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Computer Aided Creativity: Practical Experience and
Theoretical Concerns
Robert Pepperell
School of Art, Media and Design, University of Wales College, Newport
Caerleon Campus, Newport NP18 3YH UK
+44 (0)1633 432642 pepperell@ntlworld.com
ABSTRACT
In this paper I will outline some of the practical experiences
and theoretical concerns that have informed some 15 years
of research into the relationship between human creativity
and technology. I will discuss a number of approaches to
the design of effective creativity enhancing systems and
identify the key theoretical concerns that have informed the
practical research. Finally, I will present some conclusions
about the nature of human and synthetic creativity arising
from my published work. At conference the paper will be
presented using a variety of audio-visual illustrations.
Keywords
Ambiguity, collaboration, complexity, discontinuity, post-
humanism, randomness
INTRODUCTION
My first encounter with computer technology within the
context of art practice came at the end of my graduate
programme in Fine Art at Newport School of Art in 1986.
The course leader at that time was Roy Ascott, the
influential telematic theorist, who invited me to assist in a
number of international computer networking projects at
venues such as the Venice Biennale and Ars Electronica.
During my subsequent postgraduate studies at the Slade
School of Art in London I became increasingly interested
in the artistic and creative potential of computer
technologies, not just as a medium of global
communication but also in the direct production and
manipulation of sound, text and images. There were two
issues that intrigued me: first, the potential for automation
of various creative processes such as image generation,
music sequencing or writing and, second, the potential for
the creation of images of semantic ambiguity and
indeterminacy.
AUTONOMOUS AUTOMATED CREATIVITY
The first issue stemmed from the proposition that many of
the creative decisions made in video editing suites, music
composition studios and during graphic layout exercises
often involve a significant degree of randomness. First
hand experience gained in making pop videos, composing
music with sequencers and producing desktop published
artwork in the years immediately following my exit from
the Slade confirmed to my mind, and to those of my
colleagues, that many time-intensive processes integral to
such activities might, to some extent, be susceptible to
automation. For example, any designer faced with
producing a poster layout will spend a significant amount
of their (often expensive) time making choices from
numerous possible typefaces, colour schemes, content
orientations and the relative positioning of elements. At the
same time, these potentially inexhaustible choices are
limited by certain constraints such as the paper size, the
clarity and balance of organisation, the scale and legibility
of elements, conformity to certain stylistic or formal rules,
not to say budgets and other financial determinants. Around
1988 we envisioned a general system that would
autonomously produce multiple random variations of any
creative object within certain limits set by the user who
would be then free to ‘select’ the output variation best fitted
the design requirements. In many ways the idea was
inspired by natural evolution and, in particular, the
‘Biomorphs’ of Richard Dawkins [1], who had previously
modeled genetic formulae to striking visual effect, as well
as the work of William Latham [2] and the IBM research
labs whose computer-evolved organic shapes were widely
disseminated at the time. Our early experiments with
computer generated images, music and digital typography
were necessarily crude given the lack of any research
funding and the poor capabilities of the computers we were
using (low-specification Acorn Archimedes and Apple Mac
Classics). Nevertheless, the results were sufficiently
encouraging to spur further investigation, whilst it became
clear that problems of producing ‘interesting’ material
using random data generation were more profound than we
first assumed. Although it was not immediately obvious to
us, any information theorist would have been able to point
out that the random generation of data will produce a high
level of noise in proportion to signal – the signal being the
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interesting material we hoped to generate and the noise
being the ‘uninteresting’, i.e. tedious or unintelligible,
material which formed the bulk of the computer output.
Through these investigations it became increasingly clear
that creative activity, whether human or machine-based,
would operate in a way consistent with other natural
phenomena in the Universe, conforming in particular to the
Second Law of Thermodynamics, which describes the
relationship between order, randomness and the exchange
of energy; in short, you don’t get anything useful for free.
The probability of producing noise from a random
configuration of any given matter is much greater that the
probability of creating a signal; that is, some improbable
configuration that would interest a human. Since the
creation of human life itself is one striking example of such
an improbable configuration of matter and energy in the
Universe, it should not be surprising that life-dependent
processes such as creativity might operate in a related way.
