? In existing systems
to which creativity is attributed, is the creativity that
25
1. The answer is novel and useful (either for the individual or for society)
2. The answer demands that we reject ideas we had
previously accepted
3. The answer results from intense motivation and persistence
4. The answer comes from clarifying a problem that
was originally vague
26
Whereas the above reflects a “top-down” approach to
computational creativity, an alternative thread has developed among “bottom-up” computational psychologists
involved in artificial neural network research. During the
late 1980s and early 1990s, for example, such generative
neural systems were driven by genetic algorithms.[4] Experiments involving recurrent nets[5] were successful in
hybridizing simple musical melodies and predicting listener expectations.
CHAPTER 2. COMPUTATIONAL CREATIVITY
2.4.1 Important categories of creativity
Margaret Boden[15][16] refers to creativity that is novel
merely to the agent that produces it as “P-creativity” (or
“psychological creativity”), and refers to creativity that is
recognized as novel by society at large as “H-creativity”
(or “historical creativity”). Stephen Thaler has suggested
a new category he calls “V-" or “Visceral creativity”
wherein significance is invented to raw sensory inputs
to a Creativity Machine architecture, with the “gateway” nets perturbed to produce alternative interpretations, and downstream nets shifting such interpretations
to fit the overarching context. An important variety of
such V-creativity is consciousness itself, wherein meaning is reflexively invented to activation turnover within
the brain[17]
Concurrent with such research, a number of computational psychologists took the perspective, popularized by
Stephen Wolfram, that system behaviors perceived as
complex, including the mind’s creative output, could arise
from what would be considered simple algorithms. As
neuro-philosophical thinking matured, it also became evident that language actually presented an obstacle to producing a scientific model of cognition, creative or not,
since it carried with it so many unscientific aggrandizements that were more uplifting than accurate. Thus ques- 2.4.2 Exploratory and transformational
creativity
tions naturally arose as to how “rich,” “complex,” and
“wonderful” creative cognition actually was.[6]
Boden also distinguishes between the creativity that arises
from an exploration within an established conceptual
space, and the creativity that arises from a deliberate
transformation or transcendence of this space. She labels the former as exploratory creativity and the latter as
2.3 Artificial Neural Networks
transformational creativity, seeing the latter as a form of
creativity far more radical, challenging, and rarer than the
Before 1989, artificial neural networks have been used former. Following the criteria from Newell and Simon
to model certain aspects of creativity. Peter Todd elaborated above, we can see that both forms of creativity
(1989) first trained a neural network to reproduce musi- should produce results that are appreciably novel and usecal melodies from a training set of musical pieces. Then ful (criterion 1), but exploratory creativity is more likely
he used a change algorithm to modify the network’s in- to arise from a thorough and persistent search of a wellput parameters. The network was able to randomly gen- understood space (criterion 3) -- while transformational
erate new music in a highly uncontrolled manner.[7][8][9] creativity should involve the rejection of some of the conIn 1992, Todd[10] extended this work, using the so- straints that define this space (criterion 2) or some of the
called distal teacher approach that had been developed by assumptions that define the problem itself (criterion 4).
Paul Munro,[11] Paul Werbos,[12] D. Nguyen and Bernard Boden’s insights have guided work in computational creWidrow,[13] Michael I. Jordan and David Rumelhart.[14] ativity at a very general level, providing more an inspiraIn the new approach there are two neural networks, one tional touchstone for development work than a technical
of which is supplying training patterns to another. In framework of algorithmic substance. However, Boden’s
later efforts by Todd, a composer would select a set of insights are more recently also the subject of formalizamelodies that define the melody space, position them on a tion, most notably in the work by Geraint Wiggins.[18]
2-d plane with a mouse-based graphic interface, and train
a connectionist network to produce those melodies, and
listen to the new “interpolated” melodies that the network 2.4.3 Generation and evaluation
generates corresponding to intermediate points in the 2-d
plane.
The criterion that creative products should be novel and
useful means that creative computational systems are typically structured into two phases, generation and evaluation. In the first phase, novel (to the system itself,
thus P-Creative) constructs are generated; unoriginal con2.4 Key concepts from the litera- structs that are already known to the system are filtered
at this stage. This body of potentially creative constructs
ture
are then evaluated, to determine which are meaningful
and useful and which are not. This two-phase structure
Some high-level and philosophical themes recur through- conforms to the Geneplore model of Finke, Ward and
out the field of computational creativity.
Smith,[19] which is a psychological model of creative gen-
2.5. LINGUISTIC CREATIVITY
27
eration based on empirical observation of human creativ- into mental spaces and conceptual metaphors. Their basic
ity.
model defines an integration network as four connected
spaces:
2.4.4
Combinatorial creativity
A great deal, perhaps all, of human creativity can be understood as a novel combination of pre-existing ideas or
objects. Common strategies for combinatorial creativity
include:
• Placing a familiar object in an unfamiliar setting
(e.g., Marcel Duchamp's Fountain) or an unfamiliar
object in a familiar setting (e.g., a fish-out-of-water
story such as The Beverly Hillbillies)
• Blending two superficially different objects or genres (e.g., a sci-fi story set in the Wild West, with
robot cowboys, as in Westworld, or the reverse, as
in Firefly; Japanese haiku poems, etc.)
• A first input space (contains one conceptual structure or mental space)
• A second input space (to be blended with the first
input)
• A generic space of stock conventions and imageschemas that allow the input spaces to be understood
from an integrated perspective
• A blend space in which a selected projection of elements from both input spaces are combined; inferences arising from this combination also reside here,
sometimes leading to emergent structures that conflict with the inputs.
• Comparing a familiar object to a superficially
unrelated and semantically distant concept (e.g., Fauconnier and Turner describe a collection of optimal“Makeup is the Western burka"; “A zoo is a gallery ity principles that are claimed to guide the construction of
a well-formed integration network. In essence, they see
with living exhibits”)
blending as a compression mechanism in which two or
• Adding a new and unexpected feature to an exist- more input structures are compressed into a single blend
ing concept (e.g., adding a scalpel to a Swiss Army structure. This compression operates on the level of conknife; adding a camera to a mobile phone)
ceptual relations. For example, a series of similarity relations between the input spaces can be compressed into
• Compressing two incongruous scenarios into the
a single identity relationship in the blend.
same narrative to get a joke (e.g., the Emo Philips
joke “Women are always using me to advance their Some computational success has been achieved with
the blending model by extending pre-existing compucareers. Damned anthropologists!”)
tational models of analogical mapping that are com• Using an iconic image from one domain in a domain patible by virtue of their emphasis on connected sefor an unrelated or incongruous idea or product (e.g., mantic structures.[24] More recently, Francisco Câmara
using the Marlboro Man image to sell cars, or to ad- Pereira[25] presented an implementation of blending thevertise the dangers of smoking-related impotence). ory that employs ideas both from GOFAI and genetic algorithms to realize some aspects of blending theory in
The combinatorial perspective allows us to model cre- a practical form; his example domains range from the
ativity as a search process through the space of possible linguistic to the visual, and the latter most notably incombinations. The combinations can arise from com- cludes the creation of mythical monsters by combining
position or concatenation of different representations, or 3-D graphical models.
through a rule-based or stochastic transformation of initial and intermediate representations. Genetic algorithms
and neural networks can be used to generate blended or
crossover representations that capture a combination of 2.5 Linguistic creativity
different inputs.
Language provides continuous opportunity for creativity, evident in the generation of novel sentences, phrasConceptual blending
ings, puns, neologisms, rhymes, allusions, sarcasm, irony,
similes, metaphors, analogies, witticisms, and jokes. NaMain article: Conceptual blending
tive speakers of morphologically rich languages (including all Slavic languages) frequently create new wordMark Turner and Gilles Fauconnier[20][21] propose a forms that are easily understood, although they will never
model called Conceptual Integration Networks that elab- find their way to the dictionary. The area of natural lanorates upon Arthur Koestler's ideas about creativity[22] guage generation has been well studied, but these creative
as well as more recent work by Lakoff and Johnson,[23] aspects of everyday language have yet to be incorporated
by synthesizing ideas from Cognitive Linguistic research with any robustness or scale.
28
2.5.1
Story generation
being key to the generation of novel analogies. The dominant school of research, as advanced by Dedre Gentner,
views analogy as a structure-preserving process; this view
has been implemented in the structure mapping engine
or SME,[34] the MAC/FAC retrieval engine (Many Are
Called, Few Are Chosen), ACME (Analogical Constraint
Mapping Engine) and ARCS (Analogical Retrieval Constraint System). Other mapping-based approaches include Sapper,[24] which situates the mapping process in
a semantic-network model of memory. Analogy is a
very active sub-area of creative computation and creative
cognition; active figures in this sub-area include Douglas
Hofstadter, Paul Thagard, and Keith Holyoak. Also worthy of note here is Peter Turney and Michael Littman’s
machine learning approach to the solving of SAT-style
analogy problems; their approach achieves a score that
compares well with average scores achieved by humans
on these tests.
Substantial work has been conducted in this area of linguistic creation since the 1970s, with the development of
James Meehan’s TALE-SPIN [26] system. TALE-SPIN
viewed stories as narrative descriptions of a problemsolving effort, and created stories by first establishing
a goal for the story’s characters so that their search
for a solution could be tracked and recorded. The
MINSTREL[27] system represents a complex elaboration of this basis approach, distinguishing a range of
character-level goals in the story from a range of authorlevel goals for the story. Systems like Bringsjord’s
BRUTUS[28] elaborate these ideas further to create stories with complex inter-personal themes like betrayal.
Nonetheless, MINSTREL explicitly models the creative
process with a set of Transform Recall Adapt Methods (TRAMs) to create novel scenes from old. The
MEXICA[29] model of Rafael Pérez y Pérez and Mike
Sharples is more explicitly interested in the creative process of storytelling, and implements a version of the 2.5.4 Joke generation
engagement-reflection cognitive model of creative writing.
Main article: Computational humor
The company Narrative Science makes computer generated news and reports commercially available, including summarizing team sporting events based on statistical
data from the game. It also creates financial reports and
real estate analyses.[30]
2.5.2
Metaphor and simile
Example of a metaphor: “She was an ape.”
Example of a simile: “Felt like a tiger-fur blanket."
The computational study of these phenomena has mainly
focused on interpretation as a knowledge-based process. Computationalists such as Yorick Wilks, James
Martin,[31] Dan Fass, John Barnden,[32] and Mark Lee
have developed knowledge-based approaches to the processing of metaphors, either at a linguistic level or a logical level. Tony Veale and Yanfen Hao have developed a
system, called Sardonicus, that acquires a comprehensive
database of explicit similes from the web; these similes
are then tagged as bona-fide (e.g., “as hard as steel”) or
ironic (e.g., “as hairy as a bowling ball", “as pleasant as
a root canal"); similes of either type can be retrieved on
demand for any given adjective. They use these similes as the basis of an on-line metaphor generation system
called Aristotle[33] that can suggest lexical metaphors for
a given descriptive goal (e.g., to describe a supermodel
as skinny, the source terms “pencil”, “whip”, “whippet”,
“rope”, “stick-insect” and “snake” are suggested).
Humour is an especially knowledge-hungry process, and
the most successful joke-generation systems to date have
focussed on pun-generation, as exemplified by the work
of Kim Binsted and Graeme Ritchie.[35] This work includes the JAPE system, which can generate a wide range
of puns that are consistently evaluated as novel and humorous by young children. An improved version of
JAPE has been developed in the guise of the STANDUP
system, which has been experimentally deployed as a
means of enhancing linguistic interaction with children
with communication disabilities. Some limited progress
has been made in generating humour that involves other
aspects of natural language, such as the deliberate misunderstanding of pronominal reference (in the work of
Hans Wim Tinholt and Anton Nijholt), as well as in the
generation of humorous acronyms in the HAHAcronym
system[36] of Oliviero Stock and Carlo Strapparava.
2.5.5 Neologisms
The blending of multiple word forms is a dominant force
for new word creation in language; these new words are
commonly called “blends” or "portmanteau words" (after Lewis Carroll). Tony Veale has developed a system
called ZeitGeist[37] that harvests neological headwords
from Wikipedia and interprets them relative to their local
context in Wikipedia and relative to specific word senses
in WordNet. ZeitGeist has been extended to generate
neologisms of its own; the approach combines elements
from an inventory of word parts that are harvested from
2.5.3 Analogy
WordNet, and simultaneously determines likely glosses
The process of analogical reasoning has been studied for these new words (e.g., “food traveller” for “gastrofrom both a mapping and a retrieval perspective, the latter naut” and “time traveller” for "chrononaut"). It then uses
2.7. VISUAL AND ARTISTIC CREATIVITY
Web search to determine which glosses are meaningful
and which neologisms have not been used before; this
search identifies the subset of generated words that are
both novel (“H-creative”) and useful. Neurolinguistic inspirations have been used to analyze the process of novel
word creation in the brain,[38] understand neurocognitive
processes responsible for intuition, insight, imagination
and creativity[39] and to create a server that invents novel
names for products, based on their description.[40] Further, the system Nehovah[41] blends two source words into
a neologism that blends the meanings of the two source
words. Nehovah searches WordNet [42] for synonyms and
TheTopTens.com to search for pop culture hyponyms.
The synonyms and hyponyms are blended together to create a set of candidate neologisms. The neologisms are
then scored based on their word structure, how unique
the word is, how apparent the concepts are conveyed, and
if the neologism has a pop culture reference. Nehovah
loosely follows conceptual blending. It can be accessed
at http://axon.cs.byu.edu/~{}nehovah.
2.5.6
Poetry
29
is capable of analyzing and generalizing from existing
music by a human composer to generate novel musical
compositions in the same style. EMI’s output is convincing enough to persuade human listeners that its music is
human-generated to a high level of competence.[46]
In the field of contemporary classical music, Iamus is
the first computer that composes from scratch, and produces final scores that professional interpreters can play.
The London Symphony Orchestra played a piece for full
orchestra, included in Iamus’ debut CD,[47] which New
Scientist described as “The first major work composed
by a computer and performed by a full orchestra.”.[48]
Melomics, the technology behind Iamus, is able to generate pieces in different styles of music with a similar level
of quality.
Creativity research in jazz has focused on the process of
improvisation and the cognitive demands that this places
on a musical agent: reasoning about time, remembering
and conceptualizing what has already been played, and
planning ahead for what might be played next. The robot
Shimon, developed by Gil Weinberg of Georgia Tech, has
demonstrated jazz improvisation.[49]
In 1994, a Creativity Machine architecture (see above)
was able to generate 11,000 musical hooks by training
a synaptically perturbed neural net on 100 melodies that
had appeared on the top ten list over the last 30 years. In
1996, a self-bootstrapping Creativity Machine observed
audience facial expressions through an advanced machine
Is Half Constructed
vision system and perfected its musical talents to generate
[50]
Like jokes, poems involve a complex interaction of dif- an album entitled “Song of the Neurons”
ferent constraints, and no general-purpose poem gener- In the field of musical composition, the patented works[51]
ator adequately combines the meaning, phrasing, struc- by René-Louis Baron allowed to make a robot that can
ture and rhyme aspects of poetry. Nonetheless, Pablo create and play a multitude of orchestrated melodies soGervás[43] has developed a noteworthy system called AS- called “coherent” in any musical style. All outdoor physPERA that employs a case-based reasoning (CBR) ap- ical parameter associated with one or more specific muproach to generating poetic formulations of a given input sical parameters, can influence and develop each of these
text via a composition of poetic fragments that are re- songs (in real time while listening to the song). The
trieved from a case-base of existing poems. Each poem patented invention Medal-Composer raises problems of
fragment in the ASPERA case-base is annotated with a copyright.
prose string that expresses the meaning of the fragment,
and this prose string is used as the retrieval key for each
fragment. Metrical rules are then used to combine these 2.7 Visual and artistic creativity
fragments into a well-formed poetic structure. Racter is
an example of such a software project.
Computational creativity in the generation of visual
art has had some notable successes in the creation of
both abstract art and representational art. The most
famous program in this domain is Harold Cohen's
2.6 Musical creativity
AARON,[52] which has been continuously developed and
Computational creativity in the music domain has fo- augmented since 1973. Though formulaic, Aaron excused both on the generation of musical scores for use hibits a range of outputs, generating black-and-white
by human musicians, and on the generation of music for drawings or colour paintings that incorporate human figperformance by computers. The domain of generation ures (such as dancers), potted plants, rocks, and other elhas included classical music (with software that generates ements of background imagery. These images are of a
music in the style of Mozart and Bach) and jazz. Most no- sufficiently high quality to be displayed in reputable galtably, David Cope[44] has written a software system called leries.
More than iron, more than lead, more than gold I need
electricity.
I need it more than I need lamb or pork or lettuce or cucumber.
