of Artificial Art, Amsterdam
Computation and Cognition.
Could the digital
computer have an essential influence on the art of the future, and
be more than just another new technical tool? It is hardly possible
to raise this question without thinking rightaway about the fantastic
promises of cognitive science and artificial intelligence. These
new branches of science and technology are committed to the development
of precise mathematical models of human cognition -- models which
are inspired by the digital computer and which, in their turn, can
be implemented on such a computer. These promises, taken at face
value, suggest the ultimate possibility of "artificial artists":
completely automatic computer art, produced by carefully calibrated
simulations of human emotion and human intelligence, equipped with
extensive databases about for instance everyday life, international
politics, art history, and the properties of paint.
Whether this would in principle be possible is a question which
often gives rise to passionate philosophical discussions. More interesting,
however, is the question about the practical feasibility of this
idea: is the state of technology such that it makes sense to start
to work on this? To set up, for instance, a research program spanning
a few decades in order to develop the various algorithms and data
bases that together will constitute the artificial artist? This
practical question must be answered negatively. Artificial Intelligence
research has failed to produce plausible models of human cognition
so far, and there is no reason to expect that it will become much
more successful very soon. The complexity of existing computational
models can be gauged by looking at the "expert systems"
which have recently become popular: relatively simple algorithms
with a limited, precisely demarcated task. The amount of knowledge
that a human expert can bring to bear on a problem, and the versatility
that such an expert displays in applying this knowledge, are gigantic
when we compare them to the capacities of current "expert systems".
For the time being, the project of emulating human cognition on
digital computers is frought with fundamental problems. The results
of A.I. research suggest that there are two kinds of cognitive processes,
which differ in essential respects. On the one hand there are perceptual
processes, which aim at the classification of sensory data; on the
other hand there are the formal symbol manipulations that we employ
in arithmetic, board games, legal reasoning, and other formally
defined situations. The data structures and algorithms that are
required to perform these two kinds of cognitive processes, turn
out to be very different. Today's digital computer is primarily
equipped for symbol manipulation; if one wants to implement, on
this kind of machine, the associative thought processes that constitute
perception, one must spell out these processes in an extremely cumbersome
way. For human cognition, it is the other way around: humans are
capable of both kinds of cognition as well, but in this case the
perceptual processes are the more basic ones.
The most important
challenge of A.I. research may be to implement, on digital computers,
the human cognitive processes for which that kind of hardware is
not optimally suitable. So far, this hasn't been very successful.
A.I. rules in the areas where symbol manipulation plays a crucial
role; but the computer's perceptual capabilities remain extremely
meager. We may predict, for instance, with reasonable certainty
that when the world champion chess will be a computer program, there
will not yet be a program that can reliably distinguish twenty human
faces, if lighting and camera angle are allowed to vary a little.
For this reason, emulating the decision processes of the human artist
is not a realistic goal -- and that is not because artistic processes
are necessarily more difficult to mimic than other mental processes,
but because the existing models of all cognitive processes
are inadequate. Even if 'creativity' would be a completely
mythical notion, and genuine conceptual innovation were a negligible
element in artistic practice -- even then, the artificial artist
is not in the offing, and neither are the artificial engineer, the
artificial pastry-cook or the artificial kindergarten pupil.
This conclusion may not seem very surprising. It resonates with
a popular prejudice: that the artistic role of the computer should
obviously be limited to that of a technical tool, because the inspiration
that underlies all true art happens to be the prerogative of the
human artist. Even artists who largely rely on the computer to design
their work, and who are inspired by the computer's possibilities
and limitations, often pride themselves on their creativity, and
view the computer as "only a tool, like the sculptor's chisel".
This received opinion, however, underestimates the unique new opportunities
that the computer offers.
In certain kinds of cognitive skills, computers outperform people
consistently by a large margin: for instance in making extensive
calculations, in systematically checking long lists of possibilities,
in manipulating intricate algebraic formulas, and in drawing random
samples from large sets of items generated by complex definitions.
