Visual Intelligence: The First Decade of Computer Art (1965-1975)
Author(s): Frank Dietrich
Source: Leonardo, Vol. 19, No. 2 (1986), pp. 159-169
Published by: The MIT Press
Stable URL: http://www.jstor.org/stable/1578284
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VisualTheFirst

DecadeofIntelligence:
Computer Art(1965-1975)

FrankDietrich
Abstract-The author traces developmentsin computerart worldwidefrom 1965, when the first computer
art exhibitions were held by scientists, through succeeding periods in which artists collaborated with
scientists to create computerprogramsfor artistic purposes.The end of the first decadeof computerart wasmarked by economic, technological and programmingadvancesthat allowed artists more direct access tocomputers, high quality images and virtually unlimited color choices.

I. INTRODUCTION
The year 1984 has been synonymous withthe fundamental Orwellian pessimism ofa future mired in technological alienation. Yet one year later, in 1985, we arecelebrating the official maturity of an art
form born just 20 years ago: computer
art. These adjacent dates, one fictional,
the other factual, share an intimate
relationship with technological development in general and the capabilities ofimaging machines in particular.

scientists were motivated mainly byresearch related to visual phenomena:visualization of acoustics and the foundations of binocular vision. Researchersat
Bell contributed a wealth of information
to spur the growth of computer graphics.
Numerous computer animations were
produced, mostly for educational purposes, but a few artistic experiments werealso conducted. Julesz and Noll workedon the display of stereoscopic images.
Noll developed the mathematics for Ndimensional projections, as well as a 3-Dtactile-input device. Harmon andKnowlton devised automatic digitizing
methods for images, work related to a
project on sampling and plotting of voice
data under the direction of Manfred
Schroeder. Ken Knowlton contributed
several graphics languages for animation.
Throughout this article I will discuss theresearchconducted at Bell Labs in further
detail [1-5].
The German center of activity wasestablished at the Technische Universitat
Stuttgart under the influence of philo-

II. EARLY WORK AND THE FIRSTCOMPUTER ART SHOWSComputer art represents a historicalbreakthrough in computer applications.
For the first time computers became
involved in an activity that had been the
exclusive domain of humans: the act of
creation. The number of Ph.D.'s involved
emphasized the heavily academic natureof the art form.
The first computer art exhibitions,which ran almost concurrently in 1965 in
the US and Germany, were held not byartists at all, but by scientists: Bela Julesz
and A. Michael Noll at the Howard Wise
Gallery, New York; and Georg Nees andFrieder Nake at Galerie Niedlich, Stuttgart, Germany.
Noll and Julesz conducted their visualresearch at Bell Laboratories in New
Jersey. The Murray Hill lab became oneof the hotbeds for the development ofcomputer graphics. Also working there
were Manfred Schroeder, Ken Knowlton,
Leon Harmon, Frank Sinden and E.E.
Zajac, who all belonged to the first
generation of 'computer artists'. TheseFrank Dietrich (artist, computer graphics consultant), 3477 South Court, Palo Alto, CA 94306,
U.S.A.
Copyright ? 1985 IEEE. Reprinted with permission,from IEEE ComputerGraphicsand Applications,Vol. 5, No. 7, pp. 34-35, July 1985.

Pergamon Journals Ltd.
Printed in Great Britain.
0024-094X/86$3.00+0.00

an1966.Anearlyattemptatsimulating
Fig. 1. A.MichaelNoll,BridgetRiley'sPainting"Currents",
existingpaintingwith a computer.Muchof 'op art' uses repetitivepatternsthat usuallycan beterms.Thesewaveforms
weregeneratedas parallelsinusoids
expressedverysimplyin mathematical
Pietwithlinearincreasingplotter.A.MichaelNollalsoapproximatedperiodanddrawnona microfilm
Mondrian'spaintingCompositionwith Lines statisticallyand created a digital versionwithof bothpictureswereshownto 100subjects,andnumbers.Xerographic
reproductions
pseudorandom
the computer-generated
picturewas preferredby 59.