I need it for my dreams. Racter, from The Policeman’s Beard
“Experiments in Musical Intelligence” (or “EMI”)[45] that Other software artists of note include the NEvAr system
30
(for “Neuro-Evolutionary Art”) of Penousal Machado.[53]
NEvAr uses a genetic algorithm to derive a mathematical
function that is then used to generate a coloured threedimensional surface. A human user is allowed to select
the best pictures after each phase of the genetic algorithm, and these preferences are used to guide successive
phases, thereby pushing NEvAr’s search into pockets of
the search space that are considered most appealing to the
user.
The Painting Fool, developed by Simon Colton originated as a system for overpainting digital images of a
given scene in a choice of different painting styles, colour
palettes and brush types. Given its dependence on an
input source image to work with, the earliest iterations
of the Painting Fool raised questions about the extent
of, or lack of, creativity in a computational art system.
Nonetheless, in more recent work, The Painting Fool has
been extended to create novel images, much as AARON
does, from its own limited imagination. Images in this
vein include cityscapes and forests, which are generated
by a process of constraint satisfaction from some basic
scenarios provided by the user (e.g., these scenarios allow
the system to infer that objects closer to the viewing plane
should be larger and more color-saturated, while those
further away should be less saturated and appear smaller).
Artistically, the images now created by the Painting Fool
appear on a par with those created by Aaron, though
the extensible mechanisms employed by the former (constraint satisfaction, etc.) may well allow it to develop into
a more elaborate and sophisticated painter.
2.8 Creativity in problem solving
Creativity is also useful in allowing for unusual solutions
in problem solving. In psychology and cognitive science, this research area is called creative problem solving.
The Explicit-Implicit Interaction (EII) theory of creativity has recently been implemented using a CLARIONbased computational model that allows for the simulation
of incubation and insight in problem solving.[57] The emphasis of this computational creativity project is not on
performance per se (as in artificial intelligence projects)
but rather on the explanation of the psychological processes leading to human creativity and the reproduction
of data collected in psychology experiments. So far, this
project has been successful in providing an explanation
for incubation effects in simple memory experiments, insight in problem solving, and reproducing the overshadowing effect in problem solving.
2.9 Debate about “general” theories of creativity
Some researchers feel that creativity is a complex phenomenon whose study is further complicated by the plasticity of the language we use to describe it. We can describe not just the agent of creativity as “creative” but
also the product and the method. Consequently, it could
be claimed that it is unrealistic to speak of a general theThe artist Krasimira Dimtchevska and the software devel- ory of creativity given the amorphousness of the concept,
oper Svillen Ranev have created a computational system the plasticity of the language, and the tendency of our
combining a rule-based generator of English sentences cultural perspectives on the concept to evolve over time.
and a visual composition builder that converts sentences Nonetheless, some generative principles are more gengenerated by the system into abstract art.[54] The software eral than others, leading some advocates to claim that
generates automatically indefinite number of different certain computational approaches are “general theories”.
images using different color, shape and size palettes. The Stephen Thaler, for instance, proposes that certain modalsoftware also allows the user to select the subject of the ities of neural networks are generative enough, and gengenerated sentences or/and the one or more of the palettes eral enough, to manifest a high degree of creative capabilused by the visual composition builder.
ities. Likewise, the Formal Theory of Creativity[58][59] is
An emerging area of computational creativity is that of
video games. ANGELINA is a system for creatively developing video games in Java by Michael Cook. One important aspect is Mechanic Miner, a system which can
generate short segments of code which act as simple game
mechanics.[55] ANGELINA can evaluate these mechanics for usefulness by playing simple unsolvable game levels and testing to see if the new mechanic makes the level
solvable. Sometimes Mechanic Miner discovers bugs in
the code and exploits these to make new mechanics for
the player to solve problems with.[56]
based on a simple computational principle published by
Jürgen Schmidhuber in 1991.[60] The theory postulates
that creativity and curiosity and selective attention in general are by-products of a simple algorithmic principle for
measuring and optimizing learning progress.
Popular wisdom claims that creativity is a rich and complex phenomenon, made richer and more complex by the
fact that we can talk about it in so many ways, technologically, culturally, socially and historically. Accordingly,
most think it makes little sense to claim any computational theory to be a general theory of creativity. They
would say, with great confidence, that a single generative mechanism, and a related mechanism for evaluating
and filtering the outputs of generation, does not a general
theory make, no matter how rich the outputs. They may
cede that such theories could be a valuable contribution
to the field, but likewise contend that computationalists
2.10. EVENTS
31
must strive to synthesize the many different aspects of based upon the success or failure of self-conceived concreativity, the many different modes of generation and cepts and strategies seeded upon such internal network
evaluation, to arrive at a framework that will one day be damage.[78]
considered general.
Of course others in the field do not hold these opinions,
claiming that what was once perceived as amorphous has
now crystallized into a comprehensive theory.
2.9.1
Stephen L. Thaler’s work on a unified
model of creativity
A unifying model of creativity[61] was proposed by S.
L. Thaler through a series of international patents in
computational creativity, beginning in 1997 with the issuance of U.S. Patent 5,659,666.[62] Based upon theoretical studies of traumatized neural networks and inspired
by studies of damage-induced vibrational modes in simulated crystal lattices,[63] this extensive intellectual property suite taught the application of a broad range of noise,
damage, and disordering effects to a trained neural network so as to drive the formation of novel or confabulatory patterns[64][65][66][67] that could potentially qualify as
ideas and/or plans of action.
Thaler’s scientific and philosophical papers both preceding and following the issuance of these patents described:
1. The aspects of creativity accompanying a broad
gamut of cognitive functions (e.g., waking to dreaming to near-death trauma),[68][69][70]
2.10 Events
The International Conference on Computational Creativity occurs annually. The most recent conference was June
12–14, 2013 in Sydney, Australia. Previous conferences
have been in Dublin, Ireland (2012), Mexico City, Mexico (2011) and Lisbon, Portugal (2010). Previously, the
community of computational creativity has held a dedicated workshop, the International Joint Workshop on
Computational Creativity, every year since 1999. Previous events in this series include:
• IJWCC 2003, Acapulco, Mexico, as part of IJCAI'2003
• IJWCC 2004, Madrid, Spain, as part of ECCBR'2004
• IJWCC 2005, Edinburgh, UK, as part of IJCAI'2005
• IJWCC 2006, Riva del Garda, Italy, as part of
ECAI'2006
• IJWCC 2007, London, UK, a stand-alone event
• IJWCC 2008, Madrid, Spain, a stand-alone event
2. A shorthand notation for describing creative neural
architectures and their function,[71]
The steering committee for these events comprises the
following researchers:
3. Quantitative modeling of the rhythm with which
creative cognition occurs,[61][72] and,
• Oliver Bown, University of Sydney, Australia
4. A prescription for critical perturbation regimes lead• Amílcar Cardoso, University of Coimbra, Portugal
ing to the most efficient generation of useful information by a creative neural system.[72][73]
• Simon Colton, Goldsmiths, University of London,
UK
Thaler has also recruited his generative neural architectures into a theory of consciousness that closely models
• Pablo Gervás, Universidad Complutense de Madrid,
the temporal evolution of thought, creative or not, while
Spain
also accounting for the subjective feel associated with this
• Kyle Jennings, University of California, Berkeley,
hotly debated mental phenomenon.[61][72][74][75][76][77]
USA
In 1989, in one of the most controversial reductions to
practice of this general theory of creativity,[61] one neu• Mary Lou Maher, University of North Carolina,
ral net termed the “grim reaper,” governed the synaptic
USA
damage (i.e., rule-changes) applied to another net that
• Nick Montfort, Massachusetts Institute of Technolhad learned a series of traditional Christmas carol lyrics.
ogy, USA
The former net, on the lookout for both novel and grammatical lyrics, seized upon the chilling sentence, “In the
• Alison Pease, University of Dundee, UK
end all men go to good earth in one eternal silent night,”
thereafter ceasing the synaptic degradation process. In
• Rafael Pérez y Pérez, Autonomous Metropolitan
subsequent projects, these systems produced more useUniversity, México
ful results across many fields of human endeavor, of• Graeme Ritchie, University of Aberdeen, UK
tentimes bootstrapping their learning from a blank slate
32
• Rob Saunders, University of Sydney, Australia
• Applications of artificial intelligence
• Dan Ventura, Brigham Young University, USA
• Artificial Architecture
• Tony Veale, University College, Dublin, Ireland
• Computer art
• Geraint A. Wiggins, Queen Mary, University of
London, UK
• Computer-generated music
2.11 Publications and Forums
A number of recent books provide either a good introduction or a good overview of the field of Computational
Creativity. These include:
• Creativity
• Digital morphogenesis
• Digital poetry
• Generative systems
• Musikalisches Würfelspiel (Musical dice game)
• Procedural generation
• Pereira, F. C. (2007). “Creativity and Artificial Intelligence: A Conceptual Blending Approach”. Ap- Lists
plications of Cognitive Linguistics series, Mouton
• List of emerging technologies
de Gruyter.
• Veale, T. (2012). “Exploding the Creativity Myth:
The Computational Foundations of Linguistic Creativity”. Bloomsbury Academic, London.
• McCormack, J. and d'Inverno, M. (eds.) (2012).
“Computers and Creativity”. Springer, Berlin.
• Veale, T., Feyaerts, K. and Forceville, C. (2013,
forthcoming). “Creativity and the Agile Mind:
A Multidisciplinary study of a Multifaceted phenomenon”. Mouton de Gruyter.
• Outline of artificial intelligence
2.13 References
[1] Amabile, Teresa (1983), The social psychology of creativity, New York, NY: Springer-Verlag
[2] Minsky, Marvin (1967), “Why programming is a good
medium for expressing poorly understood and sloppily
formulated ideas”, Design and Planning II-Computers in
Design and Communication, pp. 120–125
In addition to the proceedings of conferences and workshops, the computational creativity community has thus
far produced three special journal issues dedicated to the
topic:
[3] Newell, Allen, Shaw, J. G., and Simon, Herbert A. (1963),
The process of creative thinking, H. E. Gruber, G. Terrell
and M. Wertheimer (Eds.), Contemporary Approaches to
Creative Thinking, pp 63 – 119. New York: Atherton
• New Generation Computing, volume 24, issue 3,
2006
[4] Gibson, P. M. (1991) NEUROGEN, musical composition
using genetic algorithms and cooperating neural networks,
Second International Conference on Artificial Neural Networks: 309-313.
• Journal of Knowledge-Based Systems, volume 19, issue 7, November 2006
• AI Magazine, volume 30, number 3, Fall 2009
[5] Todd, P.M. (1989) A connectionist approach to algorithmic composition. Computer Music Journal, 13(4), 27-43.
• Minds and Machines, volume 20, number 4, November 2010
[6] Thaler, S. L. (1998). “The emerging intelligence and its
critical look at us,” Journal of Near-Death Studies, 17(1):
21-29.
• Cognitive Computation, volume 4, issue 3, September 2012
[7] Todd, P.M. (1989). A connectionist approach to algorithmic composition. Computer Music Journal, 13(4), 27-43.
• AIEDAM, volume 27, number 4, Fall 2013 (forthcoming)
[8] Bharucha, J.J., and Todd, P.M. (1989). Modeling the perception of tonal structure with neural nets. Computer Music Journal, 13(4), 44-53.
2.12 See also
• Algorithmic art
• Algorithmic composition
[9] Todd, P.M., and Loy, D.G. (Eds.) (1991). Music and
connectionism. Cambridge, MA: MIT Press.
[10] Todd, P.M. (1992). A connectionist system for exploring
melody space. In Proceedings of the 1992 International
Computer Music Conference (pp. 65-68). San Francisco:
International Computer Music Association.
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[14] Forward models: Supervised learning with a distal
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[15] Boden, Margaret (1990), The Creative Mind: Myths and
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[16] Boden, Margaret (1999), Computational models of creativity., Handbook of Creativity, pp 351–373
[17] Thaler, S. L. (2011, " The Creativity Machine Paradigm:
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Info/Newsletters/APAOnline/Publications/Newsletters/
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[18] Wiggins, Geraint (2006), A Preliminary Framework for
Description, Analysis and Comparison of Creative Systems,
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[19] Finke, R., Ward, T., and Smith, S. (1992), Creative cognition: Theory, research and applications, Cambridge: MIT
press.
[20] Fauconnier, Gilles, Turner, Mark (2007), The Way We
Think, Basic Books
[21] Fauconnier, Gilles, Turner, Mark (2007), Conceptual Integration Networks, Cognitive Science, 22(2) pp 133–187
[22] Koestler, Arthur (1964), {The act of creation}, London:
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[23] Lakoff, George; Johnson, Mark (2008), Metaphors we live
by, University of Chicago press
[24] Veale, Tony, O’Donoghue, Diarmuid (2007), Computation and Blending, Cognitive Linguistics, 11(3-4), special
issue on Conceptual Blending
[25] Pereira, Francisco Câmara (2006), Creativity and Artificial Intelligence: A Conceptual Blending Approach, Applications of Cognitive Linguistics. Amsterdam: Mouton de
Gruyter
[26] Meehan, James (1981), TALE-SPIN, Shank, R. C. and
Riesbeck, C. K., (eds.), Inside Computer Understanding:
Five Programs plus Miniatures. Hillsdale, NJ: Lawrence
Erlbaum Associates
[27] Turner, S.R. (1994), The Creative Process: A Computer
Model of Storytelling, Hillsdale, NJ: Lawrence Erlbaum
Associates
[28] Bringsjord, S., Ferrucci, D. A. (2000), Artificial Intelligence and Literary Creativity. Inside the Mind of BRUTUS,
a Storytelling Machine., Hillsdale NJ: Lawrence Erlbaum
Associates
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[29] Pérez y Pérez, Rafael, Sharples, Mike (2001), MEXICA: A
computer model of a cognitive account of creative writing,
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[30] http://www.narrativescience.com/solutions.html
[31] Martin, James (1990), A Computational Model of
Metaphor Interpretation, Academic Press
[32] Barnden, John (1992), Belief in Metaphor: Taking Commonsense Psychology Seriously, Computational Intelligence 8, pp 520-552
[33] Veale, Tony, Hao, Yanfen (2007), Comprehending and
Generating Apt Metaphors: A Web-driven, Case-based
Approach to Figurative Language, Proceedings of AAAI
2007, the 22nd AAAI Conference on Artificial Intelligence. Vancouver, Canada
[34] Falkenhainer, Brian, Forbus, Ken and Gentner, Dedre
(1989), The structure-mapping engine: Algorithm and examples, Artificial Intelligence, 20(41) pp 1–63
[35] Binsted, K., Pain, H., and Ritchie, G. (1997), Children’s
evaluation of computer-generated punning riddles, Pragmatics and Cognition, 5(2), pp 309–358
[36] Stock, Oliviero, Strapparava, Carlo (2003), HAHAcronym: Humorous agents for humorous acronyms,
Humor: International Journal of Humor Research, 16(3)
pp 297–314
[37] Veale, Tony (2006), Tracking the Lexical Zeitgeist with
Wikipedia and WordNet, Proceedings of ECAI’2006, the
17th European Conference on Artificial Intelligence
[38] Duch, Wlodzislaw (2007), Creativity and the Brain, In: A
Handbook of Creativity for Teachers. Ed. Ai-Girl Tan,
World Scientific Publishing, Singapore, pp 507–530
[39] Duch, Wlodzislaw (2007), Intuition, Insight, Imagination
and Creativity, IEEE Computational Intelligence Magazine, 2(3) pp 40–52
[40] Pilichowski Maciej, Duch Wlodzislaw (2007), Experiments with computational creativity, Neural Information
Processing – Letters and Reviews, 11(4-6) pp 123-133
[41] Smith, M. R., Hintze, R. S., and Ventura, D. (2014),
Nehovah: A Neologism Creator Nomen Ipsum, Proceedings of the International Conference on Computational
Creativity (ICCC 2014), pp 173-181
[42] WordNet, Princeton University., 2010 |first1= missing
|last1= in Authors list (help)
[43] Gervás, Pablo (2001), An expert system for the composition
of formal Spanish poetry, Journal of Knowledge-Based
Systems 14(3-4) pp 181–188
[44] Cope, David (2006), Computer Models of Musical Creativity, Cambridge, MA: MIT Press
[45] David Cope (1987), “Experiments in Music Intelligence.”
In Proceedings of the International Computer Music Conference, San Francisco: Computer Music Assn.
[46] Triumph of the Cyborg Composer
34
[47] Iamus’ debut CD, Melomics Records, 2012
[48] “Computer composer honours Turing’s centenary”. News
Scientist. 5 July 2012.
