A silent video series consisting of life-size deepfakes of a range of London drag performers. How can we as a queer community subvert deepfake technology, using it in an ethical and consensual way to celebrate queer bodies? Everyone involved in the project has power over their own data and involvement as well as all being part of the same community. In this piece forms are re-animated by drag legend Wet Mess whose improvised movement causes the AI to beautifully break down and fail, imagining an alternate queer utopia for AI.

The Zizi Project (2019 - ongoing) is a collection of works by Jake Elwes exploring the intersection of Artificial Intelligence (A.I.) and drag performance. Drag challenges gender and explores otherness, while A.I. is often mystified as a concept and tool, and 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 A.I.