LEONARDO, Vol. 19, No. 2, pp. 159-69, 1986

159

C. Knowlton
andLeonHarmon,StudiesinPerception
andHarmonmadethispictureat BellLaboratories
inMurrayHill,
I, 1966.Knowlton
Fig.2. Kenneth
andprobablythefirst'computer
NewJersey.It is anearlyexampleof imageprocessing
nude'.It wasexhibitedintheshow"TheMachine"at theMuseumof
ModernArtin NewYorkin 1968.Scanninga photograph,theyconvertedtheanalogvoltagesintobinarynumbers,whichwerestoredon magnetictape.
Anotherprogramassignedtypographicsymbolsto these numbersaccordingto halftonedensities.Thusthe archetypeof artistictopics,the nude,isof electronicsymbolsprintedby a microfilmplotter.
represented
by a microcosmos

sopher Max Bense. Bense's main areas ofresearch covered the history of scienceand the mathematics of aesthetics. He
coined the terms 'artificial art' and'generative aesthetics' in his main work,
Aesthetica [6].
Advances in both computer music andpoetry (or text processing) formed thecontext and also offered initial guidelines
for computer art. Computer-generated
texts were produced in Stuttgartbeginningin 1960. An entire branch of text analysis
relied heavily on computer-processed
statistics dealing with vocabulary, lengthand type of sentences, etc. [7].
Electronic music studios predated
computer art studios, leading a numberof visual artists to seek information about
computers from university music departments. Dutch artist Peter Struycken,
for instance, took a course in electronic
music offered by the composer G.M.
Koenig at one of the few European
centers, the Instituut voor Sonologie at
the Rijks Universiteit at Utrecht [8].
Lejaren A. Hiller programmed the "Illiac
Suite" in 1957 on the ILLIAC computerat the University of Illinois, Champaign,andthewell-known
composed"Computer Cantata" with Robert A.
Baker in 1963 [9]. Some musicians who
were using computers as a compositional
tool also created graphics in an attempt tofoster synergism between the arts (Iannas
Xenakis, Herbert Briin, etc.)[10-19]. The
filmmaker John Whitney, on the other
hand, began structuring his computer
animations according to harmonies of themusical scale and later called this concept
Digital Harmony [20].

160

Only in a second phase did artists
become involved and participate with
scientists in three large-scale shows:"Cybernetic Serendipity," organized in
London for the Institute of Contemporary Art by Jasia Reichard (1968),"Some More Beginnings," a show
organized by Experiments in Art andTechnology at the Brooklyn Museum,
New York (1968), and "Software,"curated by Jack Burnham at the Jewish
Museum in New York (1970). The

I
Fig. 3. CharlesA. CsuriandJamesShaffer,Sine WaveMan,1967.Thispicturewonfirstprizein

Computersand Automationmagazine's annual computerart competition in 1967. Initially the artist
drewa humanface and coded a handfulof selected coordinatesfrom the linedrawing.This data served
as fixed points for the applicationof Fourier transforms.The result was a numberof sine curveswith
different slopes, although each shares the seed points from the drawing of the face.

Dietrich, Visual Intelligencecatalogs of these shows still represent
some of the best overviews of emerging
approaches to computers and othertechnologies for artistic purposes [21-24].
These shows presented the first results
and publicly questioned the relationshipof computers and art. They attracted
many more artists to the growing field ofcomputer art but did not succeed in
making the art world in general more
receptive to the new art form.
III. THE TECHNOLOGICAL ARTISTAND THE COMPUTER
When we look at the handful of earlycomputer art aficionados, certainpatterns
emerge. All scientists and artists in thisgroup belong to the same generation,born between the two World Wars,
approximately 1925-1940. Their heritage
is not bound by national borders;ratherit
is international, representing the highly
industrialized countries of Europe, North
America and Japan.
Initially, artists saw a very utilitarianadvantage in using the computer as anaccelerator for "high-speed visual
thinking" [25]. Robert Mallary calls thisthe synergistic use of the computer in thecontext of man-machine interactions. He
refers to the computer's "application as atool for enhancing the on-the-spot
creative power and productivity of theartist by accelerating and telescoping thecreative process and by making available
to its user a multitude of design options
that otherwise might not occur to him"
[26].
Because these artists were not interested
in descriptive or elaborated painting, they
could allow themselves to relate to thesimple imagery generated by computers.
Their interest was fueled by othercapabilities of the computer, for instanceits ability to allow the artist to be an
omnipotent creator of a new universe
with its own physical laws. Charles Csuri
pointed out this far-reaching concept in
an interview: "I can use a well-known
physical law as a point of departure, andthen, quite arbitrarily, I can change thenumericalvalues,which essentiallychanges
the reality. I can have light travel fivetimes faster than the speed of light, and ina sense put myself in a position of creating
my own personal science fiction" [27].
Many of the artists were constructivists. They were accustomed to arranging form and color logically andvoluntarily restrictingthemselves to a few
well-defined image elements. They tried
to focus on the act of seeing andperception by stripping away any notionof content. The French Groupe deRecherche d'Art Visuel, or GRAV, was aFig. 4. GeorgeNees, Sculpture,1968. One of the earliestsculpturescreatedcompletelyundercomputercontrol. This piece was exhibitedat the Biennale in Venice in 1969. Nees hada long-standing
interest in the study of artificial visual complexity in connection with the chance-determination
reaction. He programmeda Siemens 4004 computerto generate pseudorandomnumbers,whichweretightly controlled to determinewidth, length and depth of rectangularobjects. The three-dimensional
data were stored on magnetic tape and used to drive an automatic milling machine off line. The
sculpture was cut from a block of wood.