[49] http://www.npr.org/templates/story/story.php?storyId=
121763193
[50] http://www.emusic.com/listen/#/album/
machine-intelligence/song-of-the-neurons/11039062/
[51] (French) Article de presse : « Génération automatique
d'œuvres numériques », article sur l'invention Medal de
Béatrice Perret du Cray », Science et Vie Micro
[52] McCorduck, Pamela (1991), Aaron’s Code., W.H. Freeman & Co., Ltd.
[53] Romero, Juan, Machado, Penousal (eds.) (2008), The Art
of Artificial Evolution: A Handbook on Evolutionary Art
and Music, Natural Computing Series. Berlin: Springer
Verlag
[54] “Methods, systems and software for generating sentences,
and visual and audio compositions representing said sentences” Canadian Patent 2704163
[55] http://www.gamesbyangelina.org/2012/11/
introducing-mechanic-miner/
[56] http://www.gamesbyangelina.org/2012/11/
why-i-think-mechanic-miner-is-exciting/
[57] Helie, S., & Sun, R. (2010). Incubation, insight, and creative problem solving: A unified theory and a connectionist model. Psychological Review, 117, 994-1024.
[58] Schmidhuber, Jürgen (2010), Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990-2010).
IEEE Transactions on Autonomous Mental Development,
2(3):230-247
[59] Schmidhuber, Jürgen (2006), Developmental Robotics,
Optimal Artificial Curiosity, Creativity, Music, and the
Fine Arts. Connection Science, 18(2): 173-187
[60] Schmidhuber, J. (1991), Curious model-building control
systems. In Proc. ICANN, Singapore, volume 2, pp 14581463. IEEE.
[61] Thaler, S. L. (2013)The Creativity Machine Paradigm,
Encyclopedia of Creativity, Invention, Innovation, and Entrepreneurship, (ed.)
E.G. Carayannis, Springer Science+Business Media, available
http://www.springerreference.com/docs/html/
at
chapterdbid/358097.html
[62] Thaler, S.L., “Device for the autonomous generation
of useful information,” http://patft.uspto.gov/netacgi/
nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=
%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&
f=G&l=50&co1=AND&d=PTXT&s1=5659666.PN.
&OS=PN/5659666&RS=PN/5659666
[63] Thaler, S. L. (1982) “The Raman Spectrum of Neutron
Irradiated Silicon,” Ph.D. Thesis, University of Missouri,
1982
[64] Thaler, S. L. (1997). “Device for the Autonomous Generation of Useful Information*: A Completely Connectionist Approach to Cognition, Creativity, and Machine Consciousness,” International Conference on Vision, Recognition, Action, Neural Models of Mind and Machine,
Boston University, May 28–31, 1997.
[65] Confabulation (neural networks)
[66] N. Marupaka, L. Lyer, A. Minai (2012). Connectivity and thought: The influence of semantic network structure in a neurodynamical model of thinking, Neural Networks (2012), doi:10.1016/j.neunet.2012.
02.004, available at http://www.ece.uc.edu/~{}aminai/
papers/marupaka_creativity_NN12.pdf
[67] S. Thaler, Lessons from connectionism in differentiating
knowledge, „e-mentor” 2014, nr 3 (55), s. 81-86, http:
//dx.doi.org/10.15219/em55.1112.
[68] Thaler, S. L. (1993). “4-2-4 Encoder Death,” World
Congress on Neural Networks, WCNN'93
[69] Thaler, S. L. (1995). Death of a gedanken creature, Journal of Near-Death Studies, 13(3), Spring 1995
[70] Thaler, S. L. (1996) “The death dream and near-death darwinism,” Journal of Near-Death Studies, 15(1).
[71] Thaler, S. L. (1996). “A Proposed Symbolism for
Network-Implemented Discovery Processes,” In Proceedings of the World Congress on Neural Networks,
(WCNN’96), Lawrence Erlbaum, Mawah, NJ.
[72] Thaler, S. L. (1997) “A Quantitative Model of Seminal
Cognition: The Creativity Machine Paradigm,” Mind II
Conference, Dublin Ireland.
[73] Ricciardiello, L. and Fornaro, P., “Beyond the cliff of creativity, a novel key to Bipolar Disorder and creativity,”
Medical Hypotheses 80(2013) 534-543.
[74] Thaler, S. L. (1996) “Network 'cavitation' in the modeling
of consciousness,” Toward a Science of Consciousness,
Tucson, AZ, March, 1996.
[75] Thaler, S. L. (1996) “Is Neuronal Chaos the Source of
Stream of Consciousness?", World Congress on Neural
Networks, San Diego, 1996.
[76] Thaler, S. L. (2010) “Thalamocortical Algorithms in
Space! The Building of Conscious Machines and the
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[77] Thaler, S. L. (2011), “The Creativity Machine: Withstanding the Argument from Consciousness,” APA
Newsletter on Philosophy and Computers
[78] for example, US Patent 7,454,388
2.14 External links
Further reading
Documentaries
Chapter 3
Ideation (idea generation)
Ideation is the creative process of generating, develop- Philosophical idea The philosophical idea lives in the
ing, and communicating new ideas, where an idea is unmind of the creator and can never be proven. This
derstood as a basic element of thought that can be eitype of idea however can still have vast residual efther visual, concrete, or abstract.[1] Ideation comprises
fects. For example, the idea of eternal recurrence.
all stages of a thought cycle, from innovation, to development, to actualization.[2] As such, it is an essential part Computer-assisted discovery This uses a computer in
order to widen possibilities of research and numeric
of the design process, both in education and practice.[3]
possibilities.
3.1 Methods of innovation
In Ideation: The Birth and Death of Ideas, Douglas Graham and Thomas T. Bachmann propose that methods of
innovation include:
Problem solution This is the most simple method of
progress, where someone has found a problem and
as a result, solves it.
Derivative idea This involves taking something that already exists and changing it.
Symbiotic idea A symbiotic method of idea creation is
when multiple ideas are combined, using different
elements of each to make a whole.
Revolutionary idea A revolutionary idea breaks away
from traditional thought and creates a brand new
perspective. For example, Marxism (an evolutionary form of Hegelianism), or the writings
of Copernicus (a development of classical Greek
thought).
Serendipitous discovery Serendipitous solutions are
ideas which have been coincidentally developed
without the intention of the inventor. For example,
the discovery of penicillin.
This list of methods is by no means comprehensive or
necessarily accurate. Graham and Bachmann’s examples
of revolutionary ideas might better be described as evolutionary; both Marx and Copernicus having built upon
pre-existing concepts within new or different contexts.
Similarly, the description provided for artistic innovation
represents one perspective. More nuanced understandings, such as that expressed by Stephen Nachmanovitch
in Free Play: Improvisation in Life and Art, recognize
the generative force technical and perceptual limitations
provide within specific arts practices. In painting, for example, technical limitations such as the frame, the surface and the palette, along with perceptual constraints like
figure/ground relationships and perspective, provide creative frameworks for the painter. Similarly in music, harmonic scales, meter and time signatures work in tandem
with choices of instrumentation and expression to both
produce specific results and improvise novel outcomes.
The T.O.T.E. model, an iterative problem solving strategy based on feedback loops, provides an alternative approach to considering the process of ideation. Ideation
may also be considered as a facet of other generative systems, such as Emergence.
3.2 See also
Targeted innovation Creating a targeted innovation
deals with a direct path of discovery. This is often accompanied by intensive research in order to
have a distinct and almost expected resolution. For
example, linear programming.
Artistic innovation Artistic innovation disregards the
necessity for practicality and holds no constraints.
35
• Brainstorming
• Brainstorming software
• Creativity
• Creativity techniques
• Enterprise social software
36
• Decision tree
• Originality
3.3 Notes
[1] Jonson, 2005, page 613
[2] Graham and Bachmann, 2004, pg 54
[3] Broadbent, in Fowles, 1979, page 15
3.4 References
• Gänshirt, C.: Tools for Ideas. An Introduction
to Architectural Design. Basel, Boston, Berlin:
Birkhäuser, 2007
• Jonson, B (2005) Design Ideation: the conceptual
sketch in the digital age. Design Studies Vol 26 No
6 pp 613–624.
• Graham, D and Bachmann, T., (2004) Ideation: The
Birth and Death of Ideas. John Wiley and Sons Inc.
• Nachmanovitch, S (1990) Free Play: Improvisation
in Life and Art. Tarcher/Putnam.
• Fowles, R A (1979) Design Methods in UK Schools
of Architecture. Design Studies Vol 1 No 1 pp 15–
16
• T.O.T.E.
• Emergence
CHAPTER 3. IDEATION (IDEA GENERATION)
Chapter 4
Design
Design is the creation of a plan or convention for the
construction of an object or a system (as in architectural
blueprints, engineering drawings, business processes,
circuit diagrams and sewing patterns).[1] Design has different connotations in different fields (see design disciplines below). In some cases the direct construction of an
object (as in pottery, engineering, management, cowboy
coding and graphic design) is also considered to be design.
both the design object and design process. It may involve considerable research, thought, modeling, interactive adjustment, and re-design. Meanwhile, diverse
kinds of objects may be designed, including clothing,
graphical user interfaces, skyscrapers, corporate identities, business processes and even methods of designing.[8]
4.1 Design as a process
More formally design has been defined as follows.
Substantial disagreement exists concerning how designers in many fields, whether amateur or professional,
alone or in teams, produce designs. Dorst and Dijkhuis argued that “there are many ways of describing
design processes” and discussed “two basic and fundamentally different ways”,[9] both of which have several
names. The prevailing view has been called “The Ra(verb, transitive) to create a design, in an
tional Model”,[10] “Technical Problem Solving”[11] and
[2]
environment (where the designer operates)
“The Reason-Centric Perspective”.[12] The alternative
view has been called “Reflection-in-Action”,[11] “EvoluAnother definition for design is a roadmap or a strategic tionary Design”,[7] “co-evolution”[13] and “The Actionapproach for someone to achieve a unique expectation. It Centric Perspective”.[12]
defines the specifications, plans, parameters, costs, activities, processes and how and what to do within legal, political, social, environmental, safety and economic constraints 4.1.1 The Rational Model
in achieving that objective.[3]
Here, a “specification” can be manifested as either a plan The Rational Model was independently developed by
[14]
[15]
or a finished product, and “primitives” are the elements Simon and Pahl and Beitz. It posits that:
from which the design object is composed.
1. designers attempt to optimize a design candidate for
With such a broad denotation, there is no universal lanknown constraints and objectives,
guage or unifying institution for designers of all dis(noun) a specification of an object, manifested
by an agent, intended to accomplish goals, in a
particular environment, using a set of primitive
components, satisfying a set of requirements,
subject to constraints;
ciplines. This allows for many differing philosophies
and approaches toward the subject (see Philosophies and
studies of design, below).
The person designing is called a designer, which is also
a term used for people who work professionally in one
of the various design areas, usually also specifying which
area is being dealt with (such as a fashion designer, concept designer or web designer). A designer’s sequence of
activities is called a design process. The scientific study
of design is called design science.[4][5][6][7]
2. the design process is plan-driven,
3. the design process is understood in terms of a discrete sequence of stages.
The Rational Model is based on a rationalist philosophy[10] and underlies the Waterfall Model,[16] Systems
Development Life Cycle[17] and much of the engineering
design literature.[18] According to the rationalist philosophy, design is informed by research and knowledge in a
Designing often necessitates considering the aesthetic, predictable and controlled manner. Technical rationality
functional, economic and sociopolitical dimensions of is at the center of the process.
37
38
CHAPTER 4. DESIGN
Example sequence of stages
4.1.2 The Action-Centric Model
Typical stages consistent with The Rational Model in- The Action-Centric Perspective is a label given to a collection of interrelated concepts, which are antithetical to
clude the following.
The Rational Model.[12] It posits that:
• Pre-production design
• Design brief or Parti pris – an early (often the
beginning) statement of design goals
• Analysis – analysis of current design goals
• Research – investigating similar design solutions in the field or related topics
1. designers use creativity and emotion to generate design candidates,
2. the design process is improvised,
3. no universal sequence of stages is apparent – analysis, design and implementation are contemporary
and inextricably linked[12]
• Specification – specifying requirements of a The Action-Centric Perspective is based on an empiricist
design solution for a product (product design philosophy and broadly consistent with the Agile apspecification)[19] or service.
proach[23] and amethodical development.[24] Substantial
• Problem solving – conceptualizing and empirical evidence supports the veracity of this perspective in describing the actions of real designers.[21] Like
documenting design solutions
the Rational Model, the Action-Centric model sees design
• Presentation – presenting design solutions
as informed by research and knowledge. However, research and knowledge are brought into the design process
• Design during production
through the judgment and common sense of designers –
by designers “thinking on their feet” – more than through
• Development – continuation and improvement the predictable and controlled process stipulated by the
Rational Model. Designers’ context-dependent experiof a designed solution
ence and professional judgment take center stage more
• Testing – in situ testing a designed solution
than technical rationality.
• Post-production design feedback for future designs
Descriptions of design activities
• Implementation – introducing the designed solution into the environment
At least two views of design activity are consistent with
the Action-Centric Perspective. Both involve three basic
• Evaluation and conclusion – summary of pro- activities.
cess and results, including constructive criticism and suggestions for future improvements In the Reflection-in-Action paradigm, designers alternate between “framing,” “making moves,” and “evaluate
• Redesign – any or all stages in the design process moves.” “Framing” refers to conceptualizing the problem,
repeated (with corrections made) at any time before, i.e., defining goals and objectives. A “move” is a tentative design decision. The evaluation process may lead to
during, or after production.
further moves in the design.[11]
In
the
Sensemaking-Coevolution-Implementation
Framework, designers alternate between its three titular
activities. Sensemaking includes both framing and
evaluating moves. Implementation is the process of
Criticism of the Rational Model
constructing the design object. Coevolution is “the
process where the design agent simultaneously refines its
The Rational Model has been widely criticized on two mental picture of the design object based on its mental
primary grounds
picture of the context, and vice versa.”[25]
Each stage has many associated best practices.[20]
The concept of the Design Cycle describes the reflective
1. Designers do not work this way – extensive empirical and repetitive structure of design processes, assuming
evidence has demonstrated that designers do not act that this structure is underlaying all such processes.[26]
as the rational model suggests.[21]
The Design Cycle is understood as a circular time
structure,[27] which may start with the thinking of an idea,
2. Unrealistic assumptions – goals are often unknown then expressing it by the use of visual and/or verbal means
when a design project begins, and the requirements of communication (design tools), the sharing and perceivand constraints continue to change.[22]
ing of the expressed idea, and finally starting a new cycle
4.3. PHILOSOPHIES AND STUDIES OF DESIGN
with the critical rethinking of the perceived idea. Anderson points out that this concept emphasizes the importance of the means of expression, which at the same time
are means of perception of any design ideas.[28]
Criticism of the Action-Centric Perspective
39
• Sound design
• Systems architecture
• Systems design
• Systems modeling
• Transition Design
As this perspective is relatively new, it has not yet encountered much criticism. One possible criticism is that it is
less intuitive than The Rational Model.
4.2 Design disciplines
• Urban design
• User experience design
• Visual design
• Web design
• Applied arts
• Architecture
• Automotive design
• Benchmarking design
• Communication design
• Configuration design
• Engineering design
• Environmental Graphic Design
• Experiential Graphic Design
• Fashion design
• Game design
• Graphic design
• Information Architecture
• Industrial design
• Instructional design
• Interaction design
• Interior design
• Landscape architecture
• Lighting design
• Military Design Methodology[29]
• Modular design
• Motion graphic design
• Product design
• Process design
• Service design
• Software design
4.3 Philosophies and studies of design
There are countless philosophies for guiding design as
the design values and its accompanying aspects within
modern design vary, both between different schools
of thought and among practicing designers.[30] Design
philosophies are usually for determining design goals. A
design goal may range from solving the least significant
individual problem of the smallest element, to the most
holistic influential utopian goals. Design goals are usually
for guiding design. However, conflicts over immediate
and minor goals may lead to questioning the purpose of
design, perhaps to set better long term or ultimate goals.
4.3.1 Philosophies for guiding design
Design philosophies are fundamental guiding principles
that dictate how a designer approaches his/her practice.
Reflections on material culture and environmental concerns (Sustainable design) can guide a design philosophy. One example is the First Things First manifesto
which was launched within the graphic design community and states “We propose a reversal of priorities in favor of more useful, lasting and democratic forms of communication – a mindshift away from product marketing
and toward the exploration and production of a new kind
of meaning. The scope of debate is shrinking; it must
expand. Consumerism is running uncontested; it must
be challenged by other perspectives expressed, in part,
through the visual languages and resources of design.”[31]
In The Sciences of the Artificial by polymath Herbert A.
