An Interview with Xuan Ye
In 2018, InterAccess welcomed its first Digital Artist in Residence, Xuan Ye. For this residency, the artist developed EveryLetterCyborg V1.3, a web-based artwork that accepts input text and translates it using an algorithm that sources language from Donna Haraway's Cyborg Manifesto. Ye invited users to participate in the project by inputting text, which she would then map in webVR. The work was featured in a one-night public presentation in InterAccess's gallery on December 13th, 2018.
The following is an interview with Xuan Ye in advance of this public presentation.
Can you describe the algorithm you created for this project? What does it do?
XY: EveryLetterCyborg is a project with three versions, each developed in the same uncreative writing method that is borrowed from an arbitrary deterministic technique called “diastic” or “spelling-thru.”
In 1963, Jackson Mac Low coined the word "diastic" from the Greek words dia (through) and stichos (a line of writing) to introduce a procedure for non-intentional poetic writing in which the writer reads through a source text, incorporating words from it into the poem such that “the first linguistic unit in the poem begins with the first letter of the first word of the title or other seed, the second unit has the second letter of the first word of the seed in its second place, and so forth” (Mac Low). The resulting text is made entirely out of words from the source text without following standard English syntax.
What is the importance of Donna Haraway’s Cyborg Manifesto to this project, or your creative interests more generally?
What can people expect to see at the project’s public presentation at InterAccess?
Are there other projects or subjects you’re exploring that you’d like to mention? How can our members follow along with them?
XY: I’ve recently created a series of works titled Erroar!, commissioned by Beijing Inside-Out Art Museum, that speaks to the errant and noise that emerge from experiments of artificial intelligence and machine learning. Three works are interlaced into the installation of Erroar!, consisting of a ChatBot, a wall installation and a three-channel video. The multimedia trilogy involves results generated from the process in which I used open data in various formats (text, image and sound) to train prevalent deep learning algorithms such as RNN and CNN. More can be found on http://a.pureapparat.us & @apureapparatus.
View the documentation of the public presentation here.