Fig. 5. Frieder Nake, Matrix Multiplications, 1967. These four pictures reflect the translation of amathematicalprocess into an aesthetic process. A squarematrix was initially filled with numbers.The
matrix was multipliedsuccessivelyby itself, andthe resultingnew matricesweretranslatedinto imagesof predeterminedintervals. Each numberwas assigned a visual sign with a particularform and color.
These signs were placed in a raster according to the numericvalues of the matrix. The images werecomputed on a AEG/Telefunken TR4 programmedin ALGOL 60 and were plotted with a ZUSE
GraphomatZ64. A portfolio with 12 drawingswas publishedand sold in 1967 by Edition Hansjoerg
Mayer, Stuttgart, Germany.

Dietrich, Visual Intelligence161

Fig. 6. Tony Longson, Quarter#5, 1977. As a sculptorTony Longson got interestedin the perceptionof space and how it is supportedby perspectiveprojectionand parallaxvision. Quarter#5 is the last ofa series of pieces started in 1969. All are madeof foursheets of Perspex mountedwithsmall intervalson
top of each other such that the viewer sees throughall four layers. The complete image consists of anarrangementof dots in a rectangular grid. But this image has been decomposedrandomly into four
sections, so that only a subset of dots is engravedinto each sheet of plastic. Viewersapproachingthe
piece will see first an apparentlychaotic distributionof dots. However, once the vieweris positionedin
one of four fixed viewpoints,chaos will suddenlychange into a highly structuredorder of dots in one of
the quadrants[58].

proponent of this direction and became
instrumental in the Op Art and Kinetic
Art movements of the 60's [28]. Vera
Molnar, a cofounder of GRAV, conceived a "Machine Imaginaire" to enable
her "to produce combinations of forms
never seen before, either in nature or inmuseums, to create unimaginableimages."
She realized that the computer could
permit her "to go beyond the bounds oflearning, cultural heritage, environment-in short, of the social thing, which wemust consider to be our second nature"[29]. Conventional aesthetics and theirsocial-psychological connotations wereseen as a hindrance to creative visualresearch. It was precisely the computer's
nonhumanness that was understood tofree art from these influences. Art critics
who pointed out the cool and mechanicallook of the first results of computer art
did not grasp the implications of thisconcept.
According to the Japanese artist
Hiroshi Kawano, who started producing
computer art in 1959 [30], humanstandards of aesthetics are not applicable162

to computer art. Instead the works
generated by a computer requirefrom theartist (or critic) "a rigorous stoicism
against beauty." For Kawano, thecomputer artist's only function is to teachthe computer how to make art by
programming an algorithm. Thus theartist/programmer has become a "metaartist," and the executing artist could be
the computer itself, the "art-computer"[31].
One artist who explicitly taught thecomputer is Harold Cohen. He wanted toautomate the process of drawing, or, tobe more precise, Cohen wanted to have acomputer simulate his personal style ofdrawing. Cohen set out in 1973 to create
an expert drawing system at Stanford
University's Artificial Intelligence Laboratory. The computer was programmed
to model the essence of Cohen's creative
strategies. The program contained a large
repertoire of various forms and shapes hehad been using previously in his paintings. The other main component was a'space-finder' to establish compositional
relationships heuristically between forms

Dietrich, Visual Intelligenceon one lane. Well-defined rules andrandom number generators guaranteed
the creation of never-endingvariations ofdrawings with a very distinctive style[32, 33].
Cohen's project AARON is an earlyexample of a functioning harmonic
symbiosis between man and machine thatenables the team to achieve a top
performance. Increasingly sophisticatedrelationships between artists and computers have been classified by Robert
Mallary in his article "Computer Sculpture: Six Levels of Cybernetics." Hespeculates that the computer could
develop into an autonomous organism,
capable of self-replication. Even if themachines could never actually be "alive,"
Mallary suggests their potential superiority. "The computer, while not alive in any
organic sense, might just as well be, if itwere to be judged solely on the basis of its
capabilities and performances-which
are so superlative that the sculptor, like achild, can only get in the way" [34].
But this prediction sounded like purefantasy to those trying to enable thecomputer to assist the artist with very
simple tasks. Especially in the beginning,interfacing with computers required
artists to collaborate extensively with
programmers.