These capabilities are not enough to emulate human thinking, but
their implementation embues the computer with an independent, inhuman
style of thinking, which is interesting because it gives rise to
unforeseeable results. This becomes apparent if we take a closer
look at the successes of Artificial Intelligence. These are mostly
due to programs that solve limited, formally defined problems, which
do not require the perceptual capabilities that are only possessed
by higher animals. Examples are programs that play simple games,
and expert systems for well-defined design problems, such as the
lay-out of integrated electronic circuits. A brief glance at the
behavior of such programs yields an interesting insight: they employ
a rather different procedure than the human expert who solves the
same problem. The computer program finds the best solution by systematically
investigating all possibilities. The human expert, who is unable
to face the full richness of the whole search space, thinks in terms
of a limited repertoire of prototypes and conventions, and explores
minimal variations on these if necessary.
The procedural differences also lead to different results. In dealing
with a technical problem which allows different solutions that can
be compared as being more or less optimal, the computer program
will often come up with the better results, because it has looked
more systematically at the different possibilities; that is why
the electronics industry employs computers to design integrated
circuits. Computer-generated solutions differ in interesting ways
from human designs: they are often surprising and unconventional.
When a computer program plays a demonstrably correct and winning
chess end-game, it may very well seem bizarre and incomprehensible
to a human observer. In such a case, the program shows that there
are many possibilities which the chess game allows, but which the
human perspective on chess overlooks.
If we do not care about emulating human behavior, but are interested
in unexpected and unconventional results, the computer program may
thus be superior. And art production is an obvious case in point.
Though many artists have a hang-up about originality, they often
produce works which look very much like those of their role-models
and colleagues. We therefore propose a more analytic approach to
art production: first define a mathematical system which charts
all formal and perceptual possibilities as thoroughly as possible,
and then implement computer programs which generate random images
on the basis of this system. This approach may eventually yield
more interesting results then the necessarily more limited method
of the traditional individual artist.
To generate artworks by means of algorithms that make random
choices from a mathematically defined class of possibilities, is
not a new idea. There is a tradition known as "chance art",
which aims at the production of art works which are not determined
by the artist -- arbitrary artworks, random samples from the space
of all possibilities. The attitude behind this resembles the stance
of artists who exhibit nothing or who declare the whole world to
be an artwork: one avoids choices and positions, one throws the
observer back on his inalienable responsibility for his own esthetic
experiences, and draws attention to the esthetic interpretability
So far, the project of making 'arbitrary' paintings has only been
realized to a limited extent. In a way, painters like Picabia and
Polke come closest, when they mingle intuively selected elements
from various domains of life and art. But chance art based on clear,
hard mathematical probabilities involves a paradox: more explicitly
than any other genre, it displays the conceptual context that frames
it. When, for instance, graphic designs are defined as grids of
pixels that may be either black or white, drawing a random sample
tends to yield a grey-looking plane (Morellet). One gets somewhat
more variation by putting a random number of dots with a random
size at random locations on the plane (De Vries), or by drawing
a random number of lines with a random thickness through random
points in random directions (Mandelbrot).
Constructions for making random shapes can also be more complex.
For instance, Lévy's construction for random mountainscapes,
as described by Mandelbrot: superimposing infinitely many infinitely
small 'edges' which run across the plane through random points in
random directions. (An 'edge' is a step-function on the plane: on
one side of a straight line, the plane is elevated a certain amount.)
Cutting a horizontal plane through such a random mountainscape,
yields a 'map' with random coastlines.
To conclude this quick enumeration of elementary principles, I want
to point to the phenomenon of Lissajous patterns, where a shape
is created by multiplying different harmonic oscillations. More
complex patterns arise when more complex movements are multiplied
(cf. 'Machine Drawings').
So far, chance artists have been content with applying probabilistic
operations within such simple systems. That is sufficient if all
one wants to do is put forward the very idea of chance. But
to really take on the project of the arbitrary painting, we need
more; we need a formal language which allows us to assign distinct
codes to perceptually different paintings, but also to assign the
same code to perceptually equivalent paintings whose details may
nevertheless differ considerably (as in the case of the different
instantiations of Morellet's random pixels). Such a language is
an algebra: it specifies a set of elementary shapes and a set of
operations which map shapes onto other, possibly more complex shapes.
