fuel us to be more creative.” Being ex-
posed to extremely different influences
can be inspiring, and is often essential
to producing breakthroughs, he adds.
“What better way, save for visiting alien
cultures, is there to experience truly dif-
ferent ways of thinking and artistic ex-
pression than letting AI produce art? I
predict it will unlock vast new cultural
and scientific landscapes for humans to
explore.”
The art produced by networks has
greatly informed our scientific under-
standing of how deep neural networks
see the world, says Clune, and they do
so very differently than humans do.

He references the Turing Test, and how computers must not only produce art, but “produce art at a level of quality and originality such that it is indistinguishable from art produced by a human” to pass the test. Clune decided to test that theory by submitting art the lab’s deep neural networks (DNNs) produced to the University of Wyoming’s 40th Annual Juried Student Exhibition, which accepted 35.5% of the submissions.

Clune and his team developed an
AI “artist” agent and a “critic” or judge
agent. The purpose was for the artist
to try and produce art the critic/judge
would like, he explains. To do that, the
team created an innovation engine
algorithm with the artist and judge
agents inside. The critic was a DNN
trained to recognize 1,000 categories
of images, Clune says, “and it’s the AI
artist’s job to produce images that the
critic agrees count as each type of im-
age,” like a motorcycle.

“We have found that it’s important for artificial intelligence, while it’s learning, to have to constantly switch goals and have many goals,” he explains. That is why they challenged the AI artist to make 1,000 different types of images, instead of just one. The team went through the images the artist agent produced and submitted a handful for the competition they thought appeared to show interesting artistic interpretations of concepts, such as a beacon or a prison cell.

There were no rules forbidding such entries, he notes, “largely because I’m sure the competition organizers didn’t realize it was possible for AI to produce high-quality art. In fact, if the rules for art competitions begin to be rewritten to limit submissions to humans, we will know that AI has become such a great artist that many humans are afraid to

“We have found that
it’s important for
artificial intelligence,
while it’s learning, to
have to constantly
switch goals and
have many goals.”

compete against it.”

The outcome? Not only were the images accepted, but they were also among the 21.3% of submissions to receive an award. The work was then displayed at the university’s art museum. Clune adds that the judges were evaluating all submitted art on its own merits to see which was good enough to be accepted. “I imagine the judges never considered the fact that the art might have been made by AI.”

Music to the Ears

Perry Cook, professor emeritus of com-
puter science at Princeton University, be-
lieves art has been combined with tech-
nology longer than many people realize.
“The march of music has been about
technology. Music has, in some cases,
brought about new technologies, and
certain music has taken advantage of the
technology of the day,” says Cook, who is
also a research coordinator and IP Strat-
egist for SMule, a social network based
on creating and sharing music, and co-
founder and executive vice president of
Kadenze, an online arts and technology
education startup. In a blog post (http://
bit.ly/2feVCyd), Cook cited numerous
artists who have created artwork using
machine learning, which he says opens
up all kinds of new possibilities.
Although a common perception is
that computer music came along late
in the evolution of electronic music, ac-
cording to Cook, people were looking at
using computers to store and analyze
music in the 1950s. “Forward to today,
the computer is just another technol-
ogy, in my opinion. It’s somewhat com-
parable to putting a valve on a bugle so
you could play more notes, [which] al-
lowed music to get louder and softer.”

The arts are an especially good way to introduce people who normally would not have thought they should or would want to learn concepts about computer science, he notes, specifically artists, children, and underrepresented minority groups “who think they’re kind of locked out or aren’t interested and don’t want to be engineers or computer scientists. Getting to them through the arts is a way to open up [computer science] to a whole new community.”

 

Making CS “Culturally Responsive” That is exactly what Gaskins is doing at

Images produced with innovation engines were not only accepted to a selective art competition and displayed at the University of Wyoming Art Museum, but they also were among the 21% of submissions that won an award.