Randomness is comparatively cheap and therefore of less
value than order, which can be very expensive in terms of
the ‘cost’ of energy required to sustain it. Hence, surface
life on Earth needs a continuous source of ‘free’ energy
from the Sun. For our part, the energetic cost, as it were, of
sustaining interesting output from random data generation
was incurred by the need to construct ever-more
sophisticated rules, or constraints, which limited the
parameters of the random behaviour so as to provide a
greater probability of organised output. In the case of music
composition for example, one needs to provide rules about
tempo, syncopation, harmony, melody and so on, without
which one tends to get a formless yet repetitive cacophony.
But the excessive imposition of rules can lead equally to
tedium of a different kind: a product with no variation,
deviation or surprise. As Ernst Gombrich elegantly
declared in A Sense of Order [3]:
“. . . however we analyse the difference between the
regular and the irregular, we must ultimately be able
to account for the most basic fact of aesthetic
experience, the fact that delight lies somewhere
between boredom and confusion.”
Since rigid compositional order can be as unstimulating as
scattered noise, we are forced to engage with the
complicated region between the two extremes where the
mathematical certainties of absolute order and disorder no
longer pertain — the realm, in fact, of complexity. We
pursued our researches into this region of complexity,
producing a number of computer generated music and
videos works in the late 1980s and early 1990s, which were
shown at film festivals, on television, in night-clubs, on
videos and interactive CD-ROMs and released as records
(see the Web site ‘www.stem-arts.com/hex.htm’ for
examples). While these products were of some limited
commercial and critical success (and were able to
financially sustain our research) we were still unsatisfied
with the quality of the output which was not always
aesthetically pleasing, while the overheads of coding in
rules and constraints were often greater than the savings in
effort afforded by the automated creativity. It was almost
quicker to do things in the ‘old-fashioned’ way.
GENERATOR & COLLABORATIVE TECHNOLOGY
In the mid-1990s my attention turned away from
autonomous self-driven systems of automated creativity
toward more user activated, dynamic systems that
generated their output in response to continuous user input.
This research was initiated by a commission from the
Glasgow Gallery of Modern Art in 1995, for the
construction of an interactive exhibit in their newly built
‘Fire’ gallery — the first purpose built interactive gallery in
Britain. Prior to 1995 much of my experimental computer
art-work had been exhibited in night-clubs and at festivals
rather than conventional galleries, most of whom were
paying little attention to computer-based art (which is
largely still the case, although some of the blame for this
lies with the subsequent proliferation of ‘content-free’,
technology fixated works that were little more that
demonstrations of devices). In was whilst working in clubs
as a ‘VJ’ providing an ever-changing visual backdrop for
the DJs that I evolved certain techniques for the live mixing
of video sources which paralleled those techniques used by
DJs in the cutting and mixing of records. It was these
techniques of audio-visual manipulation that I attempted to
embed in the work produced for the Gallery of Modern Art,
entitled Generator [4].
Figure 1. Generator at the Glasgow Gallery of Modern Art
Generator consisted of two consoles supporting button
banks, a set of computers, a video projector and speakers.
