When German artist Mario Klingemann
started using computers to “augment” his creativity, the worldwide web and
Google did not exist. Over the years, the German artist had to tweak the new
computerized tools he was being offered, writing his own plugins for tools like
Photoshop or After Effects, before 21st century technologies allowed him to
build more complex systems for algorithmic generative art.
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| The Butcher’s Son by Mario Klingemann |
Today, Klingemann who creates artworks
using algorithms, code and neural network, is considered one of the pioneers in
the use of computer learning in the art. The Google Arts and Culture resident
recently won the 2018 Lumen Prize for digital art for The Butcher’s Son, a sitting
nude image that had been entirely generated by a machine using a chain of GANs
(generative adversarial neural) networks. First developed in 2014, GANs are a
class of artificial intelligence algorithms used in unsupervised machine
learning, with two neural networks contesting each other in a zero-sum game
framework.
“These algorithms are called
“adversarial” because there are two sides to them: One generates random images;
the other has been taught, via the input, how to judge these images and deem which
best align with the input,” explains Ahmed Elgammal, director of the Art &
AI lab at Rutgers University.
In the case of The Butcher’s Son, Klingemann
built a system from multiple neural networks that explores the human form. “It
does that by first generating random stick figures after having learned the
possible variations in human posture by analysing hundred thousands of photos.
Each of these figures is then passed to a GAN that has learned to translate
them into a rough sketch that reminds of a painting - interestingly that
painterly look is the result of the model making mistakes and abstractions,
since I did not train this model on painting, but actually on pornographic photos.
In the final step this sketch is given to another GAN which tries to fill in
the missing details and adds interesting textures and artefacts,” Klingemann
explains.
The final winning portrait, with its
disfigured face and blurred flesh color tones, was reminiscent of Francis
Bacon’s artworks, in line with a distinct GANs aesthetic that reflects how the
algorithms process information.
“Visually there are typically surreal
distortions in localized areas which create a very interesting part-whole relation
in the painting: what seems like a typical beach landscape might suddenly in
one region sprout a forest,” explains Karthik Kalyanaraman, one half of the
curatorial collective known as 64/1 which focuses on art for the post-human age
and which curated last year a show entirely dedicated at AI art at Nature Morte,
one of the largest contemporary art galleries in India.
Kalyanaraman believes an art expert can
usually identify work produced by a GAN because of tell-tale textural effects, “a
kind of shimmer or a scrambling of various image-making techniques like
impasto, dry paint, etc,” though artists are now working on overcoming this
‘GAN signature.’
Elgammal, for example, has developed a
system he calls AICAN — a ‘creative’ rather a ‘generative’ network, that is specifically
programmed to produce novelty. The program, which can works on his own, was
essentially created a “creative collaborator and partner” for artists, and some
of these collaborations with Tim Bengel and Devin Gharakhanian were premiered
at the fair SCOPE Miami Beach in December. “We designed AICAN with the intention of
opening up exciting possibilities for artists to explore new territories of
their own creativity and artistic process,” said Ahmed Elgammal.
Before its appearance at SCOPE, AI-generated
art had already been in the spotlight with a controversial sale at Christie’s
New York, which saw an AI artwork smashing its $7,000 to $10,000 pre-sale
estimate to hammer at $432,500. The portrait, titled Edmond Belamy, had been
created by GANs trained by Obvious, a Paris-based collective that signed the
work with the algorithm name instead of their own, which seems to indicate that
the algorithm was the real artist.
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| Anna Ridler |
Who
is the artist?
So are AI machine about to replace
artists? Not so, say art practitioners.
“The narrative that the AI is the
‘artist’ is absurd and that is clear once one starts to understand these
algorithms. Humans conceive the algorithm, teach the algorithm a particular
visual style by curating the ‘training set,’ and uses their aesthetic eye to
curate the final output! In so far as there is not a shred of autonomy or
will in the working of this process, I think it is really premature to call the
AI an artist. Do we think the lens and the camera and ‘nature’ which
provides the setting is the true artist and not the photographer?,” says
Kalyanaraman.
“A GAN by itself is often just an empty
vessel,” concurs Kligemann, adding “as an artist you have to fill it with
content by deciding what to train it on and then finding and curating thousands
of images that you want to extract some essence from.”
“Machines can probably only ever be as
creative as humans, not much more, since if they came up with radically
creative ideas we would not be able to recognize their brilliance since we
would simply not be able to understand it. That is the problem with human
imagination - it can only expand slightly beyond our horizon - new ideas take
time to be accepted and understood,” Klingemann remarks, “But like any other
technology that allows us to do things faster, better or with less effort AI
already seeps into our daily life and will not stop at helping us with our
imagination and creativity. Just like you probably can't imagine a life without
your mobile phone anymore in the future people might not be able to imagine how
people in our times could have had ideas by themselves without the help of
their creative assistant.”
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| Tom White |