Chris Woebken
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Deep Unlearning (I), 2018
In collaboration with Sascha Pohflepp

In the presence of learning machines, human knowledge of the Western kind has become one among many. Non-human creativity emerging from many substrates and its application in time are likely to produce realities so complex and alien that we may never fully understand them.

Here, games play an important role, not only as benchmarks for intelligence, but also as a common platform on which those synthetic minds can be directly encountered. In response to this, we propose a process of deep unlearning, a playful self-alienation in order to gain a tiny measure of access to the ways of knowledge of the not-us.

For the first stage of this project we have designed a card game which by self-randomization through shuffling allows for the creation of almost 3 billion possible algorithmic instructions, not unlike the instruction pieces of the Fluxus era. A certain measure of nonsensicality is expected, as it is at precisely this boundary where unlearning takes place and irrational meaning may emerge.

Project website:

Curated by Nora O Murch, Thanks to our workshop participants and friends who sent us inspiring algorithms: Burak Arikan, Sankalp Bhatnagar, Lars Buesing, Taeyoon Choi, Alexis Convento, Sam Hart, Melanie Hoff, Pam Liou, Geoff Manaugh, Mike Mozer, Yuka Murakami, Philipp Schmitt, Karolina Sobecka, Julie Solovyeva, Phil Stearns