Algebras like this have been developed already for characterising
specific styles. Harold Cohen, for instance, embued his drawing
program AARON with an original style reminiscent of the COBRA painters.
Programs which try to mimic existing artists have also been developed,
for instance for Miró and Diebenkorn. The 'arbitrary painting'
project, however, requires a system with a much richer repertoire
of stylistic possibilities, and with the capability to exploit those
possibilities in a very flexible way -- so that the degree of stylistic
coherence within a painting (or within an exhibition) is itself
a parameter whose value can be chosen at random.
From a completely different perspective, the psychology of Gestalt
perception has also developed some coding languages which are relevant
for our purpose -- for instance, in the work by Leeuwenberg and
Buffart in Nijmegen on the mental representation of drawings built
up out of straight line segments, and in the work by Lerdahl and
Jackendoff in Boston on the perception of music.
It is clear
that the machinery needed for the 'arbitrary painting' project would
have to be substantially richer and more complex than any of these
currently existing systems. New coding languages are needed to begin
to conceptualize the range of possible images in a halfway adequate
fashion. And drawing random samples from the space defined by such
a language, and calculating the detailed execution of the various
operations, will not be possible without a computational implementation.
Art is often viewed as a means of communication, employed by high-minded
individuals to convey profound ideas. In this view it is self-evident
that artworks are designed, made, assembled, or at the very least
chosen by artists: the artist is responsible for the artwork; the
validity of the artwork is grounded in the artist's sense of life.
The actual production and reception of art in our society is a very
different matter, however: works of art constitute material for
an unconstrained process of esthetic reflection and interpretation,
which is not subject to any rules. In Marcel Duchamp's words: 'the
spectator makes the picture'. As a consequence, anything whatsoever
can serve as input for the esthetic reflection process; the special
status of the artwork is abolished.
Another point to note, is that the esthetic experience is in fact
not a particular kind of extraordinary psychological state, but
an ingredient of almost all experience --whenever objects, situations
and processes which are not elements of a predefined code, are nevertheless
employed by our mind as symbols for other (usually vaguer and more
complex, perhaps intrinsically more important) things, circumstances
and developments. Every object, every situation, every process thus
has an infinite potential of meanings.
the first unequivocal articulations of this idea about esthetics
is provided by Marcel Duchamp's 'readymades' -- simple objects from
the real world, which he exhibited as works of art. Duchamp's gesture
is sometimes interpreted as a celebration of the sublime autonomous
creative power of the artist's Kunstwollen, but I would like
to argue for a different interpretation. It is true that Duchamp
chose his objects quite judiciously, but one should not be mistaken
about the nature of his circumspection. Duchamp has made explicit
statements about this, but one can also read it off the objects
themselves. They are very ordinary, 'neutral' objects: schoolbook,
coat-rack, hat-rack, bicycle-wheel, bottle-rack, snow-shovel, plastic
bucket, coffee grinder, typewriter-cover: standard objects, drawing
Duchamp's own words: "It is very difficult to choose an object,
because after a few weeks you start to like it or to hate it. One
must approach a thing with indifference, as if one has no esthetic
emotion. The choice of readymades is always based on visual indifference
and, at the same time, on the complete absence of good or bad taste." Like the chairs and tables which always represent 'the object' in
philosophical discussions, Duchamp's readymades are 'free variables',
schemas that all other objects can substitute for, lacking specific
properties which would block unification. [The preponderance of
racks and containers might be taken to symbolize exactly this 'non-property'.]
Duchamp's readymades imply the esthetic interpretation of everything.
They imply the abolishment of an esthetics in the traditional sense
-- of an esthetics which assigns a different value to different
things and experiences -- that appreciates paintings by brilliant
artists more highly than children's drawings or technical diagrams
-- which looks differently at bronze sculptures than at supermarkets
or natural phenomena. They imply that esthetic perception is viewed
as a cognitive process that is not tied to the art-context -- a
process that has its origin and its justification in the observer,
and that can be applied to arbitrary material.