IV. COLLABORATION OF ARTISTSANDSCIENTISTS/PROGRAMMERS/ENGINEERS

Usually artists cooperated with
scientists because only scientists could
provide access to computers in industrial
research labs and university computer
centers. But artists needed the programming expertise of scientists evenmore. Some collaborations prospered
over many years and led to successfulachievements in custom-designed programs for artistic purposes [35].
Even so, Ken Knowlton described thedifferent attitudes of artists and programmers as a major difficulty. In
Knowlton's view artists are "illogical,
intuitive, and impulsive." They needed
programmers who were "constrained,
logical, and precise" as translators andinterfaces to the computers of the 1960s[36]. But the first of a growing breed oftechnological artists with hybrid capabilities started to appear, too. Manfred
Mohr proudly declared that he was selftaught in computer science, Edvard Zajec
learned programming and today teaches
it to art students, and Duane Palyka
holds degrees in both fine arts andmathematics.

V. THE FIRST GRAPHICSLANGUAGES

Early attempts at graphics languages
fell into one of two categories. Either they
were graphics subroutines implemented
in one of the common programming
languages and callable from them, or they
were written in machine language and set
up their own syntax and command set or
vocabulary. The first graphics extensions,
G1, G2 and G3 by Georg Nees, forinstance, were written in ALGOL 60 andcontained only commands for pen
control and random number generators[38]. More elaborate was Mezei's
SPARTA, a system of Fortran calls
incorporating graphics primitives (line,
arc, rectangle, polygon, etc.), different
pen attributes (dotted, connected, etc.),
and transformations (move, size, rotate).
A further development led to ARTA, aninteractive language based on light-pen
control. ARTA also provided subroutines for key-frame interpolation, allowing both the interactive drawing of two
key frames and the description of the typeof interpolation with a function [39]. A
language extension similar to Fortranwas GRAF, written by Jack Citreon etal., at IBM; GRAF also offered optional
light-pen input [40]. Even though thesegraphics extensions made programmingin machine code superfluous, they stillrequired programming in Fortran or
ALGOL 60.
In the second group of graphics
languages we find Frieder Nake's COMPART ER 56 as well as Ken Knowlton's
languages, BEFLIX and EXPLOR. The
names of these programming environments are indicative of either function- or
machine-dependent implementation of
the language. COMPART ER 56, forinstance, refers to a particular computer,the Standard Elektric ER 56, for which
the language has been written. ER 56
contained three subpackages, a spaceorganizer, a set of different random
number generators, and selectors for therepertoire of graphic elements. Nake used
COMPART ER 56 extensively to create
more than 100 drawings [30].
BEFLIX (a corruption of Bell Flicks)
was designed to produce animatedmovies on a Stromberg-Carlson 4020
microfilm recorder. Points within a 252by-184 coordinate system could becontrolled, each having one of eight
different shades of gray. In contrast withtoday's frame buffers, which hold theimage memory in theirbit map, BEFLIX's
images resided in the computer's main
memory. As an animation language it
provided instructions for several motion
effects as well as for camera control.
Knowlton had initially hoped that artists

would learn the language to program
their own movies, but he came to realizethat they usually wanted to create
something the language could not
facilitate, and they also shied away fromprogramming. Therefore he accommodated the artists by, for example, writing
special extensions to BEFLIX for Stan
Vanderbeek, or creating a completely
new language, EXPLOR (images from
EXplicit Patterns, Local Operations andRandomness), for Lillian Schwarz [41].
None of the graphics languages mentioned received widespread use, partly
because their implementation was mach-ine dependent and also because eachlanguage was restricted in scope. The
tools were useful for their inventors' goals
but lacked sufficient flexibility and easeof use to accommodate the creative ideas
of many different artists. BEFLIX,
however, was installed in several art
departments and provided the helping
hand many programmershad given whencollaborating individually with artists.
At Ohio State University Charles Csuri
directed, over many years, the development of several graphics languages, alldesigned for ease of use, interactive
control, and animation capabilities. One

Fig. 7. Herbert W. Franke,Portrait AlbertEinstein, 1973. A photographof Einstein was scanned anddigitized optically. The data was stored on tickertape and displayed on a CRT using programs
developed for applications in medical diagnosis. Herbert Franke generated the colors with random
numbersand by smoothingcontourlines. This series of portraitsgraduallybecomesmoreabstractand
thus fuses visually Einstein's portrait and a nuclear blob.

