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Abstract and Figures

The authors present an introduction to the new interdisciplinary area of aesthetic computing and proceed to define this area with examples from each of their own disciplines, practices and research. While several decades of publication and work have resulted in significant advancements in art as implemented through technology, less emphasis has been placed on studying the converse issue of art's effect on computing, or "aesthetic computing." The authors present their individual work in this area and then follow with brief criticism of one another's work to elucidate different perspectives on the idea. By approaching the topic of aesthetic computing in this manner, the paper serves as an introduction to and survey and analysis of the field.
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Abstract— We present an introduction to the new
interdisciplinary area of aesthetic computing and then define this
area with examples from each of our own disciplines, practices,
and research. While several decades of publication and work
have resulted in significant advancements in art, as instrumented
with technology, less emphasis has been placed on studying the
converse issue of art affecting computing, or “aesthetic
computing.” We present our individual work in this area, and
then critique each others’ work to surface different perspectives
of the area. By approaching the topic of aesthetic computing in
this manner, the paper serves as an introduction, survey, and
analysis of the field.
Index Terms— Aesthetics, Art, Semiotics, Computing,
Programming, Interaction Design
I. I
N collaboration with Leonardo, we participated in a
workshop on Aesthetic Computing in the hills of
southwestern Germany in July 2002. The workshop [1],
organized by Paul Fishwick, Roger Malina, and Christa
Sommerer, was one week in duration, and was attended by
over 30 representatives of the following disciplines: art,
design, computer science, and mathematics. The purpose of
the workshop was to define the area, and to try to surface key
aspects of the field from a variety of perspectives. A
manifesto of approximately one page was recently published
in Leonardo [2]. Aesthetic Computing is the theory and
application of art to computing. Given this brief definition,
several questions come to mind and we shall address these
questions, and then proceed with the purpose of this paper,
which is to cover sample projects in the area and the different
ways in which the authors proceed to accomplish their
singular crafts.
A question regarding the name “Aesthetic Computing” may
well be one requiring us to justify its existence. After all, isn’t
all computing within the realm of aesthetics, and isn’t there
Manuscript received X, 2003.
P. A. Fishwick is with the Computer and Information Science Department
at the University of Florida (corresponding author), e-mail:
Stephan Diehl is with the Computer Science Department at the Catholic
University Eichstätt, Germany , email:
Jonas Löwgren is with the School of Arts and Communication, Malmö
University, SE-205 06 Malmö, Sweden, email:
Jane Prophet is Director of The Centre for Arts Research Technology and
Education (CARTE), University of Westminster, London, email
already a significant number of projects that capture some
combination of computing and art? Let’s begin with the first
question regarding aesthetics. We will define aesthetics
broadly as a combination of cognitive and sensory modes of
experience, which is generally associated within the definition
of the philosophy of art. However, if we treat only the purely
cognitive aspect of aesthetics, we find evidence of this within
mathematics [3] and computing. One speaks of an elegant
proof for a theorem, or a beautiful representation. With such
qualifiers, the mathematician is usually referring to
cognitively-grounded aesthetics. When we speak of aesthetics
in this article, we take it to mean the range and variety
encompassing cognitive and sensual aesthetics characteristic
of art. As Knuth points out in his discussion of Metafont [4],
underlying his TeX typesetting system, “Type design can be
hazardous to your other interests. Once you get hooked, you
will develop intense feelings about letterforms.” Taken more
generally, Knuth is directly addressing the issue of aesthetics
as being more than the purely cognitive, even within
computing, which grew out of mathematics. A textual section
of a computer program will have both denotative as well as
connotative signifiers, and it is easy to imagine that the
program might align itself with the goals of art, thereby
stretching the traditional boundaries of what may be
considered to be a usable computer program representation.
The second question regarding the combination of science
with art is addressed by first noticing that, unlike computer or
digital art, aesthetic computing implies that art is affecting
and reflecting—some aspect of computing. This results in
quite a different agenda than that found in many other fields
of digital art. It may be that taken to its logical conclusion, art
affects computing and that this, in turn, affects art, closing the
loop: art creates art. However, we are presently a long way
from that proposition.
We acknowledge our interest of aesthetics in computing to
expand human-computer interaction and representation to
reach into numerous areas of computer science from the
primary operating systems interface to the interface used by
computer scientists to create programs, and by scientists to
create models of geometry and dynamics. This leads to two
observations, partially justifying the move toward aesthetic
computing: (1) aesthetics in computing are broader than the
purely cognitive dimension, and (2) the art-science confluence
embedded within the discipline of interaction design is
broader than the primary “desktop” interface. The first
observation is one of both ontology and epistemology—that
while we might leverage existing aesthetic principles toward
the sensory. Consider the case of “software patterns” as one
Perspectives on Aesthetic Computing
Paul Fishwick, Stephan Diehl, Jane Prophet, Jonas Löwgren
example. One would surely state that these patterns reflect
abstractions of software structures, and that they are found
lurking in numerous software applications. There are two
ways at looking at patterns, reflecting two ways of defining
aesthetics: cognitive versus material. What if the patterns were
surfaced in a way that was more attuned to material
embodiment? This would build upon the existing pattern
literature and extend it. The “factory” method espoused by
Gamma et al. [5] could be the basis for a 2D or 3D scene
which looked, and operated, like a factory. The look and feel
of the factory would improve with artistic influence and
guidance, and provide strong metaphorical cues. This sensory
dimension seems lacking from the pattern literature since one
generally finds that representation is limited to rectangles and
arcs. And yet, it is not only in the pattern literature that it is
lacking, since the visual minimalism of program structures,
and the mathematical structures underlying them, is fairly
common in computing. The second observation is that
interaction design needs to concern itself with all interaction
and presentation found in computing, including that of how to
represent data and program structures, for instance. The
emerging areas of Information Visualization [6] and Software
Visualization [7,8] render themselves toward this goal, and yet
the representations of information and software could do with
greater emphasis on a wider range of artistic expression,
without sacrificing utility. So, it is not that the area of design
does not presently concern itself with incorporating aesthetics,
but that the current level and degree of this incorporation
needs to be expanded beyond that of the typical user interface
at the operating systems level.