The readymade implies that art history is finished: the artwork
looses its special status, and art history its incentive. But at
the same time it suggests a new beginning: to practise the esthetic
interpretation of everything. Important movements in twentieth-century
art betray an awareness of this: surrealism, nouveau réalisme,
pop art, postmodernism all put forth some version of this idea.
But they also take it back rightaway, by defining themselves as
a style, with a focused interest in certain aspects of reality,
and sometimes with preconceived ideas about how that reality is
to be interpreted.
Other artists have thematized the esthetic interpretability of the
real world in an explicit, somewhat humorous fashion: a socle with
the whole world on it, a signature on a glass pane, paintings with
the word "everything". Or, complementarily, they chose
the uselessness and superfluousness of art as their topic: paintings
with the word "nothing", mirrors, empty canvases, empty
frames, empty rooms.
The project of artificial art shows that the awareness of the esthetic
interpretability of everything is indeed a new beginning -- the
beginning of an activity that is related to art, but at the same
time clearly distinguished from traditional art practice. The crucial
thing is that we do not know what 'everything' is! In our conventional,
habitual thinking we tend to content ourselves with what we encounter
already in the existing world, and what looks very much like it.
The computer, however, makes it possible now to explore the combinatorics
of the space that is defined by our full repertoire of visual elements
and operations. Just as photography has been used for 150 years
now to find out what we can see in the world we live in, the computer
will systematically explore the esthetic possibilities of our cognitive
Chance and Architecture
Chance art faces the meaninglessness of art and life, and draws
constructive conclusions from this state of affairs. It may thus
be the only adequate reaction to the current impasse in autonomous
visual art. But in the applied arts a similar step is necessary.
In architecture, for instance, one must deal with the issue that
style is unavoidable but that every style is problematic.
is impossible. When the functions are fixed, many choices remain.
The architect must confess to a personal esthetic choice or to a
social/cultural tradition. In designing buildings for the general
public or for unknown future users, such a confession is out of
And efficiency is not an objective criterion that defines the optimal
solution among different functionally equivalent ones. Every efficiency
implies an esthetics. At best, this is a stance concerning the true
nature of materials and their proper use, and a normative stylization
of daily life. In the worst case (efficiency as an 'economic' criterion: "always choose the cheapest solution"), it boils down
to the mean esthetics of money. Architecturecannot avoid to symbolize
something. Architecture which is economically efficient in the narrowest
sense, symbolizes the Margin of Profit as the highest good.
Postmodernism is a neo-victorianism. The eclectic application of
various historical styles, intended as a solution for the dilemma
sketched above, results in a narrow, fashionably defined, neo-style.
The call for a style-transcending meta-style remains unanswered.
The meta-style that is needed here, can be developed in the context
of Artificial Art project described above, which should embrace
a mathematical, perceptually oriented analysis of all known styles.
After an explicit analysis of these styles, all possible syntheses,
interpolations and extrapolations of them can be generated at will
by means of computer programs.
Because the production of art is left to the arbitrary impulses
and shortsighted ambitions of individual artists, most art is conventional
and predictable. Human creativity is often over estimated. Well-designed
generative algorithms can yield more surprising results than toiling
For human persons it is very difficult to survey all possible combinations
of a set of items. For this reason, many structures that are implicitly
given in the visual language of our cognitive system have never
been witnessed yet. The algorithmic exploration of explicit visual
grammars will make these structures visible. I imagine the following
division of labour: people define the elements and operations of
the visual algebra, and thereby specify an infinite combinatorial
space; computer programs draw random samples from this space. Progress
by human abstraction and machine systematicity -- just as in science.
The interpretation of the artwork will be decoupled from all anecdotal
information about the artist. Image-generation software will be
developed through a collective, analytic, un-expressive effort.
Art will not revolve around the individual artist any more. A Copernican