Dietrich, Visual Intelligence163

incarnation, GRASS, or GRAphics
Symbiosis System, was designed by Tom
DeFanti, first for a real-time vector
display and later as ZGRASS for a Z80based animation language for artists.
This language has been widely used byprogramming artists, which indicatesthat it possesses sufficient generality tosupport different imaging strategies aswell as suitable command and execution
structures to adapt to artistic creation[44, 45].
VI. THE FIRST GRAPHICS
SYSTEMS
Let's turn the clock back again to the
1960s when the microcomputer had noteven been conceived. The computers used
initially were large mainframes, soon
followed by minicomputers. Suchequipment cost anywhere from $100,000
to several million dollars. All thesemachines required air conditioning andtherefore were located in separate computer rooms, which served as fairly
uninhabitable 'studios'. Programs anddata had to be prepared with the
keypunch; then the punch cards were fed
into the computer, which ran in batchmode. In general, the systems were notinteractive and could produce only still
images.
Pen plotters, microfilm plotters andline printers produced most of the visual
output. The first animations were createdby plotting all still frames of the movie
sequentially on a stack of paper or
microfilm. Motion could only be reviewed after these stills had beentransferred to 16-mm film and projected.
Only a few artists had the opportunity touse even more expensive vector displays
introduced in the late 1960s by companies
such as IBM or newly founded graphics
manufacturers such as Evans & Sutherland, Vector General, and Adage, whose
displays cost between $50,000 and$100,000. These displays featured very
high addressability, up to 4000 by 4000
points, and could update coordinates fastenough to support real-time animation of
wireframe models in 3-D [46]. One of thefirst computer art shows incorporatingthese interactive displays took place at
the College of the Arts at Ohio State
University in 1970 [47].
A more popular and cost-effective
choice was the storage display tubes
offered by Tektronix, starting around$10,000. But even if only a single line wasto be changed, the picture had to beerased completely and redrawn.
With the exception of the microfilmplotter, all output devices were line orvector oriented and thus characterized
164

Fig. 8. EdvardZajec,Prostor,1968-69.Oneof a seriesof drawingsfromtheProstorprogram.Zajec
wasconcernedwithestablishinga designsystemthatcouldgeneratea multitudeof variations.Each
timetheprogramruns,it definesa rectangleandsubdivides
it accordingto harmonicThe
proportions.
figureformationinsidethis compositiontakesplaceby selectingsuccessivelya line fromthis set:
for lengthandamplitudecomplywith
vertical,horizontal,diagonalandsinusoidal.Theparameters
harmonicratios.Thelinesconnectwitheachotheraccordingto predetermined
rules[37].

the majority of early computer art. The
microfilm plotter is something of a hybrid
between a vector CRT and a raster image
device [48]. The CRT beam scans thescreen sequentially, turning on and off
under computer control. A camera
mounted on the CRT makes a time
exposure during each scan. Thus theresulting image looks like a photographtaken from a raster device.
Some artists used the alphanumericcharacters of the line printer to produce
shaded areas by overstrikingone position
with different characters or using thecapacity of the eye to integrate theseseparate microimages into one larger
macroimage or supersign. The German
artist Klaus Basset attained extraordinarily subtle shading effects by using asimple typewriter. His work clearly
relates to computer art, even if he did not
employ a computer directly to control thewriting process. He programmedhimself,
so to speak, to execute precisely designed

