Absurd #1

Uncertainty, indeterminacy, and contingency are parts of AI learning and operation processes. As digital theorist Luciana Parisi (2013; 2017) argues that if AI is rooted on uncertainty, then it must be understood as a non-conscious form of cognition, possessing its own nonhuman way of learning.
An AI system makes sense of the world by producing mathematical abstractions that are alien to human perception. The same is true for AI computer vision systems. Vision is no longer dependent on the human eyes but a method of machine-to-machine communication. We're not dealing with one system but with an overlapping network of abstraction and representation systems that feed their output to one another: Abstractions upon abstractions. When these abstractions are misapplied to each other during these processes, context is lost and destabilization arises.
Absurd is a series of interdisciplinary artworks that aims at exploring misrepresentations within a discordant network of AI systems by violating its parts' assumptions and creating a chain reaction of errors and misinterpretations. Its purpose is to make these misrepresentations temporarily visible to human perception to reflect on the vulnerability of these systems which are controlling all aspects of life with their bits of abstraction.