Simon the author asserts design to be a meta-discipline of
all professions. “Engineers are not the only professional
designers. Everyone designs who devises courses of action aimed at changing existing situations into preferred
ones. The intellectual activity that produces material artifacts is no different fundamentally from the one that prescribes remedies for a sick patient or the one that devises
a new sales plan for a company or a social welfare policy
40
CHAPTER 4. DESIGN
for a state. Design, so construed, is the core of all professional training; it is the principal mark that distinguishes
the professions from the sciences. Schools of engineering, as well as schools of architecture, business, education, law, and medicine, are all centrally concerned with
the process of design.”[32]
4.3.2
Approaches to design
A design approach is a general philosophy that may or
may not include a guide for specific methods. Some are to
guide the overall goal of the design. Other approaches are
to guide the tendencies of the designer. A combination of
approaches may be used if they don't conflict.
Some popular approaches include:
• KISS principle, (Keep it Simple Stupid), which
strives to eliminate unnecessary complications.
• Exploring possibilities and constraints by focusing
critical thinking skills to research and define problem spaces for existing products or services—or the
creation of new categories; (see also Brainstorming)
• Redefining the specifications of design solutions
which can lead to better guidelines for traditional
design activities (graphic, industrial, architectural,
etc.);
• Managing the process of exploring, defining, creating artifacts continually over time
• Prototyping possible scenarios, or solutions that incrementally or significantly improve the inherited
situation
• Trendspotting; understanding the trend process.
4.4 Terminology
• There is more than one way to do it (TIMTOWTDI),
a philosophy to allow multiple methods of doing the The word “design” is often considered ambiguous, as it is
same thing.
applied differently in a varying contexts.
• Use-centered design, which focuses on the goals and
tasks associated with the use of the artifact, rather
than focusing on the end user.
• User-centered design, which focuses on the needs,
wants, and limitations of the end user of the designed artifact.
• Critical design uses designed artifacts as an embodied critique or commentary on existing values,
morals, and practices in a culture.
• Service design designing or organizing the experience around a product, the service associated with a
product’s use.
• Transgenerational design, the practice of making
products and environments compatible with those
physical and sensory impairments associated with
human aging and which limit major activities of
daily living.
• Speculative design, the speculative design process
doesn’t necessarily define a specific problem to
solve, but establishes a provocative starting point
from which a design process emerges. The result
is an evolution of fluctuating iteration and reflection using designed objects to provoke questions and
stimulate discussion in academic and research settings.
The new terminal at Barajas airport in Madrid, Spain
4.3.3
Methods of designing
Main article: Design methods
Design Methods is a broad area that focuses on:
4.4.1 Design and art
Today the term design is widely associated with the
Applied arts as initiated by Raymond Loewy and teach-
4.4. TERMINOLOGY
41
ings at the Bauhaus and Ulm School of Design (HfG Ulm) of term “engineering - engineer” from Latin “in genio”
in Germany during the 20th Century.
in meaning of a “genius” what assumes existence of a
The boundaries between art and design are blurred, “mind” not of an “atom”).
largely due to a range of applications both for the term
'art' and the term 'design'. Applied arts has been used
as an umbrella term to define fields of industrial design,
graphic design, fashion design, etc. The term 'decorative
arts' is a traditional term used in historical discourses to
describe craft objects, and also sits within the umbrella
of Applied arts. In graphic arts (2D image making that
ranges from photography to illustration) the distinction is
often made between fine art and commercial art, based on
the context within which the work is produced and how
it is traded.
To a degree, some methods for creating work, such as employing intuition, are shared across the disciplines within
the Applied arts and Fine art. Mark Getlein suggests the
principles of design are “almost instinctive”, “built-in”,
“natural”, and part of “our sense of 'rightness’.”[33] However, the intended application and context of the resulting Jonathan Ive has received several awards for his design of Apple
Inc. products like this MacBook. In some design fields, personal
works will vary greatly.
computers are also used for both design and production
4.4.3 Design and production
The relationship between design and production is one
of planning and executing. In theory, the plan should
anticipate and compensate for potential problems in the
execution process. Design involves problem-solving and
A drawing for a booster engine for steam locomotives. Engineering is applied to design, with emphasis on function and the creativity. In contrast, production involves a routine or
pre-planned process. A design may also be a mere plan
utilization of mathematics and science.
that does not include a production or engineering processes although a working knowledge of such processes
is usually expected of designers. In some cases, it may be
4.4.2 Design and engineering
unnecessary and/or impractical to expect a designer with
a broad multidisciplinary knowledge required for such deIn engineering, design is a component of the engineer- signs to also have a detailed specialized knowledge of how
ing process. Many overlapping methods and processes to produce the product.
can be seen when comparing Product design, Industrial
design and Engineering. The American Heritage Dic- Design and production are intertwined in many creative
tionary defines design as: “To conceive or fashion in the professional careers, meaning problem-solving is part of
mind; invent,” and “To formulate a plan”, and defines en- execution and the reverse. As the cost of rearrangegineering as: “The application of scientific and mathemat- ment increases, the need for separating design from proical principles to practical ends such as the design, manu- duction increases as well. For example, a high-budget
facture, and operation of efficient and economical struc- project, such as a skyscraper, requires separating (design)
tures, machines, processes, and systems.”.[34][35] Both are architecture from (production) construction. A Lowforms of problem-solving with a defined distinction be- budget project, such as a locally printed office party inviing the application of “scientific and mathematical prin- tation flyer, can be rearranged and printed dozens of times
ciples”. The increasingly scientific focus of engineering at the low cost of a few sheets of paper, a few drops of
in practice, however, has raised the importance of new ink, and less than one hour’s pay of a desktop publisher.
more “human-centered” fields of design.[36] How much This is not to say that production never involves problemscience is applied in a design is a question of what is solving or creativity, nor that design always involves creconsidered "science". Along with the question of what is ativity. Designs are rarely perfect and are sometimes
considered science, there is social science versus natural repetitive. The imperfection of a design may task a
science. Scientists at Xerox PARC made the distinction production position (e.g. production artist, construction
of design versus engineering at “moving minds” versus worker) with utilizing creativity or problem-solving skills
“moving atoms” (probably in cotradiction to the origin to compensate for what was overlooked in the design
42
CHAPTER 4. DESIGN
process. Likewise, a design may be a simple repetition
(copy) of a known preexisting solution, requiring minimal, if any, creativity or problem-solving skills from the
designer.
[7] Braha, D. and Maimon, O. (1998) A Mathematical Theory of Design, Springer.
[8] Brinkkemper, S. (1996). “Method engineering: engineering of information systems development methods and
tools”. Information and Software Technology 38 (4): 275–
280. doi:10.1016/0950-5849(95)01059-9.
[9] Dorst and Dijkhuis 1995, p. 261
[10] Brooks 2010
[11] Schön 1983
[12] Ralph 2010
[13] Dorst and Cross 2001
An example of a business workflow process using Business Process Modeling Notation.
[14] Newell and Simon 1972; Simon 1969
[15] Pahl and Beitz 1996
4.4.4
Process design
“Process design” (in contrast to “design process” mentioned above) refers to the planning of routine steps of a
process aside from the expected result. Processes (in general) are treated as a product of design, not the method of
design. The term originated with the industrial designing
of chemical processes. With the increasing complexities
of the information age, consultants and executives have
found the term useful to describe the design of business
processes as well as manufacturing processes.
[16] Royce 1970
[17] Bourque and Dupuis 2004
[18] Pahl et al. 2007
[19] Cross, N., 2006. T211 Design and Designing: Block 2, p.
99. Milton Keynes: The Open University.
[20] Ullman, David G. (2009) The Mechanical Design Process, Mc Graw Hill, 4th edition ISBN 0-07-297574-1
[21] Cross et al. 1992; Ralph 2010; Schön 1983
[22] Brooks 2010; McCracken and Jackson 1982
4.5 See also
• Design elements and principles
[23] Beck et al. 2001
[24] Truex et al. 2000
[25] Ralph 2010, p. 67
4.6 Footnotes
[1] Dictionary meanings in the Cambridge Dictionary of
American English, at Dictionary.com (esp. meanings 1–5
and 7–8) and at AskOxford (esp. verbs).
[2] Ralph, P. and Wand, Y. (2009). A proposal for a formal definition of the design concept. In Lyytinen, K.,
Loucopoulos, P., Mylopoulos, J., and (Robinson, W.,) editors, Design Requirements Workshop (LNBIP 14), pp.
103–136. Springer-Verlag, p. 109 doi:10.1007/978-3540-92966-6_6.
[3] Don Kumaragamage, Y. (2011). Design Manual Vol 1
[4] Simon (1996)
[26] Gänshirt, Christian: Tools for Ideas. An Introduction to
Architectural Design. Basel, Boston, Berlin: Birkhäuser,
2007, ISBN 978-3-7643-7577-5, pp. 78-80
[27] Thomas Fischer: Design Enigma. A typographical
metaphor for enigmatic processes, including designing, in:
T. Fischer, K. De Biswas, J.J. Ham, R. Naka, W.X.
Huang, Beyond Codes and Pixels: Proceedings of the
17th International Conference on Computer-Aided Architectural Design Research in Asia, p. 686
[28] Jane Anderson: Architectural Design, Basics Architecture 03, Lausanne, AVA academia, 2011, ISBN 978-2940411-26-9, p. 40
[5] Alexander, C. (1964) Notes on the Synthesis of Form,
Harvard University Press.
[29] Headquarters, Department of the Army (May 2012).
ADRP 5-0: The Operations Process. Washington D.C.:
United States Army. pp. 2–4 to 2–11.
[6] Eekels, J. (2000). “On the Fundamentals of Engineering
Design Science: The Geography of Engineering Design
Science, Part 1”. Journal of Engineering Design 11 (4):
377–397. doi:10.1080/09544820010000962.
[30] Holm, Ivar (2006). Ideas and Beliefs in Architecture and
Industrial design: How attitudes, orientations and underlying assumptions shape the built environment. Oslo School
of Architecture and Design. ISBN 82-547-0174-1.
4.7. BIBLIOGRAPHY
[31] First Things First 2000 a design manifesto. manifesto
published jointly by 33 signatories in: Adbusters, the
AIGA journal, Blueprint, Emigre, Eye, Form, Items fall
1999/spring 2000
[32] Simon (1996), p. 111.
[33] Mark Getlein, Living With Art, 8th ed. (New York: 2008)
121.
[34] American Psychological Association (APA): design. The
American Heritage Dictionary of the English Language,
Fourth Edition. Retrieved January 10, 2007
[35] American Psychological Association (APA): engineering.
The American Heritage Dictionary of the English Language, Fourth Edition. Retrieved January 10, 2007
[36] Faste 2001
4.7 Bibliography
• Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning,
J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J.,
Marick, B., Martin, R.C., Mellor, S., Schwaber, K.,
Sutherland, J., and Thomas, D. Manifesto for agile
software development, 2001.
• Bourque, P., and Dupuis, R. (eds.) Guide to the software engineering body of knowledge (SWEBOK).
IEEE Computer Society Press, 2004 ISBN 0-76952330-7.
• Brooks, F.P. The design of design: Essays from
a computer scientist, Addison-Wesley Professional,
2010 ISBN 0-201-36298-8.
• Cross, N., Dorst, K., and Roozenburg, N. Research
in design thinking, Delft University Press, Delft,
1992 ISBN 90-6275-796-0.
• Dorst, K., and Cross, N. (2001). “Creativity in the
design process: Co-evolution of problem-solution”.
Design Studies 22 (2): 425–437. doi:10.1016/0142694X(94)00012-3.
• Dorst, K., and Dijkhuis, J. “Comparing paradigms
for describing design activity,” Design Studies (16:2)
1995, pp 261–274.
• Faste, R. (2001). “The Human Challenge in Engineering Design”. International Journal of Engineering Education 17 (4–5): 327–331.
• Gänshirt, C.: Tools for Ideas. An Introduction
to Architectural Design. Basel, Boston, Berlin:
Birkhäuser, 2007
• McCracken, D.D., and Jackson, M.A. (1982).
“Life cycle concept considered harmful”. SIGSOFT Software Engineering Notes 7 (2): 29–32.
doi:10.1145/1005937.1005943.
43
• Newell, A., and Simon, H. Human problem solving,
Prentice-Hall, Inc., 1972.
• Pahl, G., and Beitz, W. Engineering design: A systematic approach, Springer-Verlag, London, 1996
ISBN 3-540-19917-9.
• Pahl, G., Beitz, W., Feldhusen, J., and Grote, K.H. Engineering design: A systematic approach, (3rd
ed.), Springer-Verlag, 2007 ISBN 1-84628-318-3.
• Pirkl, James J. Transgenerational Design: Products
for an Aging Population, Van Nostrand Reinhold,
New York, NY, USA, 1994 ISBN 0-442-01065-6.
• Ralph, P. “Comparing two software design process
theories,” International Conference on Design Science Research in Information Systems and Technology (DESRIST 2010), Springer, St. Gallen,
Switzerland, 2010, pp. 139–153.
• Royce, W.W. “Managing the development of large
software systems: Concepts and techniques,” Proceedings of Wescon, 1970.
• Schön, D.A. The reflective practitioner: How professionals think in action, Basic Books, USA, 1983.
• Simon, H.A. The sciences of the artificial, MIT
Press, Cambridge, MA, USA, 1996 ISBN 0-26269191-4.
• Truex, D., Baskerville, R., and Travis, J. (2000).
“Amethodical systems development: The deferred meaning of systems development methods”. Accounting, Management and Information
Technologies 10 (1): 53–79. doi:10.1016/S09598022(99)00009-0.
Chapter 5
Creativity techniques
Creativity techniques are methods that encourage
creative actions, whether in the arts or sciences. They
focus on a variety of aspects of creativity, including techniques for idea generation and divergent thinking, methods of re-framing problems, changes in the affective environment and so on. They can be used as part of problem
solving, artistic expression, or therapy.
visation, also called extemporization, can lead to the discovery of new ways to act, new patterns of thought and
practices, or new structures. Improvisation is used in the
creation of music, theater, and other various forms. Many
artists also use improvisational techniques to help their
creative flow.
The following are two significant methods:
Some techniques require groups of two or more people while other techniques can be accomplished alone.
These methods include word games, written exercises
and different types of improvisation, or algorithms for
approaching problems. Aleatory techniques exploiting
randomness are also common.
• Improvisational theater is a form of theater in
which actors use improvisational acting techniques
to perform spontaneously. Many improvisational
(“improv”) techniques are taught in standard drama
classes. The basic skills of listening, clarity, confidence, and performing instinctively and spontaneously are considered important skills for actors to
develop.[2]
5.1 Aleatory techniques
• Free improvisation is real-time composition. Musicians of all kinds improvise (“improv”) music;
such improvised music is not limited to a particular
genre. Two contemporary musicians that use free
improvisation are Anthony Braxton and Cecil Taylor. Through free improvisation, musicians can develop increased spontaneity and fluency.[3]
Main article: Aleatoricism
Aleatoricism is the incorporation of chance (random elements) into the process of creation, especially the creation of art or media. Aleatoricism is commonly found
in music, art, and literature, particularly in poetry. In
film, Andy Voda made a movie in 1979 called “Chance
Chants”, which he produced by a flip of a coin or roll of
a dice. In music, John Cage, an avant-garde musician,
composed music by superimposing star maps on blank
sheet music, by rolling dice and preparing open ended
scores that depended on the spontaneous decisions of the
performers. (1) Other ways of practicing randomness include coin tossing, picking something out of a hat, or selecting random words from a dictionary.
In short, aleatoricism is a way to introduce new thoughts
or ideas into a creative process.
Each type of improvisation improves the thinking and
acting skills of the actor, and this is done by using no
practice. A similar set of techniques is called alienation
since one of its many techniques uses actors that haven't
rehearsed or even read the play. Improvisation is an acting technique during which actors make up a storyline,
start and end on the spot, and try their best to keep in
character.
5.3 Problem solving
5.2 Improvisation
In problem-solving contexts, the random-word creativity
technique is perhaps the simplest method. A person confronted with a problem is presented with a randomly genMain article: improvisation
erated word, in the hopes of a solution arising from any
associations between the word and the problem. A ranImprovisation is a creative process which can be spoken, dom image, sound, or article can be used instead of a ranwritten, or composed without prior preparation.[1] Impro- dom word as a kind of creativity goad or provocation.[4][5]
44
5.6. EXTERNAL LINKS
Tools and methodologies to support creativity.[6]
• TRIZ (theory which are derived from tools such as
ARIZ or TRIZ contradiction matrix)
• Creative Problem Solving Process (CPS) (complex
strategy, also known as Osborn-Parnes-process)
• Lateral thinking process, of Edward de Bono
• Six Thinking Hats, of Edward de Bono
• Method Herrmann - right brain / left brain
• Brainstorming and Brainwriting
• Think outside the box
• Business war games, for the resolution of competitive problems
• SWOT analysis
• The method USIT of convergent creativity
• Thought experiment
• Five Ws
• Coaching
5.4 See also
• Association
• Problem solving
• Creative problem solving
• Decision tree
• Ideas banks
• Imagination
• Intuition
• Invention
• Lateral thinking
• Metaphor
5.5 References
[1] Improvisation | Define Improvisation at Dictionary.com
[2]
[3] jazz improvisation : music improvisation : jazz theory
[4] More On Idea Generation Tools and Techniques. IdeaFlow: Discussion about innovation and creativity - new
products, strategy, open innovation, commercialization of
technologies...