Dietrich, Visual Intelligencealgorithms with a mechanical drawing
device [49].
Output was often taken directly fromthe machine and exhibited. Moreover, thesignatures were sometimes plotted by themachine as part of the drawing program.
Later, artists used these graphics as
sketches for manually produced paintingsor copy for photographically transferredserigraphs.Artists also followed traditionand signed their computer-generated
work by hand. Color was often introduced
only in this later phase ofpostproduction,
or a limited range could be achieved byusing different plotter pens.
Harold Cohen realized this limitationof the available graphics equipment. His
approach was to delegate only the job ofdrawing to the computer, for which heused a plotter, a CRT, or the funnylooking 'turtle'-a remotely controlled
drawing vehicle. He colored the resulting
line drawings later by hand, thus mixing
automatic drawing and human paintingdimensionalicons. In addition,he introducesrotations and other transformationsof the cube to foster visual ambiguityand instability.The dynamicsof thiscombinations.

styles. He recently published a series of
his computer-generated line drawings in
The First Artificial Intelligence Coloring
Book as an invitation to everyone tocombine their creative efforts with thoseof the computer [50].
of e-nterina
were
Methods ofwere
Me-thodsgraphics,
entering graphics
even more restricted. With hardly any
interactive means of controlling thecomputer, artists had to rely on programs
and predefined data. (The technology oflight pens and data tablets had alreadydeveloped, but these input devices were
not widely available.) Once the data was
fed into the computer, there was no morecreative invention. Therefore the design
process took place exclusively in theconceptualization prior to running aleaszt a decade
decadetibefore
beforenrogram. It
Ituuwasat
was at least
program.
Ivan Sutherland's interactive concepts,
demonstrated in 1963 with "Sketchpad"[51], resulted in a breakthrough and theultimate proliferation of paint systems
that enabled the artist to draw directly

Dietrich, Visual Intelligence

into the computer's memory. Today
paint systems, sophisticated3-D modelingsoftware, and video input provide quick
ways to create complex images, but thefirst generation of computer artists had tofocus on logic and mathematics-in
rathe-r abstract
abs%tractmethods.
methods. To
To somesomeshorrt, rather
short,
about
this
restriction
brought
degreecreative concepts derived directly fromcomputer technology itself.

165

VII. THE CONCEPTS
The pioneers of computer art were
driven by the newness of the technology,
the untouched areas wide open for
inventive investigation. Because of thelack of viable commercial applications atthat time, they enjoyed the rare freedom
to define their own goals, guided only by
personal motivation and intuition. This
small group of believers had a vision,
which has not yet been fulfilled. These
artists felt challenged to come up withsophisticated artistic and intellectual
concepts to offset the crude computer
graphics machines of the mid-1960s with
their lack of color, speed and interactivity.
It might be fruitful to resolve with today's
technology the paradox Manfred Mohrfound in his work, a paradox particularly
applicable to the early days of computer
art: "The paradox of my generative workis that formwise it is minimalist andcontentwise it is maximalist" [52].

VIII. COMBINATORICS
The computer was thought of by Nakeas a "Universal Picture Generator"
capable of creating every possible pictureout of a combination of available pictureelements and colors [30]. Obviously, asystematic application of the mathematics
of combinatorics would lead to aninconceivable number of pictures, both
good and bad, and would require an
infinite production time in human terms,
even if exactly computable. This raised
the issue of preselecting a few elementsthat could be explored exhaustively andpresented in a series or cluster ofsubimages as one piece. Manfred Mohr,for instance, centered his work on the
cube and concisely devised successive
transformationsthat modified an ordinary
cube. The complex set of possible
transformations was then plotted, andthe transformations were displayed
simultaneously as a single image. A seriesof catalogs of his work from 1973 topresent exquisitely documents the consistent progression of his visual logic [52].
IX. ORDER, CHAOS, AND
RANDOMNESS
Other artists chose to investigate thefull range between order and chaos,
employing random number generators.
In this way they could create manydifferent images from one program,
introducing change with the random
selection of certain parameters to define,for instance, location, type or size of agraphic element [8, 29]. Random numbers served to break the predictability of166..........':',
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Fig. 10. Colette and Charles Bangert, Landlines, 1970. This couple has been collaborating on their
computer art for almost two decades. In parallel Colette has continuedto draw her art by hand.The
investigation of similarities and differencesbetween 'handwork' and computerplots is the foundationof their creative concepts, and findings are fed back into new programsand more sophisticated handdrawings. This methodological approach is tightly coupled with the subject matter of all their work:landscapes. Colette reports: "The elements of both the computerwork and my hand work are often
repetitive,like leaves, trees, grass and other landscapeelements are. There is sameness andsimilarity,

yet everythingis changing"[59].

