Mario Klingemann

Mario Klingemann is a code artist and a skeptic with a curious mind. His interests are manifold and in constant evolution, involving glitch art, data visualization or robotic installations. If there is one common denominator it's his desire to understand, question and subvert the inner workings of systems of any kind.

Since he taught himself programming 30 years ago he has been trying to create algorithms that are able to surprise and to show almost autonomous creative behaviour. The recent advancements in artificial intelligence, deep learning and data anaysis make him confident that in the near future "machine artists" will be able to create more interesting work than humans.

At the moment he is helping institutions like the British Library or the New York Public Library with the processing and classification of their vast digital archives since he believes that his future creative agents will require a solid foundation of human knowledge to build upon.

He lives in Munich, Germany where he also runs a little gallery space called the Dog & Pony. He has been speaking on conferences around the world for more than 10 years, his works have been shown at the Centre Pompidou Paris, the British Library London and the Museum of Modern Art New York.



Session: The Order of Things

"Ordnung muss sein" or "There must be order" is a much hated sentence German kids must hear often whilst growing up. Which is why many have a rather negative connotation when hearing that word - at least "order" is typically considered to be a pretty boring topic.

Over the past years I've become more and more fascinated with order in its many facets and tried to approach it from a programmer's and an artist's view. As I learned, order is at the core of everything that's interesting to humans and beauty lies at the sweet spots between order and chaos.

In this session I will talk about order in its many forms, give some insights how it can be achieved and measured and show examples how it can be put to good use, be it in art, data analysis or machine learning.