Imagining the browser as a stage, Joana Chicau. and Jonathan Reus will present a try out for a fully live-coded real-time remote performance within a virtual anatomical theater. Dissecting. Cutting. A hands-on intervention into the process of an unsupervised learning algorithm, K-means, as a body of knowledge is created.
“We research and develop performative techniques for in-situ dissections of machine learning algorithms. To better understand the habitual and fixed objects of machine learning as well as their terminologies, and provide counter-techniques for conditions of emergence and movement.
In our processual approach, we aim to develop an online repository of terminology and techniques for a critical examination of the “anatomy” of learning and prediction processes, data corpus and models of machine learning algorithms. And explore, through performance practice, how such a toolkit can confront the idealized bodies of artificial intelligence.”
This research project began in late 2018, and is produced as a co-production with V2_ Lab for the Unstable Media