45
[5] “Idea Generation, Creativity and Incentives”.
sloan.mit.edu. Retrieved 2013-08-25.
Mit-
[6] See Gänshirt, Christian: Tools for Ideas. An Introduction to Architectural Design. Basel, Boston, Berlin:
Birkhäuser, 2007
5.6 External links
• Creativity Techniques - an A to Z
• Management of creativity (French.)
Chapter 6
Emergence
For other uses, see Emergence (disambiguation).
See also: Emergent (disambiguation), Spontaneous order
and Self-organization
In philosophy, systems theory, science, and art, emer-
A termite “cathedral” mound produced by a termite colony is a
classic example of emergence in nature.
nomena are often presumed to suffice as the underlying
basis of psychological phenomena, whereby economic
phenomena are in turn presumed to principally emerge.
Snowflakes forming complex symmetrical and fractal patterns is
an example of emergence in a physical system.
gence is conceived as a process whereby larger entities, patterns, and regularities arise through interactions
among smaller or simpler entities that themselves do not
exhibit such properties. In philosophy, almost all accounts of emergence include a form of irreducibility (either epistemic or ontological) to the lower levels.[1] Also,
emergence is central in theories of integrative levels and
of complex systems. For instance, the phenomenon life as
studied in biology is commonly perceived as an emergent
property of interacting molecules as studied in chemistry,
whose phenomena reflect interactions among elementary
particles, modeled in particle physics, that at such higher
mass—via substantial conglomeration—exhibit motion
as modeled in gravitational physics. Neurobiological phe-
6.1 Definitions
The idea of emergence has been around since at least the
time of Aristotle.[2] John Stuart Mill[3] and Julian Huxley[4] are two of many historical scientists who have written on the concept.
The term “emergent” was coined by philosopher G. H.
Lewes, who wrote:
46
“Every resultant is either a sum or a difference of the co-operant forces; their sum, when
6.2. STRONG AND WEAK EMERGENCE
their directions are the same -- their difference, when their directions are contrary. Further, every resultant is clearly traceable in its
components, because these are homogeneous
and commensurable. It is otherwise with emergents, when, instead of adding measurable motion to measurable motion, or things of one
kind to other individuals of their kind, there is
a co-operation of things of unlike kinds. The
emergent is unlike its components insofar as
these are incommensurable, and it cannot be
reduced to their sum or their difference.”[5][6]
Economist Jeffrey Goldstein provided a current definition
of emergence in the journal Emergence.[7] Goldstein initially defined emergence as: “the arising of novel and coherent structures, patterns and properties during the process of self-organization in complex systems”.
47
Moreover, and this is a key point, the game of
chess is also shaped by teleonomic, cybernetic,
feedback-driven influences. It is not simply a
self-ordered process; it involves an organized,
“purposeful” activity.[8]
6.2 Strong and weak emergence
Usage of the notion “emergence” may generally be subdivided into two perspectives, that of “weak emergence”
and “strong emergence”. In terms of physical systems,
weak emergence is a type of emergence in which the
emergent property is amenable to computer simulation.
This is opposed to the older notion of strong emergence,
in which the emergent property cannot be simulated by a
computer.
Some common points between the two notions are that
Goldstein’s definition can be further elaborated to de- emergence concerns new properties produced as the sysscribe the qualities of this definition in more detail:
tem grows, which is to say ones which are not shared with
its components or prior states. Also, it is assumed that
the properties are supervenient rather than metaphysically
“The common characteristics are: (1) radiprimitive (Bedau 1997).
cal novelty (features not previously observed in
systems); (2) coherence or correlation (meanWeak emergence describes new properties arising in sysing integrated wholes that maintain themselves
tems as a result of the interactions at an elemental level.
over some period of time); (3) A global or
However, it is stipulated that the properties can be determacro “level” (i.e. there is some property of
mined by observing or simulating the system, and not by
“wholeness”); (4) it is the product of a dynamany process of a priori analysis.
ical process (it evolves); and (5) it is “ostensive”
Bedau notes that weak emergence is not a universal meta(it can be perceived). For good measure, Goldphysical solvent, as weak emergence leads to the conclustein throws in supervenience -- downward cau[8]
sion that matter itself contains elements of awareness to it.
sation.”
However, Bedau concludes that adopting this view would
provide a precise notion that emergence is involved in
Systems scientist Peter Corning also points out that living
consciousness, and second, the notion of weak emergence
systems cannot be reduced to underlying laws of physics:
is metaphysically benign (Bedau 1997).
Rules, or laws, have no causal efficacy; they
do not in fact “generate” anything. They serve
merely to describe regularities and consistent
relationships in nature. These patterns may be
very illuminating and important, but the underlying causal agencies must be separately specified (though often they are not). But that aside,
the game of chess illustrates ... why any laws
or rules of emergence and evolution are insufficient. Even in a chess game, you cannot use the
rules to predict “history” — i.e., the course of
any given game. Indeed, you cannot even reliably predict the next move in a chess game.
Why? Because the “system” involves more
than the rules of the game. It also includes
the players and their unfolding, moment-bymoment decisions among a very large number
of available options at each choice point. The
game of chess is inescapably historical, even
though it is also constrained and shaped by a
set of rules, not to mention the laws of physics.
Strong emergence describes the direct causal action of
a high-level system upon its components; qualities produced this way are irreducible to the system’s constituent
parts (Laughlin 2005). The whole is greater than the sum
of its parts. It follows that no simulation of the system
can exist, for such a simulation would itself constitute a
reduction of the system to its constituent parts (Bedau
1997).
However, “the debate about whether or not the whole
can be predicted from the properties of the parts misses
the point. Wholes produce unique combined effects, but
many of these effects may be co-determined by the context and the interactions between the whole and its environment(s)" (Corning 2002). In accordance with his Synergism Hypothesis (Corning 1983 2005), Corning also
stated, “It is the synergistic effects produced by wholes
that are the very cause of the evolution of complexity
in nature.” Novelist Arthur Koestler used the metaphor
of Janus (a symbol of the unity underlying complements
like open/shut, peace/war) to illustrate how the two perspectives (strong vs. weak or holistic vs. reductionis-
48
CHAPTER 6. EMERGENCE
tic) should be treated as non-exclusive, and should work
together to address the issues of emergence (Koestler
1969). Further,
The ability to reduce everything to simple
fundamental laws does not imply the ability to
start from those laws and reconstruct the universe. The constructionist hypothesis breaks
down when confronted with the twin difficulties of scale and complexity. At each level
of complexity entirely new properties appear.
Psychology is not applied biology, nor is biology applied chemistry. We can now see that
the whole becomes not merely more, but very
different from the sum of its parts. (Anderson
1972)
The plausibility of strong emergence is questioned by
some as contravening our usual understanding of physics.
Mark A. Bedau observes:
Although strong emergence is logically
possible, it is uncomfortably like magic. How
does an irreducible but supervenient downward
causal power arise, since by definition it cannot
be due to the aggregation of the micro-level potentialities? Such causal powers would be quite
unlike anything within our scientific ken. This
not only indicates how they will discomfort
reasonable forms of materialism. Their mysteriousness will only heighten the traditional
worry that emergence entails illegitimately getting something from nothing.[9]
Meanwhile, others have worked towards developing analytical evidence of strong emergence. In 2009, Gu et al.
presented a class of physical systems that exhibits noncomputable macroscopic properties.[10][11] More precisely, if one could compute certain macroscopic properties of these systems from the microscopic description
of these systems, they one would be able to solve computational problems known to be undecidable in computer
science. They concluded that
Although macroscopic concepts are essential for understanding our world, much of
fundamental physics has been devoted to the
search for a `theory of everything', a set of
equations that perfectly describe the behavior
of all fundamental particles. The view that this
is the goal of science rests in part on the rationale that such a theory would allow us to derive the behavior of all macroscopic concepts,
at least in principle. The evidence we have presented suggests that this view may be overly
optimistic. A `theory of everything' is one of
many components necessary for complete understanding of the universe, but is not necessarily the only one. The development of macroscopic laws from first principles may involve
more than just systematic logic, and could require conjectures suggested by experiments,
simulations or insight.[10]
6.3 Objective or subjective quality
The properties of complexity and organization of any
system are considered by Crutchfield to be subjective
qualities determined by the observer.
“Defining structure and detecting the emergence of complexity in nature are inherently
subjective, though essential, scientific activities. Despite the difficulties, these problems can be analysed in terms of how modelbuilding observers infer from measurements
the computational capabilities embedded in
non-linear processes. An observer’s notion of
what is ordered, what is random, and what is
complex in its environment depends directly on
its computational resources: the amount of raw
measurement data, of memory, and of time
available for estimation and inference. The
discovery of structure in an environment depends more critically and subtly, though, on
how those resources are organized. The descriptive power of the observer’s chosen (or implicit) computational model class, for example,
can be an overwhelming determinant in finding
regularity in data."(Crutchfield 1994)
On the other hand, Peter Corning argues “Must the synergies be perceived/observed in order to qualify as emergent effects, as some theorists claim? Most emphatically
not. The synergies associated with emergence are real
and measurable, even if nobody is there to observe them.”
(Corning 2002)
6.4 In philosophy, religion, art and
human sciences
Main article: Emergentism
In philosophy, emergence is often understood to be a
much weaker claim about the etiology of a system’s properties. An emergent property of a system, in this context, is one that is not a property of any component of
that system, but is still a feature of the system as a whole.
Nicolai Hartmann, one of the first modern philosophers
6.5. EMERGENT PROPERTIES AND PROCESSES
49
to write on emergence, termed this categorial novum (new properties result may occur in either the observed or obcategory).
serving system, and can commonly be identified by their
In religion, emergence grounds expressions of religious patterns of accumulating change, most generally called
naturalism in which a sense of the sacred is perceived in 'growth'. Emergent behaviours can occur because of inthe workings of entirely naturalistic processes by which tricate causal relations across different scales and feedmore complex forms arise or evolve from simpler forms. back, known as interconnectivity. The emergent property
Examples are detailed in a 2006 essay titled 'The Sa- itself may be either very predictable or unpredictable and
cred Emergence of Nature' by Ursula Goodenough and unprecedented, and represent a new level of the system’s
evolution. The complex behaviour or properties are not a
Terrence Deacon and a 2006 essay titled 'Beyond Reducproperty of any single such entity, nor can they easily be
tionism: Reinventing the Sacred' by Stuart Kauffman.
predicted or deduced from behaviour in the lower-level
In art, emergence is used to explore the origins of nov- entities, and might in fact be irreducible to such behavelty, creativity, and authorship. Some art/literary theo- ior. The shape and behaviour of a flock of birds or school
rists (Wheeler, 2006;[12] Alexander, 2011[13] ) have pro- of fish are good examples of emergent properties.
posed alternatives to postmodern understandings of “authorship” using the complexity sciences and emergence One reason why emergent behaviour is hard to predict
theory. They contend that artistic selfhood and meaning is that the number of interactions between components
are emergent, relatively objective phenomena. The con- of a system increases exponentially with the number of
cept of emergence has also been applied to the theory components, thus potentially allowing for many new and
of literature and art, history, linguistics, cognitive sci- subtle types of behaviour to emerge.
ences, etc. by the teachings of Jean-Marie Grassin at On the other hand, merely having a large number of inthe University of Limoges (v. esp.: J. Fontanille, B. teractions is not enough by itself to guarantee emergent
Westphal, J. Vion-Dury, éds. L'Émergence—Poétique behaviour; many of the interactions may be negligible or
de l'Émergence, en réponse aux travaux de Jean-Marie irrelevant, or may cancel each other out. In some cases,
Grassin, Bern, Berlin, etc., 2011; and: the article a large number of interactions can in fact work against
"Emergence" in the International Dictionary of Literary the emergence of interesting behaviour, by creating a lot
of “noise” to drown out any emerging “signal"; the emerTerms (DITL).
In international development, concepts of emergence gent behaviour may need to be temporarily isolated from
other interactions before it reaches enough critical mass
have been used within a theory of social change termed
SEED-SCALE to show how standard principles inter- to be self-supporting. Thus it is not just the sheer numact to bring forward socio-economic development fitted ber of connections between components which encourto cultural values, community economics, and natural ages emergence; it is also how these connections are orenvironment (local solutions emerging from the larger ganised. A hierarchical organisation is one example that
socio-econo-biosphere). These principles can be imple- can generate emergent behaviour (a bureaucracy may bemented utilizing a sequence of standardized tasks that have in a way quite different from that of the individual
self-assemble in individually specific ways utilizing recur- humans in that bureaucracy); but perhaps more interestingly, emergent behaviour can also arise from more desive evaluative criteria.[14]
centralized organisational structures, such as a marketIn postcolonial studies, the term “Emerging Literature” place. In some cases, the system has to reach a combined
refers to a contemporary body of texts that is gaining mo- threshold of diversity, organisation, and connectivity bementum in the global literary landscape (v. esp.: J.M. fore emergent behaviour appears.
Grassin, ed. Emerging Literatures, Bern, Berlin, etc. :
Peter Lang, 1996). By opposition, “emergent literature” Unintended consequences and side effects are closely related to emergent properties. Luc Steels writes: “A comis rather a concept used in the theory of literature.
ponent has a particular functionality but this is not recognizable as a subfunction of the global functionality. Instead a component implements a behaviour whose side ef6.5 Emergent properties and pro- fect contributes to the global functionality [...] Each behaviour has a side effect and the sum of the side effects
cesses
gives the desired functionality” (Steels 1990). In other
words, the global or macroscopic functionality of a sysAn emergent behavior or emergent property can ap- tem with “emergent functionality” is the sum of all “side
pear when a number of simple entities (agents) oper- effects”, of all emergent properties and functionalities.
ate in an environment, forming more complex behaviors as a collective. If emergence happens over disparate size scales, then the reason is usually a causal relation across different scales. In other words there is often a form of top-down feedback in systems with emergent properties.[15] The processes from which emergent
Systems with emergent properties or emergent structures
may appear to defy entropic principles and the second law
of thermodynamics, because they form and increase order despite the lack of command and central control. This
is possible because open systems can extract information
50
and order out of the environment.
cannot be reduced in this way. See the discussion in this
Emergence helps to explain why the fallacy of division is article of strong and weak emergence.
a fallacy.
Emergent structures can be found in many natural phenomena, from the physical to the biological domain.
For example, the shape of weather phenomena such as
are emergent structures. The development
6.6 Emergent structures in nature hurricanes
and growth of complex, orderly crystals, as driven by the
random motion of water molecules within a conducive
Main article: Patterns in nature
natural environment, is another example of an emergent
Emergent structures are patterns that emerge via col- process, where randomness can give rise to complex and
deeply attractive, orderly structures.
Ripple patterns in a sand dune created by wind or water is an
example of an emergent structure in nature.
Water crystals forming on glass demonstrate an emergent, fractal
natural process occurring under appropriate conditions of temperature and humidity.
However, crystalline structure and hurricanes are said to
have a self-organizing phase.
Giant’s Causeway in Northern Ireland is an example of a complex
emergent structure created by natural processes.
Symphony of the Stones carved by Goght River at Garni Gorge
in Armenia is an example of an emergent natural structure.
lective actions of many individual entities. To explain
such patterns, one might conclude, per Aristotle,[2] that
emergent structures are more than the sum of their parts
on the assumption that the emergent order will not arise
if the various parts simply interact independently of one
another. However, there are those who disagree.[16] According to this argument, the interaction of each part with
its immediate surroundings causes a complex chain of
processes that can lead to order in some form. In fact,
some systems in nature are observed to exhibit emergence based upon the interactions of autonomous parts,
and some others exhibit emergence that at least at present
It is useful to distinguish three forms of emergent structures. A first-order emergent structure occurs as a result
of shape interactions (for example, hydrogen bonds in water molecules lead to surface tension). A second-order
emergent structure involves shape interactions played
out sequentially over time (for example, changing atmospheric conditions as a snowflake falls to the ground build
upon and alter its form). Finally, a third-order emergent structure is a consequence of shape, time, and heritable instructions. For example, an organism’s genetic
code sets boundary conditions on the interaction of biological systems in space and time.
