Hear the artist talk about this exhibition
Jake Elwes (UK)
Image: Jake Elwes, Zizi - Queering the Dataset, 2019. Courtesy the artist.
Playing at the intersection of AI and drag.
The Zizi Project is an ongoing collection of works exploring the intersection of Artificial Intelligence (A.I.) and drag performance.
Drag challenges gender and explores otherness, while AI, often mystified as a concept and tool, is complicit in reproducing social bias. Zizi combines these themes through a deepfake, synthesised drag identity created using machine learning. The project explores what AI can teach us about drag, and what drag can teach us about AI.
Searching for poetry and narrative in the success and failures of AI systems, Jake Elwes’ practice makes use of the sophistication of machine learning, while finding illuminating qualities in its limitations. Elwes seeks to queer datasets, demystifying and subverting predominantly cisgender and straight AI systems.
A Queer PHOTO exhibition curated by Brendan McCleary Presented by Midsumma and PHOTO Australia Supported by Creative Victoria through the Victorian Government’s Go West Fund