Mattis Kuhn

Schwarz/Weiß portrait of Mattis Kuhn
Year of birth, place
1987, Marburg, Germany
lives and works in
Frankfurt a. M. und Köln, Germany

Mattis Kuhn studied art at the HfG Offenbach am Main and the Royal Academy of Fine Arts (KASK) in Gent, Belgium. He is currently studying »Experimental Computer Science« at the KHM Cologne.

Mattis Kuhn's practical and theoretical work deals with humans – as individuals and societies – in connection with non-human actors and the common ecosystem. The central themes of his research are identity, collective, decentralization, human-machine associations, networks, and artificial intelligence.

Together with Franziska Nori, Mattis Kuhn curated the exhibition »I am here to learn: On Machinic Interpretations of the World« at the Frankfurter Kunstverein.

Exhibitions as an artist

2019 »EMAF Experience, European Media Art Festival«, Osnabrück
2019 »Open Codes. The Art of Coding«, ZKM, Karlsruhe/ Goethe-Institut, Mumbai, India
2018 »Open Codes. The world as a data field«, ZKM, Karlsruhe
2017 »PIKSEL17 – festival for electronic art and technology«, Bergen, Norway
2017 »F°LAB – Festival for Performing Arts«, Frankfurt LAB
2017 »SMALL #2« , Art Space SUPER, Vienna
2016 »On Stage«, Marburg Art Association
2014 »Eight Bridges – Music for Cologne«, Cologne
2013 »TiL / City Theatre«, Giessen
2012 »LAB« Frankfurt

I am here to learn: On Machine Interpretations of the World
– A Lecture at the Open Conference »Art and Artificial Intelligence«

Perception and interpretation are two important human qualities, especially in the field of art. Now they are transferred to machines. Machines not only register their environment passively, but also actively interpret and change it. With the exhibition »I am here to learn« we addressed several aspects of perception and interpretation of the world through machines.

How does the perception of machines differ from that of humans? Physical, personal and cultural experiences define human interpretations, making them subjective. Machines sense different things indifferently. But their interpretations aren’t objective as well. They are shaped by human intentions and assumptions. Neural nets generalize data, very special features are ignored. On the other hand machine interpretations can generate data that did not exist before. Computations, even if they contain speculative content, become reality.

What notion of the world is stored or generated inside a machine? How to deal with machines, which act like persons and communicate values, but have no understanding of their actions? How do intelligent machines around us change our perception and interpretations and who decides, when human and machine interpretations diverge?