One console controlled sound and the other images. The
buttons on the sound console were organised into three
rows each representing a channel of audio and into eight
columns each representing a common musical genre such
as rock, hip-hop, opera, jazz, and so on. By pressing
different buttons (each of which was labeled with icons) the
user with no previous musical training or aptitude could
select, say, a piece of rock music to play at the same time
as a piece of opera and a piece of hip-hop. The buttons
triggered audio sample loops that were stretched and
pitched so as to be compatible in tempo and tuning. The
result was an audio mix of three distinct (and unrelated)
music styles forming a harmonious, if somewhat unusual,
whole based on selections made by the user. Critical to the
operation of the system, however, was the fact that
although the user could choose a style such as hip-hop or
reggae, the actual clip played was chosen randomly by the
computer from a database of clips classified by style. The
selection of jazz would initiate the playing of one of many
possible jazz clips. Consequently, the global output of the
system was regulated by collaboration between the user’s
choices and the random selections of the computer; neither
had complete control. This collaborative aspect of the
human-computer interface offered by the Generator
distinguishes it from most other forms of machine
interaction where user actions normally initiate a
predictable response (with the exception of certain PC
operating systems). This automaton-like predictability is
almost the defining characteristic of a ‘machine’. In the
Generator the consequence of pressing a button was not
wholly predictable in that the user could influence but not
control the activity of the system. The second console
supported a similar set of buttons, each of which triggered
video sequences arranged and selected in an identical way
to the sounds. For the user, then, the overall experience was
one of real-time audio-visual mixing in which they were
able to significantly influence the composition of the sound
and images, but were not able to precisely control them.
Private research commissioned by the gallery into the
public response to the piece showed a high level of
audience satisfaction, with many users reporting a genuine
sense of creative excitement when participating.
The experience of designing, constructing, installing and
operating Generator convinced me that such unpredictable,
collaborative technologies, as opposed to predictable,
passive ‘slave’ technologies, offered a potentially rich
method of enhancing human creativity. The advantage of
the method was that it allowed for a significant degree of
randomness, which produced great variation and
spontaneity, but was tempered by severe formal constraints
(of pitch and tempo) which prevented the descent into noise
or confusion. The user acted as an agent of both
randomness and order by causing the system to change in
ways it would not otherwise do and by creating novel
formal combinations that, to the user, were most interesting
or pleasing. The net result was a system operating in the
region of complexity between stasis and chaos where,
arguably, human creativity flourishes.
The success of Generator led to a series of further
commissions, most notably a piece called Synopticon in the
JAM exhibition at the Barbican Gallery in London in 1996
[5] and one called RAMJAM at the Nottingham Now!
Festival of Arts in 1997 [6]. These pieces extended the
methods used in Generator to include wider audience
participation. For example, RAMJAM consisted of a room
in a club filled with free-standing consoles supporting
many buttons, each linked to a sound sampler. As a DJ
played a series of backing tracks the audience (numbering
some 200) collectively triggered sound samples mixed
through the public address system. Thus the audience was,
in effect, ‘jamming’ along with the DJ. Initially the results
were fairly cacophonous as users simply pressed buttons
continuously. However, later in the evening the audience as
a whole seemed to realise that if some users left space other
users could fill, this would be reciprocated. This is a lesson
that anyone playing in a musical ensemble has to learn very
quickly. By about 2am the whole room was packed with
people ‘jamming’ along with each other and the DJ – a
truly exciting experience.
Figure 2. The Playtime interface from the Let Us Play CD-
ROM
The technique of collaborative interaction pioneered by
the Generator piece found further expression in a some
commercially released music composition software called
Playtime, released as part of the critically acclaimed CD-
ROM which accompanied the Let Us Play album produced
by Coldcut in 1997 [7]. Playtime, co-written by the author
and Miles Visman (who also collaborated on some of the
earlier art works) offered a series of sliders which modified
three banks of sound; drums loops, bass loops and ‘head
noises’. The audio loops would play in sequence with one
another to create music with an electronic ‘dance’ flavour.
Changing the position of the various sliders allowed the
user to manipulate the way in which the programme ‘cut-
up’ or rearranged the sound loops, thus creating complex
levels of variation and modulation that kept the music fresh
and interesting. Crucially, the actual choice of sound
samples and the precise ways in which the sliders
interacted with the sounds was partly random and partly
user-controlled leading to the same relationship of
collaborative influence between user and machine as was
present in the Generator. This was in contrast to the more
predictable ‘master-slave’ relationship we traditionally
expect of technology, especially complex control devices
like music sequencers. A customised performance version
of Playtime was premiered at the Sonar music festival in
Barcelona in 1997 in front of a live audience of about 2000
people [8].
