How databases can be turned into Art: Geert Mul at TEDxTilburgUniversity

How databases can be turned into Art: Geert Mul at TEDxTilburgUniversity

Translator: Agata Szczytnicka
Reviewer: Denise RQ We are alienated animals.
What does it mean? Animals don’t wonder who they are,
they don’t wonder why they are here, but that’s exactly what we do, and that’s exactly
what this institute is about. So we do that all the time, and we also have
a tradition in expressing that: writing reports, making art,
and writing books. Who are we and why are we here? In the course of history,
we had different explanations, and by designing these explanations,
we also designed the world. So we used to think
that there was one man in the sky, and he pretty well organized everything. We kept on wondering
how things were fitted together, and we looked at nature for clues. The funny thing is, if we look out,
and we give an explanation, that’s how we build our world. There was a time when we think
that logic could explain everything, that we could calculate the Universe,
that we could calculate the future if we would just use the right logic,
if we would just do the right math. There was a time
when we built the world by ideology. And now we are here. Today we are creating
our world by information. We have arrived in the Library of Babel, the Library of Babel
which has been so well described in a story by Jorge Luis Borges,
an Argentine writer, already in 1941. What is the Library of Babel? The Library of Babel is a library
as large as the universe; is endless. There are books in the Library. The books contain
all the possible combinations of the letters of the alphabet,
the comma, and the dot. All the books are there.
All knowledge is there. Your biography, my biography,
the denial of my biography, the critique on the denial
of my biography; everything is there. We have arrived there. All the knowledge, as our former
speaker said, is at our fingertips. So, we have a problem because if you take a book
from that library, probably it is all nonsense; it’s random. There are only few books,
with few sentences that make sense. How do we find the right books? How do we find truth? How do we find knowledge
in this universe of information? I know this problem. In my studio I have a computer
with a database of 2 million images. Of course I don’t really have an idea
how to navigate in this database; I do not have a concept
of the identity of 2 million images, how can I? So how do I find out what is there? How do I find out
what does this database contain? Because they are collected randomly. For example, I wonder if there could be an image
of a tennis player so then I could use another computer and design a very clever system to teach this computer
what a tennis player looks like in all [possible] positions and conditions like we heard before in the cat story. Then I could run that algorithm
against the database. And it does not find a tennis player. So there is no tennis player
in my collection of 2 million images. Maybe there is a cup of soup? So then I go back to the other computer, I design an algorithm
that finds cups of soup, etc., etc. It’s pointless, it doesn’t work. So, what do we do? We, as a culture, took another turn and instead of looking for
content and meaning, we started to look for patterns, interrelations. self-referential order. This is what my database looks like
with this technology when I look for patterns; it’s called data-mining. And it’s called pattern recognition. It’s called knowledge engineering. Actually, knowledge engineering
is what this culture, contemporary culture, is built on; it’s our daily life, our beliefs,
and our economic system, and even our healthcare,
or part of the healthcare — computer IT diagnosis. This is not a computer
that looks for a specific problem, is a computer that recognizes patterns and comes out with patterns
that might be potential problems. We used data-mining
in the political world. We data-mine voters so we can write a proper campaign
to reach out to them. We use data-mining in engineering. There used to be a time in engineering when you were looking for a problem
and you were going out to find it for example if a building
was collapsing due to water. Now you stick in sensors everywhere, you collect the data,
you look for patterns, and hey, when the Sun comes up,
the [level] goes down, because the water evaporates. You weren’t looking for it,
but you found it. It’s a finding engine;
it’s not a search engine. In economy,
70% of all stock trade in the U.S. is done by high-frequency
trade machines — autonomically. Those are computers which make decisions and sell and buy thousands
of stocks, based on analysis. They even read the news
in their own format. And here is an example from my database: I was not looking for Van Gogh,
but Van Gogh found me. Van Gogh is a pattern. So what about the arts? Think about this momentum where we live, think about all this information, the libraries, the museums,
all information that we use; we store it in databases. We should be able to read those databases, otherwise, we cannot