the computer. They simulated intuition ina very limited fashion and helped
overcome the severe restrictions ofhuman interaction with the computer.
Random numbers could be constrained
within a limited numeric range and thenapplied to a set of rules of aesthetic
relationships. If these rules were derived
from an analysis of traditional paintings,
the program could simulate a number ofsimilar designs, according to Noll [53]and Nake [30]. Or the artist could set up
new rules for generating entire families of
new aesthetic configurations, using random numbers to decide where and how toplace graphic elements.
Peter Struycken recoveredthe rigoroustradition of the art movement de Stijl andconsciously disregarded even abstract
forms by focusing exclusively on purecolor. In his own words: "Form is aneasier conceptual representation andrepetition than color. Form can almost
always be associated with a form that isalready known. How easy it is to connect
abstract forms to reality:this is just like a
cloud, that like a snake, these like flowers.
Form is then regarded as something in
itself, where recognition is as importantas seeing as such" [8]. To discourage eventhe faintest notion of content, he reduced
the image in "Plons" (Dutch for Splash)to simple squares forming a coordinate
system. The computer calculated propagation of color energy emanating from an

Dietrich, Visual Intelligencearbitrary point of initial impact. Thechanges of color distribution were
presented in numerical codes, which theartist translated into actual color paintings by hand.
X. MATHEMATIC FUNCTIONS
Numeric evaluations of functions
could be plotted directly. Graphs ofdifferent functions could be merged, or
their points could be connected. Thesemethods relate directly to experimentswith analog computing machines by Ben
F. Laposky and Herbert W. Franke in the
1950s. They constructed their own
imaging systems based on an arrangement of voltage-controlled oscillators.
The voltages deflected the beam ofoscilloscopes to produce electronic line
drawings. Laposky called his images
accordingly 'oscillons'. They were photographic time exposures of the CRT
display [54].
Entire number fields were drawn withdigital computers, which features acontrol superior to that of analog
systems. For instance, artist/scientists
would display modular relationships orparticularpropertiessuch as primeness orvarious stages of a matrix multiplication
approaching its limiting boundaries. The
use of mathematics does not necessarily
imply a highly geometrical result. Some
scientists tried to model irregular pat-terns. Knowlton, for example, simulated
crystal growth, and Manfred R. Schroeder visualized equations describing noisein phone lines. Both experiments relate to
the mathematics of fractals so prevalent
today for the modeling of natural
phenomena [55].

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XI. REPRESENTATIONALIMAGES
Whereas the last type of image
visualizes the mathematical behavior of
numbers, the numbers could also represent the coordinates of a hand drawing.
This data had to be meticulously enteredinto the computer via punch cards; thenvarious processing methods could beapplied to the image data. Leslie Mezei
deformed the image progressively into
complete noise [56]. Charles Csuri andJames Shaffer applied Fourier transforms to a subset of the data samples andgenerated complex sine functions
through those fixed points. The originallydigitized drawing, combined with several
sine waves, formed the final image of the"Sine Wave Man".
The Japanese Computer Graphics
Technique Group experimented with themetamorphosis of one image into acompletely different one. Thus a realistic
face could be completely distorted or
gradually transformed into a geometric
entity such as a square. The interpolation
techniques they were using for thecreation of a simple image became thecornerstone of animation. This animation technique, called key-frame animation, was pioneered at the National Film
Board of Canada by Burtnyk andMarcelli Wein [57]. Peter Foldes usedinterpolation techniques successfully as

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Fig. 11. KlausBasset,Kubus,1974.Thetypewriter
graphicsarecomposedof onlyfivesigns:'I','O',
thesetypesymbolsinvariouscombinations,
Bassetachieveda rangeof'o', 'H'and'%'.Byoverstriking
halftonesfrombrightto dark.He usedthesetonesto shadecubicobjects,whichhe calculatedandwitha lineprinteras anoutput
meticulously
typedbyhand.Recently,Bassetstartedto usea computerdevice.He claimsthatthe typewrittenpiecesare moreprecise.

the major stylistic method in his movie
Hunger.
Optical scanners automated the task ofentering visual data into the computerand in effect revealed the potential ofmachine vision. These images were stored
in the computer in the form of different
numbers to encode different gray values,
and later color. They could be printed
with plotters, using a printing concept
similar to that used for halftones, where

dots of different sizes and densities are
employed. The artist could relate the grayvalues of an image to a set of arbitrary
visual symbols and print out theconverted images. Thus images werecreated like the nude by Knowlton andHarmon, which on closer inspection isseen to consist of numerous electricalsymbols, or an eye whose close-up reveals
letters forming the sentence "One picture
is worth a thousand words" (Schroeder).