6.6. EMERGENT STRUCTURES IN NATURE
6.6.1
Non-living, physical systems
In physics, emergence is used to describe a property, law,
or phenomenon which occurs at macroscopic scales (in
space or time) but not at microscopic scales, despite the
fact that a macroscopic system can be viewed as a very
large ensemble of microscopic systems.
An emergent property need not be more complicated than
the underlying non-emergent properties which generate
it. For instance, the laws of thermodynamics are remarkably simple, even if the laws which govern the interactions between component particles are complex. The
term emergence in physics is thus used not to signify complexity, but rather to distinguish which laws and concepts
apply to macroscopic scales, and which ones apply to microscopic scales.
Some examples include:
• Classical mechanics: The laws of classical mechanics can be said to emerge as a limiting case from the
rules of quantum mechanics applied to large enough
masses. This is particularly strange since quantum
mechanics is generally thought of as more complicated than classical mechanics.
• Friction: Forces between elementary particles are
conservative. However, friction emerges when considering more complex structures of matter, whose
surfaces can convert mechanical energy into heat
energy when rubbed against each other. Similar
considerations apply to other emergent concepts in
continuum mechanics such as viscosity, elasticity,
tensile strength, etc.
• Patterned ground: the distinct, and often symmetrical geometric shapes formed by ground material in
periglacial regions.
51
Temperature is sometimes used as an example of an
emergent macroscopic behaviour. In classical dynamics, a snapshot of the instantaneous momenta of a large
number of particles at equilibrium is sufficient to find the
average kinetic energy per degree of freedom which is
proportional to the temperature. For a small number of
particles the instantaneous momenta at a given time are
not statistically sufficient to determine the temperature
of the system. However, using the ergodic hypothesis, the
temperature can still be obtained to arbitrary precision by
further averaging the momenta over a long enough time.
Convection in a liquid or gas is another example of emergent macroscopic behaviour that makes sense only when
considering differentials of temperature. Convection
cells, particularly Bénard cells, are an example of a selforganizing system (more specifically, a dissipative system) whose structure is determined both by the constraints of the system and by random perturbations: the
possible realizations of the shape and size of the cells depends on the temperature gradient as well as the nature of
the fluid and shape of the container, but which configurations are actually realized is due to random perturbations
(thus these systems exhibit a form of symmetry breaking).
In some theories of particle physics, even such basic
structures as mass, space, and time are viewed as emergent phenomena, arising from more fundamental concepts such as the Higgs boson or strings. In some interpretations of quantum mechanics, the perception of a
deterministic reality, in which all objects have a definite
position, momentum, and so forth, is actually an emergent phenomenon, with the true state of matter being described instead by a wavefunction which need not have a
single position or momentum. Most of the laws of physics
themselves as we experience them today appear to have
emerged during the course of time making emergence the
most fundamental principle in the universe and raising the
question of what might be the most fundamental law of
physics from which all others emerged. Chemistry can
in turn be viewed as an emergent property of the laws
of physics. Biology (including biological evolution) can
be viewed as an emergent property of the laws of chemistry. Similarly, psychology could be understood as an
emergent property of neurobiological laws. Finally, freemarket theories understand economy as an emergent feature of psychology.
• Statistical mechanics was initially derived using the
concept of a large enough ensemble that fluctuations
about the most likely distribution can be all but ignored. However, small clusters do not exhibit sharp
first order phase transitions such as melting, and at
the boundary it is not possible to completely categorize the cluster as a liquid or solid, since these concepts are (without extra definitions) only applicable
to macroscopic systems. Describing a system using
statistical mechanics methods is much simpler than In Laughlin’s book, he explains that for many particle sysusing a low-level atomistic approach.
tems, nothing can be calculated exactly from the microscopic equations, and that macroscopic systems are char• Electrical networks: The bulk conductive response acterised by broken symmetry: the symmetry present in
of binary (RC) electrical networks with random the microscopic equations is not present in the macroarrangements can be seen as emergent properties scopic system, due to phase transitions. As a result, these
of such physical systems. Such arrangements can macroscopic systems are described in their own termibe used as simple physical prototypes for deriving nology, and have properties that do not depend on many
mathematical formulae for the emergent responses microscopic details. This does not mean that the miof complex systems.[17]
croscopic interactions are irrelevant, but simply that you
do not see them anymore — you only see a renormal• Weather.
52
ized effect of them. Laughlin is a pragmatic theoretical
physicist: if you cannot, possibly ever, calculate the broken symmetry macroscopic properties from the microscopic equations, then what is the point of talking about
reducibility?
6.6.2
Living, biological systems
Emergence and evolution
See also: Abiogenesis
Life is a major source of complexity, and evolution is the
major process behind the varying forms of life. In this
view, evolution is the process describing the growth of
complexity in the natural world and in speaking of the
emergence of complex living beings and life-forms, this
view refers therefore to processes of sudden changes in
evolution.
An example to consider in detail is an ant colony. The
queen does not give direct orders and does not tell the
ants what to do. Instead, each ant reacts to stimuli in the
form of chemical scent from larvae, other ants, intruders,
food and buildup of waste, and leaves behind a chemical trail, which, in turn, provides a stimulus to other ants.
Here each ant is an autonomous unit that reacts depending
only on its local environment and the genetically encoded
rules for its variety of ant. Despite the lack of centralized
decision making, ant colonies exhibit complex behavior
and have even been able to demonstrate the ability to solve
geometric problems. For example, colonies routinely find
the maximum distance from all colony entrances to dispose of dead bodies.[18]
Organization of life
A broader example of emergent properties in biology is
viewed in the biological organisation of life, ranging from
the subatomic level to the entire biosphere. For examRegarding causality in evolution Peter Corning observes: ple, individual atoms can be combined to form molecules
such as polypeptide chains, which in turn fold and refold to form proteins, which in turn create even more
“Synergistic effects of various kinds have
complex structures. These proteins, assuming their funcplayed a major causal role in the evolutionary
tional status from their spatial conformation, interact toprocess generally and in the evolution of coopgether and with other molecules to achieve higher bioeration and complexity in particular... Natural
logical functions and eventually create an organism. Anselection is often portrayed as a “mechanism”,
other example is how cascade phenotype reactions, as deor is personified as a causal agency... In realtailed in chaos theory, arise from individual genes mutatity, the differential “selection” of a trait, or an
ing respective positioning.[19] At the highest level, all the
adaptation, is a consequence of the functional
biological communities in the world form the biosphere,
effects it produces in relation to the survival
where its human participants form societies, and the comand reproductive success of a given organism
plex interactions of meta-social systems such as the stock
in a given environment. It is these functional
market.
effects that are ultimately responsible for the
trans-generational continuities and changes in
nature.” (Corning 2002)
6.7 In humanity
Per his definition of emergence, Corning also addresses
6.7.1
emergence and evolution:
"[In] evolutionary processes, causation is
iterative; effects are also causes. And this is
equally true of the synergistic effects produced
by emergent systems. In other words, emergence itself... has been the underlying cause
of the evolution of emergent phenomena in
biological evolution; it is the synergies produced by organized systems that are the key.”
(Corning 2002)
Spontaneous order
See also: Spontaneous order and Self-organization
Groups of human beings, left free to each regulate themselves, tend to produce spontaneous order, rather than the
meaningless chaos often feared. This has been observed
in society at least since Chuang Tzu in ancient China. A
classic traffic roundabout is a good example, with cars
moving in and out with such effective organization that
some modern cities have begun replacing stoplights at
problem intersections with traffic circles , and getting betSwarming is a well-known behaviour in many ani- ter results. Open-source software and Wiki projects form
mal species from marching locusts to schooling fish to an even more compelling illustration.
flocking birds. Emergent structures are a common strat- Emergent processes or behaviours can be seen in many
egy found in many animal groups: colonies of ants, other places, such as cities, cabal and market-dominant
mounds built by termites, swarms of bees, shoals/schools minority phenomena in economics, organizational phenomena in computer simulations and cellular automata.
of fish, flocks of birds, and herds/packs of mammals.
6.7. IN HUMANITY
Whenever you have a multitude of individuals interacting with one another, there often comes a moment when
disorder gives way to order and something new emerges:
a pattern, a decision, a structure, or a change in direction
(Miller 2010, 29).[20]
Economics
The stock market (or any market for that matter) is an
example of emergence on a grand scale. As a whole it
precisely regulates the relative security prices of companies across the world, yet it has no leader; when no
central planning is in place, there is no one entity which
controls the workings of the entire market. Agents, or
investors, have knowledge of only a limited number of
companies within their portfolio, and must follow the regulatory rules of the market and analyse the transactions
individually or in large groupings. Trends and patterns
emerge which are studied intensively by technical analysts.
Money
Money, insofar as being a medium of exchange and of
deferred payment, is also an example of an emergent phenomenon between market participators. In their strive to
possess a commodity with greater marketability than their
own commodity, such that the possession of these more
marketable commodities (money) facilitate the search for
commodities that participators want (e.g. consumables).
Austrian School economist Carl
Menger wrote in his work Principles of Economics, “As each economizing individual becomes increasingly more aware of his economic
interest, he is led by this interest, without any agreement, without
legislative compulsion, and even
without regard to the public interest, to give his commodities in exchange for other, more saleable,
commodities, even if he does not
need them for any immediate consumption purpose. With economic
progress, therefore, we can everywhere observe the phenomenon of
a certain number of goods, especially those that are most easily
saleable at a given time and place,
becoming, under the powerful influence of custom, acceptable to everyone in trade, and thus capable
of being given in exchange for any
other commodity.”[21]
53
World Wide Web and the Internet
The World Wide Web is a popular example of a decentralized system exhibiting emergent properties. There is
no central organization rationing the number of links, yet
the number of links pointing to each page follows a power
law in which a few pages are linked to many times and
most pages are seldom linked to. A related property of
the network of links in the World Wide Web is that almost any pair of pages can be connected to each other
through a relatively short chain of links. Although relatively well known now, this property was initially unexpected in an unregulated network. It is shared with
many other types of networks called small-world networks (Barabasi, Jeong, & Albert 1999, pp. 130–131).
Internet traffic can also exhibit some seemingly emergent
properties. In the congestion control mechanism, TCP
flows can become globally synchronized at bottlenecks,
simultaneously increasing and then decreasing throughput in coordination. Congestion, widely regarded as a
nuisance, is possibly an emergent property of the spreading of bottlenecks across a network in high traffic flows
which can be considered as a phase transition [see review
of related research in (Smith 2008, pp. 1–31)].
Another important example of emergence in web-based
systems is social bookmarking (also called collaborative tagging). In social bookmarking systems, users assign tags to resources shared with other users, which
gives rise to a type of information organisation that
emerges from this crowdsourcing process. Recent research which analyzes empirically the complex dynamics of such systems[22] has shown that consensus on stable distributions and a simple form of shared vocabularies does indeed emerge, even in the absence of a central
controlled vocabulary. Some believe that this could be
because users who contribute tags all use the same language, and they share similar semantic structures underlying the choice of words. The convergence in social tags
may therefore be interpreted as the emergence of structures as people who have similar semantic interpretation
collaboratively index online information, a process called
semantic imitation.[23] [24]
Open-source software, or Wiki projects such as
Wikipedia and Wikivoyage are other impressive examples of emergence. The “zeroeth law of Wikipedia”
is often cited by its editors to highlight its apparently
surprising and unpredictable quality: The problem with
Wikipedia is that it only works in practice. In theory, it
can never work.
Architecture and cities
Emergent structures appear at many different levels of
organization or as spontaneous order. Emergent selforganization appears frequently in cities where no planning or zoning entity predetermines the layout of the
54
microbes that populate and evolve.[25][26][27]
Traffic patterns in cities can be seen as an example of spontaneous
order
Eric Bonabeau’s attempt to define emergent phenomena
is through traffic: “traffic jams are actually very complicated and mysterious. On an individual level, each driver
is trying to get somewhere and is following (or breaking)
certain rules, some legal (the speed limit) and others societal or personal (slow down to let another driver change
into your lane). But a traffic jam is a separate and distinct entity that emerges from those individual behaviors.
Gridlock on a highway, for example, can travel backward
for no apparent reason, even as the cars are moving forward.” He has also likened emergent phenomena to the
analysis of market trends and employee behavior.[28]
Computational emergent phenomena have also been
utilized in architectural design processes, for example for formal explorations and experiments in digital
city. (Krugman 1996, pp. 9–29) The interdisciplinary materiality.[29]
study of emergent behaviors is not generally considered
a homogeneous field, but divided across its application or
6.7.2 Computer AI
problem domains.
Architects and Landscape Architects may not design all Some artificially intelligent computer applications utilize
the pathways of a complex of buildings. Instead they emergent behavior for animation. One example is Boids,
might let usage patterns emerge and then place pavement which mimics the swarming behavior of birds.
where pathways have become worn in.
The on-course action and vehicle progression of the 2007
Urban Challenge could possibly be regarded as an example of cybernetic emergence. Patterns of road use, indeterministic obstacle clearance times, etc. will work together to form a complex emergent pattern that can not
be deterministically planned in advance.
The architectural school of Christopher Alexander takes
a deeper approach to emergence attempting to rewrite the
process of urban growth itself in order to affect form,
establishing a new methodology of planning and design
tied to traditional practices, an Emergent Urbanism. Urban emergence has also been linked to theories of urban
complexity (Batty 2005) and urban evolution (Marshall
2009).
Building ecology is a conceptual framework for understanding architecture and the built environment as the
interface between the dynamically interdependent elements of buildings, their occupants, and the larger environment. Rather than viewing buildings as inanimate or
static objects, building ecologist Hal Levin views them
as interfaces or intersecting domains of living and nonliving systems.[25] The microbial ecology of the indoor
environment is strongly dependent on the building materials, occupants, contents, environmental context and the
indoor and outdoor climate. The strong relationship between atmospheric chemistry and indoor air quality and
the chemical reactions occurring indoors. The chemicals
may be nutrients, neutral or biocides for the microbial
organisms. The microbes produce chemicals that affect
the building materials and occupant health and well being. Humans manipulate the temperature and humidity
to achieve comfort with the concomitant effects on the
6.7.3 Language
It has been argued that the structure and regularity
of language--grammar, or at least language change, is
an emergence phenomenon (Hopper 1998).While each
speaker merely tries to reach his or her own communicative goals, he or she uses language in a particular way. If
enough speakers behave in that way, language is changed
(Keller 1994). In a wider sense, the norms of a language,
i.e. the linguistic conventions of its speech society, can
be seen as a system emerging from long-time participation in communicative problem-solving in various social
circumstances. (Määttä 2000)
6.7.4 Emergent change processes
Within the field of group facilitation and organization development, there have been a number of new group processes that are designed to maximize emergence and selforganization, by offering a minimal set of effective initial
conditions. Examples of these processes include SEEDSCALE, Appreciative Inquiry, Future Search, the World
Cafe or Knowledge Cafe, Open Space Technology, and
others. (Holman, 2010)
6.8 See also
• Agent-based model
• Anthropic principle
6.9. REFERENCES
55
• Big History
• Swarm intelligence
• Causality
• System of Systems
• Chaos theory
• Teleology
• Complex systems
• Synergetics (Fuller)
• Connectionism
• Synergetics (Haken)
• Consilience
• Constructal theory
• Dynamical system
• Determinism
• Deus ex machina
• Emergenesis
• Emergent algorithm
• Emergent evolution
• Emergent gameplay
6.9 References
[1] http://plato.stanford.edu/entries/properties-emergent/
[2] Aristotle, Metaphysics, Book Η 1045a 8–10: "... the totality is not, as it were, a mere heap, but the whole is something besides the parts ...”, i.e., the whole is greater than
the sum of the parts.
[3] “The chemical combination of two substances produces,
as is well known, a third substance with properties different from those of either of the two substances separately,
or of both of them taken together” (Mill 1843)
• Externality
[4] Julian Huxley: “now and again there is a sudden rapid
passage to a totally new and more comprehensive type of
order or organization, with quite new emergent properties, and involving quite new methods of further evolution”
(Huxley & Huxley 1947)
• Flocking (behaviour)
[5] (Lewes 1875, p. 412)
• Fractals
[6] (Blitz 1992)
• Free will
[7] (Goldstein 1999)
• Generative sciences
• Holism
[8] Corning, Peter A. (2002), The Re-Emergence of “Emergence": A Venerable Concept in Search of a Theory, Complexity 7 (6): 18–30, doi:10.1002/cplx.10043
• Innovation butterfly
[9] (Bedau 1997)
• Emergent organization
• Epiphenomenon
• Interconnectedness
• Irreducible complexity
• Langton’s ant
• Law of Complexity/Consciousness
• Mass action
• Neural networks
• Organic Wholes of G.E. Moore
• Polytely
• Reductionism
• SEED-SCALE
• Society of Mind theory
• Structuralism
• Supervenience
[10] Gu, Mile, et al. "More really is different.” Physica D:
Nonlinear Phenomena 238.9 (2009): 835-839.
