DataNatures

Project Module Lecturer: Verena Friedrich Credits: 18 SWS Times: Tuesday 10:00 - 13:00 Venue: DBL & online First meeting: October 21, 10:00 @ DBL

Description:

In the science fiction film Tron (1982), an orange is scanned by a laser beam in order to be transferred into a virtual computer world. At the end of this “Matter Transform Sequence”, the orange has disappeared—its digital image appears on the screen instead. The promise of this fictional technology: the total capture and modeling of the bio-logical world, in order to make it manipulable, controllable, and available at will on a data-logical level.

Some four decades later, the methods and scope of data collection, processing, and storage have developed at a rapid pace. Increasingly large parts of the world and of our everyday lives are being digitized and incorporated into technical infrastructures, to the point that one can speak of a “datafication of everything.” Yet have we really come closer to the techno-utopia of the world’s complete capture?

Does not the sheer abundance of data itself show that certain aspects of the world and of “nature” always remain fleeting—immeasurable, unavailable, and resistant to any form of technical appropriation? Or is this, after all, merely a romantic notion that can no longer stand up to the effectiveness of Big Tech? How do we, as human beings and as artists, engage with the current situation? Can artistic practices open up alternatives to a purely technocratic handling of data?

The seminar investigates these questions from artistic, technical, practical, and theoretical perspectives. Following a general introduction to the topic, we will discuss artistic works and read selected texts in order to critically engage with the increasing quantification and datafication of the world. In practical workshops, we will do statistics with pen and paper and explore basic methods of collecting, ordering, counting, and classifying biological samples. From there, we will trace the path toward today’s computer-based (classification) procedures grounded in machine learning and data-driven research in science. Hovering above all of this is the question of the relationship between materiality and digitality: what continuities persist, and what ruptures emerge?

The aim is to develop independent project ideas and realizations that engage artistically and experimentally with specific aspects of the theme DataNatures.