We now have a working idea of aesthetic computing, and
we need to explore different approaches. The structure of the
paper begins with four statements on aesthetic computing by
each of its authors, followed by a discussion of each others’
views and statements.
A. Scope
In applying aesthetics to computing, we need to confine
ourselves to some aspect of computing, or one of its subfields
such as HCI, visualization, or discrete structures, to name a
few. For the RUBE Project [9-12], we have focused primarily
on representations, informed through an artistic sensibility, in
mathematics and computing notation, from the notation of
algebraic and differential equations to that of program and
data structures. Our basic philosophy is that we want to build
a system that allows a multiplicity of different notations to be
constructed so that one may see and hear the same underlying
formalism in numerous ways. Not only do different people
and cultural entities enjoy working with a formalism using
different metaphors, but also the same person or group can
benefit from being exposed to diverse presentations.
B. Implementation
At the University of Florida, we have constructed a
software system called RUBE, which allows for different
representations to be applied to a select number of formal
dynamic model specifications. Using RUBE, it is possible to
change the way that formal models look and sound. By formal
models, I am referring to a large class of models used for
specifying systems that incorporate time for analysis and
simulation: finite state machines, Petri networks, Markov
models, queuing models, System Dynamics graphs, as well as
ordinary and partial differential equations. RUBE uses XML
(eXtensible Markup Language), which separates content from
presentation. In XML parlance, content refers to an abstract
specification defined as a document tree, and presentation
refers to the way that the tree is presented to the user, the way
it looks and sounds. Thus, using RUBE and guided by the
XML philosophy, one may specify an equation, but then
choose to present the equation as linear text, a network, or a
three dimensional structure. Choices as to which presentation
to employ can be guided by XML style sheets and their
associated transformations.
RUBE’s architecture is based open source software, and
begins with authoring toolkits: SodiPodi for 2D vector
drawing, and Blender for 3D modeling. Let’s consider the 3D
pipeline beginning with Blender. The artist creates a 3D
model in Blender, and then uses a Python scripting interface
allowing attributions to be made regarding semantics. For
example, one might point to an object and say that this object
is a state or a function. After the semantic assignment, an X3D
(eXtensible 3D) file is created for the presentation, and a
special XML file is created for specifying the formal model.
After some XML transformations, this XML file is translated
into Javascript or Java, whereby it can be reincorporated into
the VRML file, resulting in an interactive VRML world. The
2D transformations are similar, except that SVG (Scalable
Vector Graphics) is used for presentation.
Let’s begin with a formal definition of a Finite State
Machine (FSM) M [13]. These machines have states that are
connected to each other through transitions that are made
active when an input to the machine is of a particular value.
Here is a formal definition for M:
Even though this text might seem to be the formal
specification for M, it is actually one of many ways to look at
the underlying formalism which would is encoded in XML.
The above text is one type of presentation among many. In
general, all presentations require additional natural language
semantics if we are to make sense of them. Q is the state set
for M; I the input set, O the output set,
the transition
function from one state to another, and
the output function.
Figure 1 illustrates our second presentation for the FSM. It has
Fig 1: A 2D static snapshot of an interactive diagrammatic
FSM interface
iconic properties so that when the machine is in state S2, the
presentation of a circle for S2 encodes the concept of a
boundary, and that which is inside it. That is, the graphical
depiction of S2 is consistent with the underlying metaphors of
set theory, whereas the purely textual presentation does not
capture these metaphors. Moreover, Fig. 1 is incomplete on a
non-interactive medium, such as paper, since the additional
information encoded in the text representation is equally
present during interaction with the figure. Similarly, the
arrows capture the notion of transitioning from one state to
another, since anyone who has seen an arrow fly knows that it
is aimed toward a target. The metaphors of the figure
dramatically improve the semantics of the machine, and so
one is led to wonder whether employing presentations with
alternative aesthetics might further improve the impact of the
metaphor. The underlying assumption is that material aspects
of levels of representation are based largely on what is
available for a society, and what is affordable and materially
efficient. Consider Figure 2 as a representation that has only
recently become possible through computer graphics, and the
ability to employ 3D components. The metaphor of the circle
as a boundary has been replaced by a small gazebo-like
structure. The arrow in Fig. 1 is now shown as a red-clothed
woman walking from one state to another along a lamp-lit
There are a host of philosophical issues that come into play
here. Isn’t there a need to enforce visual minimalism within
this sort of structure? What are the cultural barriers imposed
that might prevent the adoption of models like Fig. 2 being
made possible for science and engineering? With respect to
the issue of minimalism, we should note that is quite possible
to maintain abstraction without requiring visual minimalism.
Within the context of the art community, this can be seen
when comparing and contrasting the genres of Abstract
Expressionism and Surrealism. Both of these genres contain a
wide variety of works that employ symbolism, iconography,
and the richness of semiotics even though the visual
Fig 2: A 2D agent-based presentation of the FSM using the
Virtual Reality Modeling Language (VRML).
presentations are strikingly different. Deriving the idea of an
abstract state in an FSM, for example, need not imply that the
state be presented visually in a minimalist fashion. The key
thing is to strengthen the metaphor underlying what it means
to be a state, and the corresponding elements of boundary that
go along with it.
The second question about cultural barriers may be at the
heart of the aesthetic computing challenge. Computer
scientists have been educated with minimalist figures and text,
and so it may come as a shock to realize that our
representations for formal objects are not as constrained as we
may have thought. Until the era of computer graphics and fast
computers, we had little need to inquire about, what initially
appeared to be, exotic ways to encode formal knowledge.