generate new knowledge. So what are the qualifications
of a stock trade programmer? “Using applied statistical techniques
to develop quantitative models.” What could be
the qualifications for an artist? “Using applied statistical techniques
to develop models.” Because art loves mistakes. You got him? And art loves probability because mistakes and probability
generate stories, they generate humor,
they generate emotions. So this is what could happen
with Vermeer. This is not a picture by Vermeer, this is what Vermeer is
as a combined image. And now we are able to see it,
to experience it, because it moves. An this is Mr. Breivik — You drop one image on the Internet, and it’s like a virus,
including mutations. It gets to be a person, it gets a life. We shape it, we form him. And this is just a study,
a classic study on portraits. I call this data-based art. This data-based form of art could generate additional information
on existing disciplines. Take, for instance, art history. If you have a museum
with all kinds of landscapes, is logical that you exhibit them
by putting them on the walls. And actually, there is interactivity,
because you go from room to room, and you can experience
all these paintings. But there are other ways
to experience paintings. You put those paintings in a database, and you can explore these paintings – if they are
in a database -, interactively. And what you see here
is a work where all these paintings, when you enter the room, split open, and underneath the horizon
there is another horizon. And you see all these momentums
of art history next to each other. It is not alternative
for classic art history, nor an alternative
for a classic exhibition, it’s an addition,
it’s additional knowledge. Or take this work: I made this for
the Photo Museum in Rotterdam. They had an archive of 150,000 images. Nd they wanted to show
the archive to an audience. But how do you show an archive
of 150,000 images to an audience? So I gave them a couple of filters: where, who, what, and when; very classic journalism. And I put filters on different posts. So the people on the post
can select different filters, they can select different times
and different subjects. It is not a search engine. It is finding engine. They are making impossible
routes to the database, and suddenly, they come into a moment where they find all the clouds in 1953 in Southeast Asia. Or take this work. This is data-based art
on football for FC Valencia. It is a work where you can interactively explore
the identity of a football club; a football club is a formal system. Every football club shares
the same system, but they are all different,
and they are all very specific. Take AFC AJAX –they are not the same,
they are not the same, but where is the tie-in? And can you feel it? You can feel it if you put
its identity in a database and if you use the visitors
to roam it, to experience it. So in this database
I made about 18 different themes of supporters, architecture,
local patterns, local colors, trades where visitors are exploring
the identity of the club in patterns that are related to the patterns of the local,
traditional patterns of the city itself. Another finding engine: as opposed to a search engine. Roaming a database is an experience. This software tries to link
images which are similar and puts them
behind each other, linearly, so they create a real time, live movie. You can play it as an instrument. This is data-based art of memories. This is a work I made for city of Enschede where there was this firework
explosion in the year 2000, when the whole inner city was blown away. I collected images of the people
who used to live there, and I brought back these images
into a room and invited people to roam it. This is the most basic methodology of organizing and reorganizing a database: you take all of images,
throw them in the air, and when they come back,
they have a different order. And a different order tells
different stories. This is what art has been
exploring; all art history. And on the news. In this system, I connected
the computer with satellite television with about 30 international
different channels. And I asked the computer
to look for similar images. And it does it very well. On the top ranking,
the images are actually similar – the only thing
that’s different is the logo – but they are not so interesting. Interesting things happen
when you go down in the bandwidth, when they start to differ. And that’s when people start to laugh
or they are shocked, and things are happening. But the funny thing
is nobody ever thought of the joke. it’s a probability joke. This is something
which is underlying our culture. This is a methodology,
called knowledge engineering, and is applied in a lot of sciences. And the arts can learn, actually,
a lot from those sciences. And this is why: [“If art’s intention
is to model possible universes, we need skills to do this, [otherwise, we copy unconsciously
the dominant model around us.” –G.Lovink] Thank you very much. (Applause)

Danny Hutson

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