This model of human/machine interaction, I believe,
offers a viable model for future information design. Given
the exponentially expanding volume of digital information
available to us, and the general desire to make machines
more intuitive and ‘human-like’, as well as the commercial
pressures to automate currently labour intensive and highly
skilled tasks, the model of unpredictable interaction
discussed here may offer a productive way of interfacing
human and machine intelligence.
AMBIGUITY AND INDETERMINACY
The second major issue that has occupied my research into
computer aided creativity is the potential for the creation of
images of semantic ambiguity and indeterminacy. I first
became aware of the existence of images that resisted
complete recognition sometime in 1985 whilst watching
The Cabinet of Dr Caligari, a silent German expressionist
film directed by Robert Wiene in 1919 [9]. At some point
toward the end of the film the action cuts from an extended
shot of a hand-written letter to a shot of a man leaning in
despair over a desk (see Figure 3). Due to the contortion of
the pose, the surreal backdrop and the grainy quality of the
black and white film print, I was temporarily ‘lost’ in the
chain of meaning that, up to that point, sustained my
involvement in the narrative of the film. Whilst I was sure I
was looking at a representation of some ‘thing’ (the image
was not ‘abstract’), I was unable to articulate in my own
mind what the image was of until the figure on the desk
stood up and the overall shape of the scene became clear.
Figure 3. Scene from The Cabinet of Dr Caligari
This encounter with ambiguous or indeterminate images
led to a great deal of research on my part as to the nature of
such images and the sensation they invoked. When
speaking to others about it (in the UK at least) I was
frequently reminded of a segment in a 1970s television quiz
show hosted by Robert Robinson called Ask the Family
[10]. Each week the contestants were asked to identify a
common household object from a photograph taken at
extreme close-up. The only example I can remember
clearly was the lever on the side of shoe polish tins used to
twist them open. As the camera drew back and more of the
image was revealed it became easier to identify the object
and marks were awarded for the speed with which
contestants could name it. One of the reasons this piece of
1970s television trivia seems to have stuck on the minds of
those who saw it is because it was one of the rare occasions
when they were confronted with an image that had a
deliberately indeterminate meaning. Our common
experience of commercial images, such as those
surrounding us in advertising, television, product packaging
and so on, is that we expect almost immediately to be able
to securely identify what they are. Yet occasionally, and
usually by accident, we come across an image that we can’t
resolve and which may cause us some anxiety. Fascinated
by the sensation this experience provoked in me I started to
try and replicate the conditions that brought it about by
constructing and manipulating images so they were devoid
of clear meaning without completely destroying their
integrity. As with the experiments on automated creativity
cited above, I soon realised the difficulties inherent in
balancing the right amount of order and confusion within
an image so as to create the desired effect. If it was too
‘meaningless’ then it attracted no interest at all; if it was
too ‘meaningful’ then there was no anxiety about the
depiction and, hence, no effect of the kind I was seeking.
After trying several techniques, including photography,
drawing, filmmaking, and collage I attempted, in
collaboration with Miles Visman, to generate indeterminate
images using randomised pixels in an array. I hoped that
random sequences of pixels would produce images that did
not ‘represent’ anything (for how could the computer know
what to represent?) yet would be sufficiently complex to
suggest to the viewer the presence of some object or scene
as yet unidentified. Like the random data generation
processes described above, the result was largely noisy,
with very little in the way of compelling form emerging to
attract the viewers’ eye. Gradually, as more rules were
introduced to constrain the random behaviour and
encourage more information to appear, the results
improved. In 1990 we set up a basic video sampler to grab
frames live off-air via a UHF aerial and instructed the
computer to randomly cut-up and rearrange the images into
a new composition — a piece called Automatic Television
(see Figure 4). The results were immediately more
interesting than the autonomously generated random
images we had previously created as there were significant
hints of residual forms and features detectable in the
mangled video captures. In a sense we were ‘importing’
order (in the shape of organised data from TV images) from
outside the system in order to create less probable
arrangements of pixels in the computer image, similar to
the way organisms on Earth import the ordered energy of
the Sun in order to sustain the improbable organisation of
living tissue.