However, it is not only a challenge for computer scientists, but
also for artists, since artists should be encouraged to consider
the computer, and computing practices, as subject material in
addition to raw material. This suggestion on formal structures
as raw or subject material may strike some artists as a
modernist era agenda; however, there the computer, and its
mathematical foundations, creates significantly higher
complexity as a tool, or as a subject, than paint, palette knife,
or chisel ever could.
Software is neither matter nor energy. It is just a kind of
information. Matter and energy are media which carry
information and thus software. To develop new or understand
existing software it has to be projected into a human readable
form – the program text. Note that the program text is not the
software, but just a representation thereof. The program text is
written in an artificial language with a strict syntax and a more
or less well-defined semantics. Trying to understand a real
software system by reading its millions of lines of program
text is a vain task. As a consequence many tools have been
developed to support software understanding. These tools rely
on analysis and visualization techniques. Per se, software is
Fig. 5: Number of simultaneously changed files
Fig. 3: Program structure with analysis results.
Fig. 4: Animation of the HeapSort algorithm
invisible. In a famous paper [14], Turing awardee Fredrick
Brooks even stated that “software is invisible and
unvisualizable” because each kind of visualization only
addresses “one dimension of the intricately interlocked
software elephant.” These dimensions include the static
structure of the software, its dynamics and its evolution. Or to
put it in other words, different kinds of visualizations show
how software is encoded, how it behaves, and how it is
developed. In the following we will present and discuss
examples of visualizations for each of these dimensions.
In Figure 3 a graphical representation of a program, its
control-flow graph, is shown. In addition the graph contains
some information computed by a program analysis. With the
help of this visualization developers can detect certain kinds
of errors, so-called stack overflows, in their programs [15].
In Figure 4 a snapshot of the animated execution of a
sorting algorithm is shown. The window contains several
representations or views of the data sorted. Algorithm
animations are typically used in education. Most of the
animation techniques do not scale for real software systems.
Finally, Figure 5 is a pixel map. In this example the color
of the pixel at position (x,y) represents the number of times
file f
and f
have been changed together relative to the total
number of times file f
has been changed. From this figure the
developer can see how strong different files are coupled. We
call this kind of coupling evolutionary [16], because it is
based on the change history of files, to distinguish it from the
logical coupling usually used in software engineering. As the
files are sorted by the containing directory the pixels form
blocks. These blocks indicate that files within a directory are
coupled, i.e. often changed together. Software developers are
mainly interested in the outliers. These are those pixels
representing couplings between files in different directories,
like those labeled “Patches” in Figure 5. Outliers can be a sign
of a bad system architecture.
We have now seen three very different kinds of
visualizations as they are used for understanding software and
its development process.
Now what about the aesthetics of these visualizations? It
may come as a surprise to the artistic eye of the reader, but
there have been actually some aesthetic criteria involved when
computing these visualizations:
In Figure 3 the number of edge crossings and bends has
been reduced and directed edges are mostly drawn
downwards. In Figure 4 color is used consistently in the
different views. While the algorithm actually performs
discrete changes, the animation of these changes is done
smoothly. In Figure 5 color coding based on the heat
metaphor is used: The color red shows the highest coupling,
blue low coupling and white now coupling at all. In other
words, hot files are those that are often changed together.
The sole purpose of the above mentioned aesthetic criteria
is to produce visualizations that convey the information as
clearly and effectively as possible. As a consequence of
concentrating on the automatic generation and usability of
visualizations the current research on software visualization is
rich when it comes to the different properties of software that
have been visualized, but poor when it comes to the spectrum
of visual metaphors used: boxes, circles, lines and color.
I will consider the interdisciplinary area of aesthetic
computing through a discussion of the interdisciplinary
project, Cell. Cell is a collaboration between an artist (the
author), liver pathologist (Neil Theise), mathematician (Mark
d’Inverno), computer scientist (Rob Saunders), and
curator/producer (Peter Ride). The Cell project explores new
approaches to cell behaviour and its representation and uses
mathematics to bridge the gap between scientific theory and
computer visualisation. Our premise is that artists can
‘imagine’ scientific and mathematical theories and thereby
influence the development of scientific, mathematical, and
computer science research and their associated aesthetics.
A. Context
Our practical research context is a triangle of different
experimental research environments: Theise’s medical
laboratory; d’Inverno’s and Saunders’ respective
mathematical and computer science labs; and Prophet’s
artist’s studio. Each provides a different context for the work
and has particular embedded methodologies, from the
hypothesis driven ethos of the medical research lab, to
reflexive practice in the art studio, and the empirically driven
environment of mathematics. The aesthetic context of each
discipline is equally diverse. Visualisation in the laboratory
differs from visualisation in the art studio, aesthetics are
important to both. In the medical laboratory representation is
usually taken literally, leading to scientific illustration. In the
art studio ‘representation’ is a term and process framed by
debates in cultural theory and numerous theories of
representation (for example, an image, sound, object can
signify something without actually sounding or looking
anything like it). In Cell we are taking account of a wide range
of aesthetic traditions, including the aesthetics of
mathematical equations to produce a range of practical
outcomes (including animated 3D illustrations of cells,
mathematical models, Zen gardens, sound pieces, and robotic
artworks). In addition we document, develop and evaluate the
interdisciplinary collaborative process itself. Through a series
of studio and laboratory visits, Theise and I became immersed
in each other’s working culture and identified significant
cultural differences. For example, in cell biology the
‘photographs’ of tissue slides have a truth status, and are
accepted as ‘proof’ of experiments and hypotheses within
papers. The beauty of these representations (see Fig.6)
produced as part of his laboratory research, is important to
Theise and there appears to be a correlation between aesthetic
quality (specifically how ‘beautiful’ a representation is) and
the publication rate of associated papers. Fig. 6 is one of
Theise’s images, and represents skin tissue from a female
mouse who received a bone marrow transplant from a male
mouse. Blue nuclei of hair follicle lining cells surround the
orange, autofluorscent hair shaft (large arrow). Two of these
nuclei contain fluorescently labeled Y-chromosomes (small
arrows) indicating that they derive from the donated male
bone marrow, not from the female's own original cells. Thus,
bone marrow stem cells have given rise to skin-type lining
By contrast, in contemporary art practice photographic
representations have no automatic truth-status (quite the
contrary) and are assumed to be subjective rather than
objective. Artificial life (Alife) systems that have a graphical
and/or sound output pose other challenges to notions of
representation. Their outputs are autonomous, not controlled
or ‘made’ by the artist or illustrator. They are time-based, not
still. They are not constant or predictable as visual or aural
outputs are produced in real-time to represent the software
running beneath them, which is itself constantly changing as a
complex system of interactions between entities takes place.
