Associate is a generative and poetic text-based artwork and an experimental documentation of collective discourse. Associate was created for Untitled festival and is algorithmically generated from discussions taking place at Untitled. It is at the same time an independent artwork and experimental documentation of the festival and the online events.
Discussions recorded in Untitled webinars, meetings and festival events were processed through a machine learning algorithm. The algorithm forms new connections between various textual elements based on machine learning models that analyse the context and statistical properties of individual words and phrases.
The machine learning model aims to bring light to emerging and new connections between textual nodes, and reflect on various alternative meanings and paths derived from the language used within Untitled discussions.
The artwork is available at https://associate.associates/ and a spoken word adaptation of selected poems is available at https://vimeo.com/455929776
The artwork was created for Untitled festival and supported by AVEK and will also be the topic of my master’s thesis.