[11] Binder, P-M. “Computation: The edge of reductionism.”
Nature 459.7245 (2009): 332-334.
[12] Wheeler, Wendy (2006). The Whole Creature: Complexity, Biosemiotics and the Evolution of Culture. London:
Lawrence & Wishart. p. 192. ISBN 1-905007-30-2.
[13] Alexander, Victoria N. (2011). The Biologist’s Mistress:
Rethinking Self-Organization in Art, Literature, and Nature. Litchfield Park, AZ: Emergent Publications. ISBN
0-9842165-5-3.
[14] Daniel C. Taylor, Carl E. Taylor, Jesse O. Taylor, ‘’Empowerment on an Unstable Planet: From Seeds of Human
Energy to a Scale of Global Change’’ (New York: Oxford
University Press, 2012)
[15] See, e.g., Korotayev, A.; Malkov, A.; Khaltourina, D.
(2006), Introduction to Social Macrodynamics: Compact Macromodels of the World System Growth, Moscow:
URSS, ISBN 5-484-00414-4
56
[16] Steven Weinberg. “A Designer Universe?". Retrieved
2008-07-14. “A version of the original quote from address at the Conference on Cosmic Design, American Association for the Advancement of Science, Washington,
D.C. in April 1999”
• Bedau, Mark A. (1997), Weak Emergence
[17] “The origin of power-law emergent scaling in large binary
networks” D. P. Almond, C. J. Budd, M. A. Freitag, G.
W. Hunt, N. J. McCullen and N. D. Smith. Physica A:
Statistical Mechanics and its Applications, Volume 392,
Issue 4, 15 February 2013
• Koestler, Arthur (1969), A. Koestler & J. R.
Smythies, ed., Beyond Reductionism: New Perspectives in the Life Sciences, London: Hutchinson
[18] Steven Johnson. 2001. Emergence: The Connected Lives
of Ants, Brains, Cities, and Software
[19] Campbell, Neil A., and Jane B. Reece. Biology. 6th ed.
San Francisco: Benjamin Cummings, 2002.
[20] Miller, Peter. 2010. The Smart Swarm: How understanding flocks, schools, and colonies can make us better at
communicating, decision making, and getting things done.
New York: Avery.
[21] Carl Menger. “Principles of Economics”. Retrieved
05/07/2012. Check date values in: |accessdate= (help)
[22] Valentin Robu, Harry Halpin, Hana Shepherd Emergence
of consensus and shared vocabularies in collaborative tagging systems, ACM Transactions on the Web (TWEB),
Vol. 3(4), article 14, ACM Press, September 2009.
• Corning, Peter A. (1983), The Synergism Hypothesis: A Theory of Progressive Evolution, New York:
McGraw-Hill
• Laughlin, Robert (2005), A Different Universe:
Reinventing Physics from the Bottom Down, Basic
Books, ISBN 0-465-03828-X
6.11 Further reading
• Alexander, V. N. (2011). The Biologist’s Mistress:
Rethinking Self-Organization in Art, Literature and
Nature. Litchfield Park AZ: Emergent Publications.
• Anderson, P.W. (1972), More is Different:
Broken Symmetry and the Nature of the Hierarchical Structure of Science, Science 177
(4047): 393–396, Bibcode:1972Sci...177..393A,
doi:10.1126/science.177.4047.393,
PMID
17796623
[23] Fu, Wai-Tat; Kannampallil, Thomas George; Kang,
Ruogu (August 2009), A Semantic Imitation Model of Social Tagging, Proceedings of the IEEE conference on Social
Computing: 66–72, doi:10.1109/CSE.2009.382, ISBN
978-1-4244-5334-4
• Barabási, Albert-László; Jeong, Hawoong; Albert,
Réka (1999), The Diameter of the World Wide
Web, Nature 401 (6749): 130–131, arXiv:condmat/9907038,
Bibcode:1999Natur.401..130A,
doi:10.1038/43601
[24] Fu, Wai-Tat; Kannampallil, Thomas; Kang, Ruogu; He,
Jibo (2010), Semantic Imitation in Social Tagging, ACM
Transactions on Computer-Human Interaction (TOCHI) 17
(3): 1, doi:10.1145/1806923.1806926
• Bar-Yam, Yaneer (2004), A Mathematical Theory
of Strong Emergence using Multiscale Variety, Complexity 9 (6): 15–24, doi:10.1002/cplx.20029
[25] http://www.microbe.net/fact-sheet-building-ecology/
• Bateson, Gregory (1972), Steps to an Ecology of
Mind, Ballantine Books, ISBN 0-226-03905-6
[26] http://www.microbe.net
[27] http://buildingecology.com
[28] Bonabeau E. Predicting the Unpredictable. Harvard Business Review [serial online]. March 2002;80(3):109-116.
Available from: Business Source Complete, Ipswich, MA.
Accessed February 1, 2012.
[29] Roudavski, Stanislav and Gwyllim Jahn (2012). 'Emergent Materiality though an Embedded Multi-Agent System', in 15th Generative Art Conference, ed. by Celestino
Soddu (Lucca, Italy: Domus Argenia), pp. 348-363
6.10 Bibliography
• Anderson, P.W. (1972), More is Different:
Broken Symmetry and the Nature of the Hierarchical Structure of Science, Science 177
(4047): 393–396, Bibcode:1972Sci...177..393A,
doi:10.1126/science.177.4047.393,
PMID
17796623
• Batty, Michael (2005), Cities and Complexity, MIT
Press, ISBN 0-262-52479-1
• Bedau, Mark A. (1997).“Weak Emergence”.
• Blitz, David. (1992). Emergent Evolution: Qualitative Novelty and the Levels of Reality. Dordrecht:
Kluwer Academic.
• Bunge, Mario Augusto (2003), Emergence and Convergence: Qualitiative Novelty and the Unity of
Knowledge, Toronto: University of Toronto Press
• Chalmers, David J. (2002). “Strong and Weak
Emergence”
http://consc.net/papers/emergence.
pdf Republished in P. Clayton and P. Davies, eds.
(2006) The Re-Emergence of Emergence. Oxford:
Oxford University Press.
• Philip Clayton (2005). Mind and Emergence: From
Quantum to Consciousness Oxford: OUP, ISBN
978-0-19-927252-5
6.11. FURTHER READING
• Philip Clayton & Paul Davies (eds.) (2006). The ReEmergence of Emergence: The Emergentist Hypothesis from Science to Religion Oxford: Oxford University Press.
• Corning, Peter A. (2005). “Holistic Darwinism:
Synergy, Cybernetics and the Bioeconomics of Evolution.” Chicago: University of Chicago Press.
• Crutchfield, James P. (1994), “The Calculi of Emergence: Computation, Dynamics, and Induction”,
Special issue on the Proceedings of the Oji International Seminar: Complex Systems — from Complex
Dynamics to Artificial Reality, Physica D
• Felipe Cucker and Stephen Smale (2007), The
Japanese Journal of Mathematics, The Mathematics
of Emergence
• Delsemme, Armand (1998), Our Cosmic Origins:
From the Big Bang to the Emergence of Life and Intelligence, Cambridge University Press
• De Wolf, Tom; Holvoet, Tom (2005), “Emergence
Versus Self-Organisation: Different Concepts but
Promising When Combined”, Engineering Self Organising Systems: Methodologies and Applications,
Lecture Notes in Computer Science: 3464, pp. 1–15
• Fromm, Jochen (2004), The Emergence of Complexity, Kassel University Press, ISBN 3-89958-069-9*
Fromm, Jochen (2005a), Types and Forms of Emergence, arXiv, arXiv:nlin.AO/0506028
57
• Hopfield, JJ (1982), Neural networks and physical systems with emergent collective computational
abilities, Proc. Natl. Acad. Sci. USA 79
(8): 2554–2558, Bibcode:1982PNAS...79.2554H,
doi:10.1073/pnas.79.8.2554, PMC 346238, PMID
6953413
• Hopper, P. 1998. Emergent Grammar. In:
Tomasello, M. eds. 1998. The new psychology
of language: Cognitive and functional approaches
to language structure. Mahwah, NJ: Earlbaum, pp.
155–176.
• Huxley, Julian S.; Huxley, Thomas Henry (1947),
Evolution and Ethics: 1893-1943, London, 1947:
The Pilot Press, p. 120
• Johnson, Steven Berlin (2001), Emergence: The
Connected Lives of Ants, Brains, Cities, and Software, Scribner’s, ISBN 0-684-86876-8
• Kauffman, Stuart (1993), The Origins of Order: SelfOrganization and Selection in Evolution, Oxford University Press, ISBN 0-19-507951-5
• Keller, Rudi (1994), On Language Change: The
Invisible Hand in Language, London/New York:
Routledge, ISBN 0-415-07671-4
• Kauffman, Stuart (1995), At Home in the Universe,
New York: Oxford University Press
• Fromm, Jochen (2005b), Ten Questions about Emergence, arXiv, arXiv:nlin.AO/0509049
• Kelly, Kevin (1994), Out of Control: The New Biology of Machines, Social Systems, and the Economic
World, Perseus Books, ISBN 0-201-48340-8
• Goodwin, Brian (2001), How the Leopard Changed
Its Spots: The Evolution of Complexity, Princeton
University Press
• Koestler, Arthur (1969), A. Koestler & J. R.
Smythies, ed., Beyond Reductionism: New Perspectives in the Life Sciences, London: Hutchinson
• Goldstein, Jeffrey (1999), Emergence as a
Construct:
History and Issues, Emergence:
Complexity and Organization 1 (1): 49–72,
doi:10.1207/s15327000em0101_4
• Korotayev, A.; Malkov, A.; Khaltourina, D. (2006),
Introduction to Social Macrodynamics: Compact
Macromodels of the World System Growth, Moscow:
URSS, ISBN 5-484-00414-4
• Haag, James W. (2008). Emergent Freedom: Naturalizing Free Will Goettingen: Vandenhoeck &
Ruprecht, ISBN 978-3-525-56988-7
• Krugman, Paul (1996), The Self-organizing Economy, Oxford: Blackwell, ISBN 1-55786-698-8,
"ISBN 0-87609-177-X"
• Hayek, Friedrich (1973), Law, Legislation and Liberty, ISBN 0-226-32086-3
• Laughlin, Robert (2005), A Different Universe:
Reinventing Physics from the Bottom Down, Basic
Books, ISBN 0-465-03828-X
• Hofstadter, Douglas R. (1979), Gödel, Escher, Bach:
an Eternal Golden Braid, Harvester Press
• Holland, John H. (1998), Emergence from Chaos
to Order, Oxford University Press, ISBN 0-73820142-1
• Leland, W.E.; Willinger, M.S.; Taqqu, M.S.;
Wilson, D.V. (1994), On the self-similar nature of Ethernet traffic (extended version),
IEEE/ACM Transactions on Networking 2: 1–
15, doi:10.1109/90.282603
• Holman, Peggy. (2010). Engaging Emergence:
Turning upheaval into opportunity. San Francisco:
Barrett-Koehler. ISBN 978-1-60509-521-9
• Lewes, G. H. (1875), Problems of Life and Mind
(First Series) 2, London: Trübner, ISBN 1-42555578-0
58
• Lewin, Roger (2000), Complexity - Life at the Edge
of Chaos (second ed.), University of Chicago Press,
ISBN 0-226-47654-5, "ISBN 0-226-47655-3"
• Wan, Poe Yu-ze (2011), Reframing the Social:
Emergentist Systemism and Social Theory, Ashgate
Publishing
• Ignazio Licata & Ammar Sakaji (eds) (2008).
Physics of Emergence and Organization, ISBN 978981-277-994-6, World Scientific and Imperial College Press.
• Weinstock, Michael (2010), The Architecture of
Emergence - the evolution of form in Nature and
Civilisation, John Wiley and Sons, ISBN 0-47006633-4
• Määttä, Urho (2000), Mistä on pienet säännöt tehty?,
Virittäjä 2: 203–221
• Wolfram, Stephen (2002), A New Kind of Science,
ISBN 1-57955-008-8
• Marshall, Stephen (2009), Cities Design and Evolution, Routledge, ISBN 978-0-415-42329-8, "ISBN
0-415-42329-5"
• Mill, John Stuart (1843), “On the Composition of
Causes”, A System of Logic, Ratiocinative and Inductive (1872 ed.), London: John W. Parker and Son,
p. 371
• Morowitz, Harold J. (2002), The Emergence of Everything: How the World Became Complex, Oxford
University Press, ISBN 0-19-513513-X
• Young, Louise B. (2002), The Unfinished Universe,
ISBN 0-19-508039-4
6.12 External links
• Emergence entry in the Internet Encyclopedia of Philosophy
• Emergent Properties entry in the Stanford Encyclopedia of Philosophy
• Emergence at PhilPapers
• Ryan, Alex J. (2006), Emergence is Coupled to
Scope, not Level, Complexity (arXiv), (to be submitted), arXiv:nlin.AO/0609011
• Emergence at the Indiana Philosophy Ontology
Project
• Schelling, Thomas C. (1978), Micromotives and
Macrobehaviour, W. W. Norton
• The Emergent Universe: An interactive introduction to emergent phenomena, from ant colonies to
Alzheimer’s.
• Jackie (Jianhong) Shen (2008), Cucker–Smale
Flocking Emergence under Hierarchical Leadership
In: SIAM J. Applied Math., 68:3,
• Exploring Emergence: An introduction to emergence using CA and Conway’s Game of Life from
the MIT Media Lab
• Smith, John Maynard; Szathmáry, Eörs (1997), The
Major Transitions in Evolution, Oxford University
Press, ISBN 0-19-850294-X
• ISCE group: Institute for the Study of Coherence
and Emergence.
• Smith, Reginald D. (2008), The Dynamics of Internet Traffic: Self-Similarity, Self-Organization,
and Complex Phenomena 0807, arXiv, p. 3374,
arXiv:0807.3374, Bibcode:2008arXiv0807.3374S
• Solé, Ricard and Goodwin, Brian (2000) Signs of
life: how complexity pervades biology, Basic Books,
New York.
• Steels, Luc (1990), “Towards a Theory of Emergent
Functionality”, in Jean-Arcady Meyer; Stewart W.