They are not ‘top-down’ but ‘bottom-up’ and potentially
emergent: unexpected behaviours represented as images or
sounds emerge from many interactions based on simple rules.
Fig. 6: Hair follicle with lining cells derived from bone
B. Converging: focussing on behaviour across time
Having orientated ourselves to each other’s research
environments we identified key concepts and contexts on
which to focus, and converged and focussed on those areas.
Theise’s research examines the plasticity of adult stem cells
and their function. To do this he uses processes based on
hypothesis and hypothesis-testing including repeatable
laboratory experiments and the analysis of specimens of cell
tissue. Because the tissue is dead at the time it is analysed it
represents a frozen moment in time, from which researchers
understand another aspect of stem cell behaviour, and
extrapolate further hypotheses to test. My experience as an
artist working in time-based media and Alife suggests a
different approach to assessing stem cell behaviour. We
therefore decided to develop an Alife engine to enable the
scientist to look at simulated stem cell behaviour as it happens
within the complex system of a wider community of cell types
and enzymes. This output draws on the aesthetics of medical
illustration and expands it by making the connection between
changing image and underlying behaviour accessible (click on
a moving cell and see Fig.7, a data read-out).
Fig 7: Cell 3D Java alife representations
C. Collaborative process, aesthetic impact
The collaboration expanded to include a mathematician
with expertise in agent-based systems (d’Inverno) to
determine the mathematical rules that describe adult stem cell
behaviour as proposed by Theise (that stem cells can evolve
into mature cells of other organs such as skeletal muscle,
bone, and brain with unexpected plasticity). A computer
scientist (Saunders) interprets the mathematical model and
produces a real time graphical display. Interface features
enable scientists (such as Theise and d’Inverno) to make
changes to stem cells and see the results; map changes through
generations of stem cells; see behaviour displayed as real-time
animation and graphs. The aesthetic is that of medical and
scientific illustration, and in common with medical
illustration, a team has produced this scientific visualisation.
Group/multiple authorship is an accepted part of scientific
publication. This is not the case in art practice. Standing
against the canon of the artwork as a product of a sole
‘genius’ artist, are conceptual and digital artworks where
collaboration is more common. Public acknowledgement of
collaborators is a significant part of the aesthetic framework
of such art practice and is in marked contrast to the
unacknowledged appropriation of “assistants’” work that has
traditionally dogged the fine arts.
D. Aesthetics and Conceptual art
The notion of ‘an’ aesthetic is contentious in Cell. Like
much conceptual art, the idea behind Cell (namely modelling
the behaviour of stem cells) and the means of producing it (via
interdisciplinary collaboration) are more important than the
finished work or its (fixed) appearance:
"In conceptual art the idea or concept is the most important
aspect of the work . . . all planning and decisions are made
beforehand and the execution is a perfunctory affair. The idea
becomes the machine that makes the art." [17]
Conceptual art can be defined as the “appreciation for a
work of art because of its meaning, in which the presentation
of shape colour and materials have no value with out the
intentions of the work.” [18] If conceptual art has an aesthetic
then it is the dematerialisation of the art-object; the object
only has value as a materialisation of the idea, not in and of
itself. Mathematics and computing science can both operate
without materiality and can describe the immaterial, which is
one reason why there may be a mutual attraction between
computer scientists, mathematicians and artists working
conceptually using digital media. The robot artwork produced
as part of Cell will comprise of objects and their functionality
and appearance is important, but the idea behind the artwork
is of equal, or more importance. The idea itself can be seen as
part of the developing aesthetic of digital and other
contemporary arts: the development of an aesthetic of
virtuality and engagement.
E. Scale
Aesthetic debates concerning scale are central to the Cell
projects. I have been interested in the ‘sublime’ in
contemporary culture for a number of years, in particular,
fractal mathematics and an apparent cultural shift to a sublime
of the very small and detailed. This develops ideas of the
‘natural’ or ‘religious’ sublime [19], based on our experience
of the human body in landscapes so large and overwhelming
that they prompt a sense of awe and momentary terror. I
suggest that there is now a sublime of the micro, nano and
virtual, a similar awe and terror as we try to grasp an inner
landscape of a scale too small in relation to the human body
for most of us to comprehend. Theise’s theory challenges the
paradigm of the progressively differentiating adult stem cell
(and of cells being one of the body’s smallest ‘building
blocks’). He draws attention to the role of technology (the
microscope) in assigning high status to the unit of the cell
(bounded by the cell wall made visible for the first time via
microscopes). Determining the bounded cell as a key ‘unit’ is
central to our thinking of scale and reinforces a reductive
model of the human body in medicine. Theise notes that if a
different imaging technology had been invented (instead of
the microscope) that, for example, showed patterns of energy
or fluid movement through the body, then we would be less
inclined to reductionism. Any subsequent development of the
microscope would have qualified the ‘fluid’ model to note that
fluids sometimes moved across boundaries (i.e. across cell
Fig 8: Cell 2D Cell alife java representation
We have discussed the modeling of stem cell behaviour and
the role of mathematics in exploring and representing shifts in
scale. In choosing to ‘manifest’ the mathematical model by
developing software written in java, Saunders kept the project
sensitive to scale at the level of the computer code itself. Java
language was suggested by Saunders because of its scalability,
providing the project with a tool that could be used on many
different types of computer, and on computers with a variety
of speeds etc. (see Fig 8). Scalability has become central to the
ethos used to design the Cell software. Discipline-specific
theories of ‘scale’ converge in Cell to become a key theme
and aesthetic.