Figure 4. Four stills from Automatic Television
The longer-term hope of this research was for a
computer system that would continuously generate high
quality indeterminate, or ambiguous, images that would
engender the sensation I had experienced during the scene
in The Cabinet of Dr Caligari. Although this hope was
never fully realised, the research did lead to the production
of a number of works in a variety of media which formed
part of a larger investigation into the nature of human
perception, creativity and the function of images (see the
Web site ‘www.stem-arts.com/robart2.htm’).
It was shortly after the images generated by
manipulation of video captures were made that I realised
the formal and conceptual similarities between them and
the works of the analytical period of cubism (approximately
1909 to 1912), particularly those by Pablo Picasso and
Georges Braque executed during their period of close
collaboration around 1910 and 1911. It became apparent to
me that the paintings, drawings, etchings and collages made
during this time had precisely the same purpose as the
indeterminate images I was trying to create. In contrast to
most western pictorial artists preceding them, Picasso and
Braque deliberately obscured the overall coherence of their
images through various dislocations, inversions and
rotations of objects without resorting to abstraction: cubist
painting of this period is always of something. In a Picasso
painting such as The Dresser [11], painted in the summer of
1910, we are able to read a quite coherent depiction of a
woman’s dressing table without ever being able to exactly
say where the table is – where it starts or ends, or what
precisely does or doesn’t belong to it. Nor were Cubists
alone in exploiting visual ambiguity and indeterminacy for
producing art; one can find examples in works from artists
as diverse and Joseph Turner, Odilon Redon, M C Escher,
Cornelius Gijsbrechts, and Marcel Duchamp who stated:
“All in all, the creative act is not performed by the artist
alone; the spectator brings the work in contact with the
external world by deciphering and interpreting its inner
qualification and thus adds his contribution to the creative
act.” [12]
The significance of such artworks for the study of human
creativity is that they encourage a dynamic collaboration
between the artwork (and by implication the artist) and the
viewer in the creation of meaning. As with the Generator
piece described above, it is this collaboration between an
indeterminate or unpredictable system (the artwork) and the
active viewer (in themselves unpredictable) who is seeking
some sort of coherence or form that draws the encounter
into the rich area of complexity between total order and
chaos. As has been suggested above, it is here that
creativity as such, whether mechanical or organic, is most
likely to be found.
My ongoing research into the creative relationship
between images and viewers informs a wider investigation
into the nature of human consciousness and human being,
which I have described in a number of articles and books as
the ‘posthuman condition’.
THE POSTHUMAN CONDITION
The practical research outlined above inevitably involved a
great deal of theoretical speculation about the nature of
human creativity and how it might be aided or automated
with computer technology. For me this, in turn,
necessitated a deeper analysis of human consciousness and
the condition of our being in the world; for it did not seem
possible to say anything useful about creativity without
understanding something of the wider circumstances of
existence in which creativity is embedded. Ultimately this
theoretical investigation emerged in book-form in 1995 as
The Post-Human Condition [13]. In this book I argued that
the nature of human beings is undergoing a profound
transformation, partly as a direct result of developments in
technology but also because many of our own conceits
about what it is to be human are no longer sustainable. For
example, the belief that humans (particularly those of a
certain race or class) are the crowning and final
achievement of cosmic evolution was once held by many as
axiomatic, but is now increasingly seen as a cranky
misapprehension. As part of my revaluation of the
condition of human existence in an age of rapidly
complexifying technologies, I attempted to synthesise
current scientific knowledge about the behaviour of reality
(specifically Quantum, Catastrophe, Chaos and Complexity
theories) and philosophical speculation about the
relationship between mind body and the environment with
insights gained from my experience in the creative
application of technology. Whilst I would direct the reader
the book itself for the full arguments, or the abbreviated
manifesto available online at ‘www.stem-
arts.com/posthum/main.htm’, it is worth summarising some
of the conclusions in this paper.