Fig. 12. Sonia Landy Sheridan, Scientist's Hand at 3M, 1976. This
educational masterpiece implicitly pays homage to the major utensil ofthe punchcard.The imageof the handhas been
early programming:

transferredonto the top line of a stack of punchcards by an electrostatic
process using a prototypeof 3M'S VQC photocopier.Sheridanwas trying

to showthe childrenof the scientistsat 3M'scentralresearchlabsin St
on cardsandhow
Paul,Minnesota,howthecomputerstoresinformation
withoutevenusinga machine.
theimageon thecardscan be manipulated
Thishandcan be stretchedmillionsof waysby merelyshiftingthecards[42, 43].

Fig. 13. Duane Palyka, PaintingSdf-Portrait,1975. (Photo:Mike
Milochek). The artist painted a self-portrait on a computer at the
University of Utah ComputerScience Departmentin 1975. In the picture,
Palyka is using a simple paint programcalled Crayon, writtenin Fortranby Jim Blinn. The programran underthe DOS operatingsystemon a DEC
PDP-11/45 using the first Evans & Sutherland frame buffer.

Dietrich, Visual Intelligence

167

XII. THE END OF AN ERA
The end of the first decade of computerart coincided with important changes due
mainly to three technological advances:
1.

2.

3.

The

inventionofthemicro-

processor changed the size, price,
and accessibility of computers
The
dramatically.
computer
could become a truly personal
tool.
Interactive
becamesystems
common in the creative process.
Traditional paradigms of artistic
creation such as painting anddrawing, photographing and videotaping could be simulated on
the computer.
Raster graphics displays increased the complexity of imagery
significantly. Bit-mapped image
memories allowed virtually unlimited choice of color and thus
thecreationofsupported
shaded or textured
smoothly
three-dimensional images.

These three advances combined tofoster the migration of computer technology into art schools and artists'studios as well as commercial production
houses. The intimate collaboration between artists and scientists was no longer
required. Supported by the emergence ofuser-friendly general-purpose and highlevel graphics language, artists became
computer literate, or they bought software off shelves stocked by a burgeoning
computer graphics industry.
Acknowledgements-The following artists andscientists provided valuable information andvisuals for this article. Thank you very much
Colette and Charles Bangert, Klaus Basset,
Jack Burnham, Harold Cohen, Charles A.
Csuri, Herbert W. Franke, Kenneth C.
Knowlton, Ben F. Laposky, Tony Longson,
Robert Mallary, Aaron Marcus, Manfred
Mohr, Vera Molnar, Zsuzsa Molnar, Frieder
Nake, Georg Nees, A. Michael Noll, Duane
Palyka, Manfred R. Schroeder, Lillian
Schwartz, Sonia Landy Sheridan, Peter
Struycken and Edvard Zajec.

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Call

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Papers

Art and ArtificialIntelligence

The editors of Leonardo invite artists and others to submit articles on work involving art
and artificial intelligence for publication consideration.
Artists whose work involves ideas, techniques or technologies of artificial intelligence,expert systems, interactive programs are invited to submit articles under 2500 words ontheir work. Computer and video engineers, computer scientists, philosophers and otherresearchers are also invited to submit articles on aspects of their work that may be ofinterest to artists.
Editorial guidelines may be found on the outside back cover of the journal. Additional
information may be obtained from the main editorial office: Leonardo, 2112 Berkeley
Way, Berkeley, CA 94704, U.S.A.
Articles that have appeared in Leonardo in this theme area include the following:-MyronKrueger, "VIDEOPLACE: A Report from the Artificial Reality
Laboratory", 18, 145 (1985).
-Susan E. Metros, "Electronic Thinking Cap: Microcomputer-Enhanced Creative
Problem Solving", 18, 100 (1985).
-William I. McLaughlin, "Human Intelligence in the Age of the Intelligent
Machine", 17, 277 (1984).
-Stephen Wilson, "Computer Art: Artificial Intelligence and the Arts", 16, 15 (1983).
-Peter Kugel, "Artificial Intelligence and Visual Art", 14, 136 (1981).
-Michael J. Apter, "Can Computers Be Programmed to Appreciate Art?", 9, 17(1977).
-Michael Thompson, "Intelligent Computers and Visual Artists", 7, 227 (1974).

Dietrich, Visual Intelligence169