F. Aesthetics and Visualization
To date, the real-time graphic representation arising from
Cell's complex adaptive system is not what I would consider a
piece of art. It is a scientific visualisation, informed by the
aesthetic framework of my art practice. As detailed below,
conceptual art has influenced our approach to making Cell. In
developing the look and feel of the scientific visualisation, I
have emphasised to the medical and computer scientists that I
work with that as a contemporary artist I have been educated
to resist beautifying the graphics. As far as possible, I want
the graphic look and feel to reflect the underlying software, to
draw attention to essence of the idea or concept with as little
frippery and decoration as possible. From this standpoint the
java version is a more satisfying outcome than the 3D version.
The 3D version has been influenced the aesthetics of medical
illustration and its goal of explaining via precise observation
of the appearance of things: this is at odds with my emphasis
on the behaviour of things (in this case stem cells). What is
key for me as an artist working on the project is to transmit a
sense of 'stem cell-ness'. What is captivating about our
contemporary understanding of these cells seems to be the
way that they behave rather than the way they look. The
aesthetic framework in flight and gaming simulations has also
contaminated the 3D version of Cell, in particular the
characteristic focus on surface rendering, depth and
transparency reflects a relentless drive towards photo realism.
This is not what I believe to be of most interest as an artist
working with software. Photorealism is informed by the
medium, material and aesthetic of photography. I am
interested in engaging with the medium of code and software
and in trying to use materials in keeping with that, and to
develop a look and feel that contribute to a computer
aesthetic, for example that take account of the lack of depth of
field and infinite focal range of virtual space. Saunders and I
have discussed these issues at length and he is interested in
developing a 3D version of Cell that avoids the criticisms I
outline above. We are committed to developing a 3D version
because that is closer to our model of stem cell behaviour than
the 2D java version. We will attempt to reflect the
characteristics of virtual space (no depth of field, infinite focal
range etc.) as we do this.
Interaction design is concerned with shaping the use
qualities of digital artefacts. Another way of putting it would
be to say that interaction design is design of the digital
materials, where the word design is used in the strong sense of
exploring all aspects of a possible future: aesthetical and
ethical aspects as well as structural and functional.
It may seem odd, and in fact it is odd, to talk about aesthetic
computing as if it were something new and hitherto
unexplored. All computing is aesthetic in the sense that all use
of digital artefacts entails aesthetic reactions. To be sure,
many contemporary digital artefacts tend to elicit aesthetic
reactions along the lines of frustration, indifference or
boredom, but these are aesthetic reactions nevertheless. And
as designers, we are free to aim for other kinds of reactions if
we like.
Of course, there are historical reasons for the existence of
such blind spots. The academic roots of interaction design
stem from the field of human-computer interaction, where the
main focus has always been on task-oriented use of digital
artefacts and in particular its efficiency and absence of errors.
It is not surprising that the image of computer use is
sometimes simplified to the extent that useful, efficient, and
error-free use is seen as the whole picture. The disregarded
parts of the picture, including aesthetic qualities of the use,
will then appear as new when they are brought into
How, then, should aesthetic use qualities be dealt with in
interaction design? A common fallacy is to equate aesthetics
with pleasing visual design. To be sure, there are design
situations where the immediate visual impression is an
important factor in determining the outcome of the interaction.
A good example is a web shop with one-time customers who
should ideally spend money on their first and only visit. The
visual design of the web shop’s front page is crucial in
establishing the right combination of desire and credibility to
actually make customers enter, shop and pay.
In nearly every other case, however, we need to realize that
a digital artefact is constituted primarily not by its static visual
design but by its dynamic Gestalt – the character of the
interaction over time. Digital design materials are temporal in
this respect, at least as much as they are spatial. The rest of
this section provides three examples of aesthetic qualities in
the use of digital artefacts. They serve as illustrations of how
the aesthetics of interaction design can be approached and
articulated for further debate as well as for practical
application in concrete design situations.
Pliability is the quality of plasticity, malleability of the
digital artefact under the hands of the user. A set of
information is pliable to the user if it feels like a responsive
material, a matter of inquiry that can be manipulated and
experienced in a tactile sense. Pliability contributes to a highly
involved process of exploration where the loop between
senses, thought and action is rapid and physical rather than
elaborate and mental. I make a small, quick move – the
material shapes and responds – I notice something new – I
make another move – and so on. Ahlberg and Shneiderman
[20] were the first to articulate this quality, under the label of
“tight coupling”..
In the interpretation above, pliability concerns the micro-
qualities of interaction, the qualities of the surface. Examples
of interaction design aiming at pliability include the influential
concept of dynamic queries [21] as well as the more recent
interaction technique Sens-A-Patch [22]. Another aspect of
pliability has to do with the user’s possibilities to act freely
and shape the material according to the larger situation at
hand, such as annotating the margins of a paper form to
communicate something outside the rigid boundaries of the
form itself. As Henderson and Harris [23] point out, this kind
of deep pliability is often unnecessarily lost in the transition
from paper to computer systems in, e.g., administrative work.
It is straightforward to see how many existing administrative
systems could be extended to accommodate free-form
annotation and the equivalent of sticky notes.
Fluency as an aesthetic quality of digital artefacts is
brought to the fore in relation with the increasingly pervasive
digital infrastructure. Use is not necessarily a primary activity
at the focus of attention, it is not a binary variable of either
using a digital artefact or not. With ubiquitous and mobile
computing, it becomes more of a dance among multiple
representations and mediations. Streams of information flow
between center and periphery as we move through the shifting
environments of everyday life and work. Transitions need to
be graceful and nondisruptive.