Wilson, From Animals to Animats (Proceedings of
the First International Conference on Simulation of
Adaptive behaviour), Cambridge, MA & London,
England: Bradford Books (MIT Press), pp. 451–
461
• Wan, Poe Yu-ze (2011), “Emergence a la Systems
Theory: Epistemological Totalausschluss or Ontological Novelty?", Philosophy of the Social Sciences,
41(2), pp. 178–210
• Towards modeling of emergence: lecture slides
from Helsinki University of Technology
• Biomimetic Architecture - Emergence applied to
building and construction
• Studies in Emergent Order: Studies in Emergent Order (SIEO) is an open-access journal
• Emergence
6.13. TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES
59
6.13 Text and image sources, contributors, and licenses
6.13.1
Text
• Creativity Source: http://en.wikipedia.org/wiki/Creativity?oldid=630746700 Contributors: AxelBoldt, Tbackstr, SimonP, Jose Icaza,
Norm, Ahoerstemeier, Ronz, Tim Retout, Nikai, Rl, Aion, Selket, Pedant17, Buridan, Fvw, Dbabbitt, Pumpie, Robbot, Petermanchester, Clngre, Jfire, DHN, Seth Ilys, Alerante, Sethoeph, DocWatson42, Jyril, HangingCurve, Everyking, Guanaco, Skagedal, Christopherlin, Andycjp, Phil Sandifer, Gscshoyru, WpZurp, Hugh Mason, Klemen Kocjancic, D6, CALR, Rich Farmbrough, Vsmith, Bishonen, User2004, Notinasnaid, Pavel Vozenilek, ESkog, Lycurgus, Mwanner, Alex Kosorukoff, RoyBoy, Bobo192, Johnkarp, Smalljim,
Adraeus, Keron Cyst, Elipongo, Maurreen, Blotwell, Nlight, Helix84, Pearle, Officiallyover, Jumbuck, Danski14, Alansohn, Somberi,
Andrew Gray, Logologist, SlimVirgin, Fivetrees, P Ingerson, Kusma, Dd2, Mahanga, Ott, Kelly Martin, RHaworth, Morning star, Iccincsm, Unixer, Benbest, CharlesC, Pictureuploader, Liface, Palica, Marudubshinki, Seishirou Sakurazuka, JiMidnite, Sparkit, Kbdank71,
JIP, Josh Parris, Rjwilmsi, Scandum, TheRingess, DouglasGreen, Klonimus, Protez, Moskvax, SchuminWeb, Pavlo Shevelo, AED, Estrellador*, Nihiltres, RexNL, AndriuZ, =Julius=, Drumguy8800, Aeroknight, Ckostovny, DVdm, YurikBot, Wavelength, Borgx, RussBot, Pigman, Nesbit, Stephenb, Gaius Cornelius, Clam0p, Epim, Cognition, Topperfalkon, PhilipO, RUL3R, Natkeeran, Action potential, Mysid, Igiffin, Theda, Josh3580, Livitup, GraemeL, Danny-w, Fram, SigmaEpsilon, Dobjsonne, Bluezy, Jeff Silvers, Victor falk,
Veinor, Cowdinosaur, SmackBot, Marcusscotus1, Prodego, McGeddon, Jtneill, Swerdnaneb, GraemeMcRae, Gilliam, Ohnoitsjamie,
Frankahilario, Chris the speller, TimBentley, Whywhywhy, Oli Filth, Apeloverage, Uthbrian, Oni Ookami Alfador, Colonies Chris, Katsesama, Darth Panda, Magenta1, Ddon, Harnad, John D. Croft, Aaker, Ligulembot, Jashank, Vina-iwbot, Blauhaus, Cookie90, Will
Beback, Byelf2007, SashatoBot, Arnoutf, Trojan traveler, Kingfish, Kuru, Khazar, Lakinekaki, Andrewjuren, Teal6, Masahiko, Ckatz,
RichardF, David.alex.lamb, Hu12, MikeWazowski, Iridescent, Sameboat, JoeBot, Badly, Mh29255, ACEO, Timwarneka, TheSmartDoccer, BrettRob, JForget, Robin de lange, Wolfdog, CmdrObot, Wafulz, LMackinnon, Lighthead, Erencexor, Penbat, Isaacdealey, Gregbard,
Jac16888, Cydebot, Gogo Dodo, Mattergy, Anthonyhcole, Afzalraza, Dr.enh, Englishnerd, Letranova, Epbr123, Qwyrxian, Ishdarian,
Chickenflicker, Amirelion, West Brom 4ever, VoteFair, Transhumanist, Mentifisto, Gioto, Thebridge, Rlanda, TimVickers, JAnDbot,
Wk1, Spiriman, The Transhumanist, Wfxy, Thinkertoy, Xeno, Cre8tive19, Rainingblood667, Jarkeld, Acroterion, Geniac, Magioladitis, PrimroseGuy, Bakilas, Creatology, Sarahj2107, Bfiene, Tedickey, Tremilux, Tonyfaull, Terjen, Spellmaster, JaGa, Oicumayberight,
Yelir61, Gwern, MartinBot, R'n'B, Tulkolahten, All Is One, Dbiel, Sanjaydalal, J 32, Bigsnoop7, Tcaudilllg, Christian Storm, Plasticup,
LittleHow, Belovedfreak, TomasBat, Brian Pearson, KylieTastic, Cometstyles, STBotD, Ichisan, Funandtrvl, Spellcast, Nievved, Lights,
ABF, Leopold Stotch, Leebo, Jennavecia, Station1, Philip Trueman, TXiKiBoT, Aleliv, Deleet, Davehi1, Creativeprofessional, Abbw254,
Raymondwinn, Elizabethpardo, Uannis, Billinghurst, Lova Falk, Wikidan829, Kusyadi, Cnilep, Why Not A Duck, Chenzw, MrChupon,
C0N6R355, Jongrover, OsamaK, Jean-Louis Swiners, Gil Dekel, Enkyo2, Quietbritishjim, SieBot, Calliopejen1, Nihil novi, Meldor, Dawn
Bard, Caltas, Loxlok, Flyer22, Tiptoety, Pedrodurruti, CutOffTies, Sunrise, Filam3nt, CharlesGillingham, ThisGuy62, Mr. Stradivarius,
Me-macias, ClueBot, GorillaWarfare, Bob1960evens, Rjd0060, John ellenberger, WMCEREBELLUM, Vlaze, Mild Bill Hiccup, Dannyguillory, Travis.m.granvold, Dvash, TheOldJacobite, Anat Rafaeli, Roman Eisele, Eolanys, Dr.orfannkyl, Goldsm, Bracton, Iohannes
Animosus, Tnxman307, VsevolodKrolikov, Redthoreau, SchreiberBike, Redfang60, DWmFrancis, Mikhailov Kusserow, Taranet, Thingg,
Aitias, Johnuniq, SoxBot III, Generativity, Ceri sullivan, Jengirl1988, XLinkBot, Rror, Jordanrambo, Mr andrea, WikHead, RealDracaena,
Vcorani, Addbot, Some jerk on the Internet, Pilibin, DOI bot, Dmccuesm, Af042, Prithu22, Leszek Jańczuk, USchick, Jefflithe, MrOllie, Download, Sara USA, Redheylin, Glane23, Kyle1278, Alex Rio Brazil, Tide rolls, Slgcat, Jackelfive, Luckas-bot, Yobot, Pink!Teen,
Fraggle81, Georgi.dimitrov, Victoriaearle, Fourmiz59, Maxí, Soiregistered, Burningjoker, AnomieBOT, SteveMX, VulcanOtaku, IRP, Galoubet, WillRabbit, 9258fahsflkh917fas, Piano non troppo, Crecy99, 90 Auto, Citation bot, GB fan, Frankenpuppy, J-E-N-O-V-A, Xqbot,
Dev2587, Tudorrickards, Gondwanabanana, RedAlgorithm, Nasnema, Justykim, Sellyme, Topilsky, The Evil IP address, Pierkolp, Kevdave, Omnipaedista, Danceron, Cresix, Propagator, Auréola, Asimzaidi, Matchtime, Aaron Kauppi, SD5, Ryangfloyd, FrescoBot, Dorimedont, Rjlx, StaticVision, Imbecileler, Skunksforever, Haeinous, E.shakir, Lebd, Hexagon70, Citation bot 1, Gdje je nestala duša svijeta,
Asnav, Annajordanous, Pinethicket, Chudhudson, Mahtabshadi, Koakhtzvigad, Jauhienij, Declan Clam, ItsZippy, SeoMac, Vezwyx, Tinystui, Danzen, Tbhotch, DARTH SIDIOUS 2, RjwilmsiBot, Alph Bot, Miles slow, Tonygilloz, Saniasoone, Sharlotte29, Jonmc, Cbrookca,
John of Reading, Fgasj, Alysakiwi, AgRince, Vkeller, Quesco, Sepguilherme, ZéroBot, Tranhungnghiep, JaneKT, Traxs7, WeijiBaikeBianji, Mar4d, MindShifts, Evereadyo2, H3llBot, Jay-Sebastos, Krvishal, Zveta, Senseagent230, Donner60, Gem131, J76392, CSMasick,
ChuispastonBot, AndyTheGrump, HandsomeFella, Khannashweta2, LaurMG, TYelliot, Miradre, Woodsrock, Ideas at the Bottom, ClueBot NG, Mochomio, Zyrdorn, Jj1236, Divinecomedy666, Widr, Kalyan79, Uatmedia, North Atlanticist Usonian, Helpful Pixie Bot, Raafat
Karimi, Footnotes2plato, Wbm1058, Nashhinton, BG19bot, Robfiscerr, Maurice Barnwell, Jls517, Subarctica, MusikAnimal, Smcg8374,
Frze, Belleville3, Chris the Paleontologist, Mark Arsten, UrbanIndianSF, JesseColton, DPL bot, Realdaytoday, Nikkiopelli, Piggykid1,
Rowan Adams, Psywikiuser, Dimanchebelleville, Gowhar2, Johncalhoun21, Dreinkin, CourtChru., Hlack11, Pratyya Ghosh, Acadēmica
Orientālis, Dgonz4psy, ChrisGualtieri, Ekren, Guido Brandt Corstius, IjonTichyIjonTichy, K7L, Cogcerebellum, Numbermaniac, Frosty,
Ranjithraj, Doctor Girl, Greenfuturefinder, Maria.tomassetti, Vanamonde93, PenDavid, Ruby Murray, Odysseyhq, Jamesmcmahon0, SinnerShanky, Tivity, Satoshi Mochizuki, Johnemoag6, Ssdco, IvanderClarent, Hiba social, Zamomin, Mark Matthew Dalton, Dvorak182,
Quenhitran, Zyouwen, FireflySixtySeven, Changer9451, TheFlash1123, Creares, Abdollahi100, Amuzesh, Monkbot, Regalizzz, Filedelinkerbot, Reylyn.Dizon, KennethAlexanderStevens, Gcattani, Qsubject, OsFish and Anonymous: 506
• Computational creativity Source: http://en.wikipedia.org/wiki/Computational_creativity?oldid=630338595 Contributors: Michael
Hardy, Ronz, Bfinn, Risk one, Jason Quinn, Beland, Jokestress, DreamGuy, Ketiltrout, Koavf, Quuxplusone, Spencerk, TimDuncan,
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Banner, FrescoBot, DDekov, Zero Thrust, Citation bot 1, Periksson28, Annajordanous, MatthiBorif, JCAILLAT, Arided, SporkBot,
Ajordanous, Arv100.kri, EvaJamax, Wbm1058, BG19bot, DPL bot, Quipa, Cerabot, TheBeardofLenin, Terraforming, Nahhhhhh, Tivity,
Midnightplunge, Kusiana, Shibbuleth, Ashleytway and Anonymous: 44
• Ideation (idea generation) Source: http://en.wikipedia.org/wiki/Ideation_(idea_generation)?oldid=612084374 Contributors: Michael
Hardy, Kku, Ronz, Charles Matthews, Chealer, Sunray, Alan Liefting, Samuel J. Howard, Pgan002, Vivacissamamente, Aaronbrick, Prsephone1674, Pearle, Fivetrees, Moba2k, Mattbrundage, Nilloc, Davidp, Blowdart, Mdboxberger, Patiwat, SmackBot, Bluebot, Myownmyth,
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VolkovBot, Ilyushka88, ClueBot, Lexpark studio, Mbrady2424, Rumbird, DumZiBoT, Noamdanon, MrOllie, Yobot, Nasa-verve, Telical,
Unialpha, Jandalhandler, Whiteanimal25, Snotbot, Adamo8925, Soulparadox, PenDavid, Goyah, TrystynAlxander, Robert McFadden and
Anonymous: 37
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Heron, Ryguasu, Olivier, D, Michael Hardy, Metatron, Mac, Ronz, Norman Fellows, Glenn, Andres, Iseeaboar, David Newton, Ike9898,
Wik, Robbot, Jredmond, Altenmann, Wikibot, Johnstone, Dbroadwell, Dina, Carnildo, Alan Liefting, Lysy, BenFrantzDale, Tom harrison, Everyking, Bensaccount, Bovlb, Alvestrand, Chowbok, Kusunose, Maximaximax, Grunners, Zro, Sysy, CALR, Discospinster, Rich
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Mdd, Jumbuck, Zachlipton, Bart133, Snowolf, Max Naylor, Sciurinæ, Buoren, Versageek, Netkinetic, Ironwolf, Abanima, Nigel Cross,
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Shel, Soc8675309, Jnthn0898, Airborne84, Takharii, Abraham70, Teuxe, Davinapo, MacMed, Pinethicket, HRoestBot, 10metreh, Qaismx,
Calmer Waters, SpaceFlight89, Paulralph, GreenGrammarian, Pyxzer, SchreyP, Asherrard, Topspinserve, Ingi.b, Vrenator, Bluefist, Reaper
Eternal, Style3000, Mistywest, Ballparx, NathDZ., EmausBot, Avenue X at Cicero, Gfoley4, Madyokel, RA0808, Simonchalky, Daniela
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Averaver, Wenttomowameadow, Inci siker asd, Jj98, Zenao1, Donner60, Grizanthropy, Ems2715, Mb bs, Labargeboy, Dj Mario8, DASHBotAV, StanC8, IrinaSztukowski, ResearchRave, Helpsome, Will Beback Auto, ClueBot NG, Gallura, Joshuagnizak, Yemreh, Snailwiki,
O.Koslowski, Widr, FrauKramer, A3dinnovation, Emmabrock, Helpful Pixie Bot, BG19bot, Tgdmatters, Maurice Barnwell, Wiki13, Matt
Chase, Vijayjoseph, Parmeshvarsharma, Da wanga, Naderi ds, Hhh0000, Aniston9, Daytonarolexboston, Donskum, Ezyoncat, Insidiae,
Poojagrawal, Tnuocca987456321, BellBoy32, Designergene, Cyberbot II, DisruptiveTigers, Faadhil2, Kushalbiswas777, Daddi1991, Bizworldusaanu, Graphium, Cody369, 8ty3hree, Supercoolguystyle123, Consider42, Lemnaminor, Kuyi123w, Uwais Jahmeerbacus, Goyah,
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Gadehi, TerryAlex, Kesterton and Anonymous: 551
• Creativity techniques Source: http://en.wikipedia.org/wiki/Creativity_techniques?oldid=628146517 Contributors: Jose Icaza, Ronz, Rl,
Furrykef, HangingCurve, Skagedal, Khalid hassani, Edcolins, Discospinster, Nabla, Mwanner, Alex Kosorukoff, Ziggurat, Espoo, Alansohn, Andrew Gray, Fivetrees, Clubmarx, RHaworth, BD2412, Kbdank71, AllanBz, Rjwilmsi, AndriuZ, Kollision, C777, Epim, Lt-wikibot, Veinor, A bit iffy, SmackBot, Swerdnaneb, Dbschlosser, Blairmain, Fuhghettaboutit, Abmac, Derek R Bullamore, Oppix, FlyHigh, CreativeConcepts, Corza, Chas martin, Noah Salzman, Hu12, Fan-1967, Iridescent, TheSmartDoccer, BrettRob, Dancter, Crinnology, VoteFair, Transhumanist, SvenAERTS, Thinkertoy, Cre8tive19, Acroterion, Seamusclifford, Dontheideaguy, JaGa, Oicumayberight, Yelir61,
Grandia01, Ideamapping, The dark lord trombonator, Thaurisil, DOLhades, Tkgd2007, Lova Falk, RSStockdale, ClueBot, Leestubbs, ExoTiger, VsevolodKrolikov, Jengirl1988, XLinkBot, Badgernet, Addbot, MrOllie, Sara USA, Korhanerel, Jarble, Luckas-bot, Creativeuser2,
Themfromspace, FireMouseHQ, Amirobot, AnomieBOT, Inseok, Innovatorglobal, Xqbot, Crzer07, Song of the South, Matchtime, I dream
of horses, Dukeofgaming, Trelawnie, Gregrjones, Kdunnohew, Danzen, JaneKT, Oleyea, Uatmedia, Northamerica1000, PenDavid, Goyah,
Adirlanz, Photofinish123, Corvus Park, Kialou and Anonymous: 67
• Emergence Source: http://en.wikipedia.org/wiki/Emergence?oldid=629028443 Contributors: CYD, The Anome, WillWare,
ChangChienFu, Heron, Bdesham, Michael Hardy, Owl, Lexor, Pnm, Karada, Ronz, Angela, Andres, Palfrey, Pipis, TonyClarke,
Technopilgrim, Ec5618, RodC, Charles Matthews, Nickg, Greenrd, Jeffrey Smith, Jerzy, Banno, Tlogmer, Vespristiano, Chopchopwhitey,
Steeev, Rursus, Blainster, Wikibot, Aetheling, Paul Murray, Aknxy, Jleedev, Stirling Newberry, Ancheta Wis, Giftlite, Gwalla, Tom
harrison, SantiagoGala, Henry Flower, Leonard G., Finn-Zoltan, Edcolins, John Abbe, Andycjp, Loremaster, Karol Langner, BookgirlST,
Histrion, Talrias, Jmeppley, IcycleMort, Robin klein, Andreas Kaufmann, Chris Howard, MiddleOfNowhere, Rich Farmbrough, Dbachmann, Pavel Vozenilek, Goochelaar, Bender235, ESkog, Ben Standeven, El C, Vipul, Aaronbrick, Ray Dassen, Mike Schwartz, C S, Teorth,
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John2000, Rintrah, Ksyrie, Arkapravo, DarkFireTaker, BlackAndy, Thiseye, Slarson, Adamrush, Rbarreira, Shadowfax0, Larry laptop,
Moe Epsilon, LodeRunner, Epipelagic, MBDowd, WAS 4.250, HereToHelp, Raveled, Curpsbot-unicodify, MagneticFlux, Bwiki, Luk,
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6.13. TEXT AND IMAGE SOURCES, CONTRIBUTORS, AND LICENSES
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Inferior Olive, Reaper Eternal, Catcamus, Bento00, Djjr, EmausBot, Rusfuture, Irvbesen, GoingBatty, Tuxedo junction, Alpha Quadrant,
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Chapter 1 Creativity

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