My overriding concern was to assess the theoretical
potential of synthetic, or artificial, creativity. This, I
believed, was a somewhat different proposition to studying
the wider field of Artificial Intelligence, which continues to
be the focus of much intellectual debate. My problem with
AI research, particularly the kind promoted by researchers
like Marvin Minsky [14] and Daniel Dennett [15], is that it
assumes an essentially logical basis for human thought.
This kind of assumption, criticised by Roger Penrose [16]
and John Searle [17] amongst others, regards human mental
processes in algorithmic terms and the human brain as a
very complicated thinking ‘machine’, a kind a organic
version of the silicon digital computer. Here is not the place
to rehearse the debate, save to say that I found such a
proposition deeply unsatisfying and highly suspect. My
own direct experience of human creative processes led me
believe that they were anything but logical, and were very
unlikely to be accurately replicated by rational algorithms. I
argued in the book that human creativity was a response by
the organism to the unpredictability of the environment. Put
briefly, human perception organises sensory data into
continuities and discontinuities (things that are the same
and things that are different) and human consciousness
recognises that the environment behaves in both predictable
and unpredictable ways. For example, a footpath may be
mainly straight and flat but sometimes there could be a tree
in the way or a bend. Humans cannot function well in
situations of either extreme monotony or extreme
stimulation (sensory deprivation or overload); we function
best when balanced between the two. Yet whilst
predictability and continuity are fairly straightforward to
model in mathematics because quantities and parameters
are given, unpredictability and discontinuity pose severe
problems since, by their very nature, they contain the
unknown. And while qualities like randomness, disorder
and chaos can be simulated in computer systems, they can
never truly emulate those in the world because computer
systems do not contain the inherent dynamic complexity of
the world. Human minds, of course, have to cope with the
randomness and complexity of real-world events on a daily
basis and, I argue, have evolved the capacity for creative
acts as a way of defending themselves from, or taking
advantage of, hostile or unexpected occurrences. Moreover,
the human mind (consisting largely, but not exclusively, of
brain activity), being a feature of the natural world itself, is
prone to the same contingencies of continuity and
discontinuity, stability and unpredictability as any other
complex system and is thus able to modify itself, or be
modified, in unexpected or incongruous ways. It is this that
allows us to generate novel and surprising ideas or
connections and ultimately new forms of art, music,
mathematics, and so on. Thus randomness, uncertainty,
unpredictability, which I argue are all essentially non-
computable, are irreducible features of any creative system.
The claim made in The Post-Human Condition, therefore,
was that an artificial system attempting to synthetically
replicate human creativity would need to function, at least
partly, in a non-predictable way. Hence statement 8.6 from
the Post-Human Manifesto [18]:
“If we wish to produce a synthetic intelligence that
displays creativity then we need it to be able to
establish connections between thoughts in a
discontinuous way. This will be achieved by
making it perpetually sensitive to random stimuli.”
and the following statement 8.7:
“If we wish to produce a synthetic intelligence that
displays aesthetic appreciation then it should be
able to sense continuity and discontinuity
simultaneously – without crashing. While this
would cause excitement in the machine, it is yet to
be determined to what extent it would be
pleasurable.”
The Post-Human Condition, therefore, argues for a model
of human creativity (and by extension human
consciousness) that is essentially non-computable. Any
closed, logical system (such as a digital computer
programme or a ‘brain in a vat’) will be able to offer little
more than a crude approximation of real mental processes.
A more effective system will be one that can respond to the
inherent uncertainty of the world (just as we do) and
maintain a balance between total confusion and sterile
order. In a sense, then, such a system would be importing
disorder from the environment, in a reciprocation of the
way organised life is sustained by importing order.
SUMMARY
In this paper I have offered an overview of the concerns
that have driven my practical and theoretical research into
the relationship between human and machine creativity. I
have expressed the belief that creativity is phenomenon that
flourishes between stasis and incoherence, order and chaos.
I have also described some applications and information
design techniques that, in my experience, have proved
worthwhile in the production of publicly sited artworks that
enhance user creativity through computer technology.
Finally, I have suggested a theoretical and philosophical
framework for the further study and design of artificial,
automated or synthetic creative machines.
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