As a simple but conceptually powerful example of fluency,
consider the Hazed Windows concept by interaction design
students Trine Freiesleben, Miska Knapek and Henrik Moberg
at Malmö university [24]. The idea is simply to offer a more
lightweight and transient communication channel, for instance
between a little girl and her granny who live in different cities.
The girl draws or writes with her finger on a display in her
home. Her signs are redrawn at granny’s display but gradually
fade away, as the metaphorical “window” is filled with
metaphorical condensation again. If granny happens to see the
signs before they are gone, she can reply in the same way. A
sign on the display disappears completely in a few hours.
The strength of the Hazed Windows concept is not in its
focus on emotional lightweight communication, which has
been done thousands of times before, but rather in the elegant
questioning of the hidden core assumptions of computer-
mediated communication. When we do our email, we devote
our full attention to it. We expect messages to be persistent
until we choose to file or delete them. In short, we approach
the communication situation as a binary task. The Hazed
Window hints at the possibility of a new middle ground, a
new approach to computer-mediated communication in text
and pictures that exhibits a much greater degree of fluency.
Seductivity refers to the captivating qualities of a digital
artefact. Following the seminal analysis by Khaslavsky and
Shedroff [25], seduction is described analytically as a process
of enticement, relationship and fulfillment. Enticement
concerns grabbing attention and making an emotional
promise. The subsequent relationship is based on making
progress with small fulfillments and more promises, possibly
lasting for a long time. The fulfillment, or ending, involves
making good on the final promises and ending the experience
in a positive and memorable way.
It should be clear from the description above that
seductivity, in the sense used here, is a quality that crucially
depends on the dynamic Gestalt, the temporal qualities of the
digital artefact. Sexually explicit pictures on the front page of
a web site has nothing to do with it. The example offered by
Khaslavsky and Shedroff is the Visual Thesaurus [26] by
Plumb Design. It is a web application that duplicates the
contents of a traditional thesaurus but takes on entirely new
qualities by virtue of its interactive properties. The user
explores words, their synonyms and eventually the transient
and temporary nature of language itself by navigating a
beautifully animated network of words and their interrelations.
Khaslavsky and Shedroff argue that the Visual Thesaurus is
seductive in the sense that it offers surprising novelty, goes
beyond obvious needs and expectations, and creates an
emotional response due to its visual and interactional beauty
(enticement). It connects to personal goals through the
fascination of words and concepts and promises to fulfill those
goals (relationship). The casual viewer may discover deeper
meanings of looking up a word in the sense of the
multidimensional and dynamic relationships between concepts
Regarding Stephan’s introduction, one of the tenets of
aesthetic computing, at least from my perspective, is that we
should endeavor to balance body and mind, sense and
thought. If software is “invisible,” then by ad absurdum,
everything is invisible. For example, I could say that most art
is invisible because the artists manifest artwork within their
minds prior to physical construction. It is not clear that
computing (including software) enjoys a kind of privileged
mental status in this regard. I would say the same holds for
mathematics. Brooks’ quote seems to re-emphasize this
artificial Cartesian mind/body duality. We need to be careful
here since if we condone this philosophy, then we place an
unnecessary barrier between art and computing. The medium
should be an integral part of software and mathematics, and
not viewed as dwelling deep in Plato’s cave only to be
trumped by ideal mental constructs conveniently positioned
In my view, Software is information and thus just another
kind of entity, so it is orthogonal to matter and energy.
Regarding your reference to “invisible art,” I think this is a
good point. The artist manifests her feelings and ideas in a
piece of art, but the piece itself is not the feeling and is not the
idea. It is just a representation of it. I think that the
visualization and the software are two separate things. And
each visualization only covers an aspect of the software, in a
sense it is an "application" or an "interpretation" of the
software, but it is not THE software. Bubble sort remains
bubble sort independent of the medium, whether I run it on a
computer, let a group of students sort themselves by height or
whether I print the program text on the screen.
In section I, defining aesthetic computing as the theory and
application of art to computing implies a position within
computer science, where the field of art is 'applied' to the
extent that it can improves practices and understandings of
computing. Paul's and Stephan's sections appear to fall into
this category. Is this a position we want, and one we feel
comfortable with? Personally, I am not sure. The following
comments might help illustrate why I find the initial position a
little awkward. The section on the aesthetic qualities of
mathematics and programming source code (in section I) is
slightly confusing to me. The discussion of 'cognitive
aesthetics' appears to be about the beauty of certain
representations as perceived by specialists creating and
manipulating those representations (mathematicians,
programmers) [27]. Then, there are a few paragraphs on wider
perspectives -- but sections 2 and 3 are essentially back on the
visual 'beauty' of representations.
Each of us applies aesthetic computing in a way that tends
to amplify our own particular specialty areas. Mathematicians
and computer scientists are on familiar terms with beauty as it
relates to their work, and so there is nothing wrong with
focusing on either cognitive or visual beauty, although I admit
that beauty is one of many facets of the aesthetic experience.
For the computer scientist, representation and modeling are
paramount, which is why I focus on representation of formal
structures, and Stephan focuses on software and program
visualization. This is what we do professionally, and so we are
seeking ways in which art and the theory of art (aesthetics)
can improve our discipline. However, I also think you are
right to suggest that aesthetic computing can, and should, be
broader than this.
To continue, the discussion of patterns in section I as well
as the whole section II appears to argue that 'the application of
art to computing amounts to finding more visually interesting
representations for some sort of computing 'contents', such as
algorithms or data structures. The contents themselves are
more or less given, and the job of the 'artist' is rather a
cosmetic one (which, to me, seems more appropriate for a
graphic designer than a visual artist). The audience for the
'artwork' appears to be computing specialists. To illustrate
why I find this perspective rather limited, consider the wide
range of art dealing with computing not as a given but as a
subject for inquiry. A rather well-known example here could
be Adrian Ward's AutoIllustrator [28], which is both a
mockery of commercial productivity software and also, more
importantly, poses rather important questions on the nature of
authorship. When a tool starts to act more independently, who
is the originator of the resulting work? The tool user? The
programmer/designer of the tool? Is AutoIllustrator an
example of aesthetic computing? I certainly think so, perhaps
a more interesting example than the ones offered by Paul and
The examples that are given in section 2 are visualizations
of different aspects of software. These visualizations are goal
driven. I don’t claim that they are aesthetic computing, but
that software visualization can both learn from aesthetic
computing and provide material and techniques. When we
developed the pixelmap to show file coupling, we didn’t know
what the result would be and were very positively surprised
when we saw that most couplings appeared along the
diagonal. At least in research, we work to some extend like
artists. Our material are the visualization techniques and data
about software systems. And in a way we form this material
by combining the techniques and applying them to the data to
get nice or useful pictures and provide new insights into
For me, computing is less a subject for inquiry and more a
medium that brings with it a range of discourses and has a
particular set of qualities. As an artist I want to work with the
computing medium in ways that reflect, counterpoint and
explore the characteristics of the medium and its discourse (I
am not really interested in computing as a tool to make
beautiful pictures for example). I think AutoIllustrator reflects
and comments on software design and the experience of using
software like Adobe Illustrator by making software. This is
like the way that Modernist painting explored the material of
paint by making paintings like Malevich's White on White -
the painting wasn't a representation of something else, it was a
reflection on the material qualities of paint and of canvas.
AutoIllustrator stays close to its subject in form and material
but it is not a representation of something, it is an idea and
comment about something.
Jane – can you inform us in more detail about the aesthetics
of scientific visualization with regard to your Cell project?
One could argue that any scientific visualization could be part
of aesthetic computing; however, I imagine that the process of
Cell, incorporating you as an artist, changed the outcome from
what Cell would otherwise be if it did not consider aesthetic
experience and involvement?
Form is in part lead by function and the current 3D version
functions well in the context of medicine and reflects a
medical illustration aesthetic. It is enough that the current
version simulates a highly controversial 'paradigm shift' in
theories of stem cell behaviour; for it to also fulfill an artistic
agenda would confuse matters and make it less useful as a
medical tool. The aesthetic of medical illustration is to avoid
any expressive artifice in the image and to attempt to produce
something as real-looking as possible. In this case it shares
some aesthetic concerns with simulation and gaming.
However, medical illustration tends to remove dirt and
extraneous objects in order to expose, or focus on, a central
mechanical structure or behaviour across time. 'Exploded'
models in anatomy drawings and sequential sketches showing
for example, cell division, have been replaced by Flash
animations and more recently by biomedical illustrations that
draw on agent based systems. At the heart of Cell, for all the
professionals involved in the collaboration, has been the
development of a conceptual model of stem cell behaviour and
then a maths model that informs the production of a
simulation (a real-time complex adaptive system with a
graphic user interface and graphic output). This 'stem cell
engine' will now be used to drive a number of diverse outputs,
each peer reviewed in our particular disciplines. Theise has
authored papers for medical journals on the impact of Cell on
his thinking about stem cells; d'Inverno will author
mathematical papers and produce a musical score and sound
piece; Saunders will make web toys (
and Prophet will make future robotics artworks.
I see, so the actual process of doing Cell has resulted in a
kind of massive catalytic reaction, involving all the players.
This does play well into your notion of conceptual art’s focus
on process rather than outcome; however, this leads me to one
of your earlier points on conceptual art—that it reflects an
idea or dematerialization. I would like to suggest that
conceptual art reflects the process of making art, and as I
demonstrated in my section, processes can be visualized and
materialized within a field of artistic influence. This is done
by modeling the process and thus surfacing it as an abstraction
for the phenomenon in question. For this reason, I am happy
with viewing “conceptual art as process,” but I do not think
this necessarily accords with dematerialization. If one records
the process, or models it, then the process itself is manifested
as an artform.
One of the key tensions that represented itself in the
discussion is the interplay between that which artists produce
versus that which computer scientists produce. Artists have
an agenda based a wide variety of styles and aesthetics from
formalism and cultural exploration to capturing social,
political, or economic aspects of phenomena. Computer
scientists are primarily after high utility artifacts; if something
is useless, then most mathematicians and computing
professionals will tend to shy away from it. However, there is
a line that stretches from “no use” to “full use” if there can be
such unambiguously defined things. To see this, we need to
step back to the definition of aesthetic computing: the
application of art practice and theory to computing.
There is no reason why this application must be targeted on
artifacts of high general utility. By exploring the boundaries
and interstices of the “use range”, we think we can enhance art
and computing. Artists will become more familiar with
elements of computing such as data structures, programs,
architectures, and even core mathematical structures upon
which computing is founded. What the artist produces reflects
a computing essence, whether or not the result is of
immediately obvious utility. To the extent that a piece makes
one reflect, it is useful in exploration, creativity and education,
and so even the term “use” or “usability” becomes
circumspect. Thus, aesthetic computing for the artist can range
from Software Art (a fairly new movement defined by artists
producing their own programs or languages), to
representational art where the computing element becomes the
subject of the art, rather than the material for the art as in
Software Art. It is this ability to weave through the webs of
utility and computing that makes aesthetic computing a unique
For the Computer Scientist, what the artists produce will be
fertile ground for representation, interaction design, and
human-computer interfaces in general. As in Software Art,
where some artists are becoming computer scientists of a sort,
we also have the converse situation where some computer
scientists become artists.
On a more general level, the encounter between art and
computing may by studied in terms of disciplinary relations.
Jantsch [29], who is the originator of concepts such as multi-
and interdisciplinarity, views disciplinary integration as an
evolutionary hierarchy. If a traditional disciplinary approach is
specialization in isolation, then multidisciplinarity simply
refers to adding different disciplines without any direct
cooperation between them.
The next step up the evolutionary ladder is
crossdisciplinarity, where one discipline supports the other
within the other’s own discipline. Our discussion above, and
the identification of fields such as Software Art and Aesthetic
Computing, might suggest that this is more or less our current
state of progress. An illustrative example is our introduction
of the dimension of utility, as a way to capture one of the
ways in which the fundamental values of the disciplines or art
and computing differ.
The most advanced integrative step, according to Jantsch, is
interdisciplinarity. It involves direct cooperation in both
directions where the outcomes could typically not be achieved
entirely without any of the disciplines involved. It also entails
the formation of new concepts, practices and values
transgressing the traditional boundaries of the disciplines
involved. It is our firm conviction that the encounter between
art and computing holds the potential for interdisciplinarity in
this strong sense, and our ongoing dialogue might represent a
possible step in that direction.
The authors are indebted to Dagstuhl, in Germany, where
many of the ideas in this paper flourished in a synergistic
week-long session. We also would like to acknowledge the
Leonardo organization for their co-sponsorship of the event.
Paul Fishwick would like to thank his graduate students in the
RUBE Project (Minho Park, Jinho Lee, and Hyunju Shim),
the National Science Foundation under grant EIA-0119532
and the Air Force Research Laboratory under grant F30602-
01-1-05920119532. Jane Prophet’s contribution is part of the
Cell collaboration and has been written following discussion
with: Mark d’Inverno, Peter Ride, Rob Saunders, Neil Theise
and Katrina Jungnickel. Cell research has been conducted
with awards from The Wellcome Trust sciart; Shinkansen
Future Physical ‘BioTech’ and The Quintin Hogg Trust.
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Aesthetic Computing Manifesto The application of computing to aesthetics and the formation of art and design has a long history. With the integration of hardware, software and cybernetics in the 1960s, computer art emerged as a new art form. We propose to look at the complementary area of applying aesthetics to computing [1]. Computing and its mathematical foundations have their own pre-existing aesthetics; however, there is currently a relative lack of variety of these aesthetics, in contrast with art, which has a long history containing a multitude of historical genres and movements. We wish to strike a balance between cognitive and material aesthetics. Software as written in text or drawn with flow-charts may be considered elegant, but that is not to say that the software could not be rephrased or re-presented given the more advanced media technologies that are available to us today. Such re-presentation need not compromise the goal of abstraction, which is a necessary but not sufficient condition for mathematics and computing, as meaning, comprehension and motivation may be enhanced if the presentation is guided by a pluralism of aesthetic choices and multiple sensory modalities.
Artforum (June, 1967). The editor has written me that he is in favor of avoiding "the notion that the artist is a kind of ape that has to be explained by the civilized critic". This should be good news to both artists and apes. With this assurance I hope to justify his confidence. To use a baseball metaphor (one artist wanted to hit the ball out of the park, another to stay loose at the plate and hit the ball where it was pitched), I am grateful for the opportunity to strike out for myself. I will refer to the kind of art in which I am involved as conceptual art. In conceptual art the idea or concept is the most important aspect of the work. When an artist uses a conceptual form of art, it means that all of the planning and decisions are made beforehand and the execution is a perfunctory affair. The idea becomes a machine that makes the art. This kind of art is not theoretical or illustrative of theories; it is intuitive, it is involved with all types of mental processes and it is purposeless. It is usually free from the dependence on the skill of the artist as a craftsman. It is the objective of the artist who is concerned with conceptual art to make his work mentally interesting to the spectator, and therefore usually he would want it to become emotionally dry. There is no reason to suppose, however, that the conceptual artist is out to bore the viewer. It is only the expectation of an emotional kick, to which one conditioned to expressionist art is accustomed, that would deter the viewer from perceiving this art. Conceptual art is not necessarily logical. The logic of a piece or series of pieces is a device that is used at times, only to be ruined. Logic may be used to camouflage the real intent of the artist, to lull the viewer into the belief that he understands the work, or to infer a paradoxical situation (such as logic vs. illogic). Some ideas are logical in conception and illogical perceptually. The ideas need not be complex. Most ideas that are successful are ludicrously simple. Successful ideas generally have the appearance of simplicity because they seem inevitable. In terms of ideas the artist is free even to surprise himself. Ideas are discovered by intuition. What the work of art looks like isn't too important. It has to look like something if it has physical form. No matter what form it may finally have it must begin with an idea. It is the process of conception and realization with which the artist is concerned. Once given physical reality by the artist the work is open to the perception of al, including the artist. (I use the word perception to mean the apprehension of the sense data, the objective understanding of the idea, and simultaneously a subjective interpretation of both). The work of art can be perceived only after it is completed.
Marrying traditional methods of computer programming with an artistic temperament allows the birth of a new phenomenon: the aesthetic program. The work of the author and his students builds on visual ap-proaches in programming as well as in software modeling, leading toward a gradual evolution from program to model. The need for the aes-thetic model is increased with the importance of personalized, individually tailored media, as found with web-based style sheets and the economic movement termed mass customization. The author and his students have formulated the rube Project methodology around the use of 3D web-based virtual-world model construction. Initial results suggest that these models are artistic, while containing symbolism and concise metaphoric mapping sufficient to be executable on a computer.
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Presently, there is little assistance available to developers who would like to create and integrate formal software models with customized visualizations of the architecture and operation of such models. To help solve this problem, the rube framework presents methodologies and development tools for both formal software modeling and for the creation of customized, three-dimensional software model visualization. As prescribed by rube, these models are multimodels and their visualizations are based on user-specified metaphors and aesthetics. We describe rube, its goals and present an example in the form of a simple operating system task scheduler. This example model is developed step-by-step with the rube modeling methodology and associated development tools to demonstrate the practical feasibility of integrating customized software model visualization with formal software modeling processes.