THE ZIZI PROJECT by Jake Elwes
Image credit: Jake Elwes.
The Zizi Project by Jake Elwes
The Zizi Project (2019 - ongoing) is a collection of works by Jake Elwes which explores the intersection of artificial intelligence (A.I.) and drag performance, and performance and human identity in the new real. 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. Zizi empowers the drag and LGBTQ+ community by a positive application of deepfake technology, exploring what AI can teach us about drag, and what drag can teach us about A.I.
Zizi is the focus of a partnership between Jake and The New Real as part of the Experiential AI research theme at Edinburgh Futures Institute and Edinburgh College of Art. The Zizi Show is a joyful and vivacious cabaret show fuelled by AI commissioned by The New Real for the first AI Art programme of Edinburgh International Festival (2021).
We asked...
How can AI fuel astonishing works, products and services for audiences during lockdown, that also debunk common misrepresentations of AI?
The outcome:
Edinburgh International Festival’s first AI Art programme, building their digital audience; and works toured globally. The drag and LGBTQ+ community empowered by a positive application of deepfake technology.
Zizi - Queering the Dataset (2019)
‘Zizi - Queering the Dataset’ aims to tackle the lack of representation and diversity in the training datasets often used by facial recognition systems. The video was made by disrupting these systems* and re-training them with the addition of 1000 images of drag and gender fluid faces found online. This causes the weights inside the neural network to shift away from the normative identities it was originally trained on and into a space of queerness
Visit this work on the artist’s website
The Zizi - Queering the Dataset, was commissioned by The New Real as part of ‘Preternatural’ which was presented at Inspace City Screen, as part of Data Play by Design Informatics and the Edinburgh Festival Fringe 2019.
The Zizi Show 2020
Drag Queens, Drag Kings, Drag Things and Artificial Intelligence...
The Zizi Show (2020) is a deepfake drag cabaret, a virtual online stage hosting a groundbreaking new show with a twist. It features acts that have been constructed using deepfake technology, learning how to do drag by watching a diverse group of human performers.
Visit this work on the artist’s website
The Zizi Show was commissioned and produced by The New Real and presented at Edinburgh Futures Institute as a part of the Edinburgh International Festival.
Zizi & Me (2020-Ongoing)
‘Zizi & Me’ is a double act between drag queen 'Me The Drag Queen', and a deepfake (A.I.) clone of 'Me The Drag Queen'. By training a neural network* on filmed footage this network learnt to construct a virtual body that can be controlled by feeding it new reference movements. The first act 'Anything You Can Do (I Can Do Better)’ satirizes the idea that an AI is something that we might mistake for a human. Through drag performance, we aim to use cabaret and musical theatre to challenge narratives surrounding A.I. and society.
Visit this work on the artist’s website
Art as explanation
Zizi exposes the latent space of a machine learning model, and highlights the way the model outputs are shaped by the training data. Where many generative works have been trained on opportunistically collected data, the purposeful curation of Zizi’s dataset explores the question of how human identity is represented within complex models. The Zizi Show develops this through digital avatars, that have been learned from real performers to create an interactive work that allows user control. Significantly, it connects low level technology to high level, social, cultural and political aspects of AI, such as ideas of cultural appropriation and machine bodies. It exposes the limits to machine intelligence, and inverts what is otherwise a deficiency in the technology, through a positive use of deep fake technology, in which a marginal identity is celebrated and embellished, rather than obscured or misrepresented.
Zizi is an explanation of bias in ML and the power of the dataset through experiential means. Zizi highlights the way data and design choices shape what ML does. It shows how the model learns a representation of people, that is embedded social life. Zizi engaged a marginalised group, developing their literacy surrounding bias in ML, thereby supporting their agency in contesting its fairness and accountability. Zizi shows end users there is something to contest, even if that do not interact directly with the model themselves. Zizi specifically targets anthropomorphised misrepresentation of AI, by constructing an AI persona, and then deconstructing it, and exposing its construction in software by the human artist.
The Creative Process and Collaboration Journey
A clash of Jake Elwes two worlds, Machine Learning and the celebration of Queernes, the Zizi project was born out of a providential moment of serendipity that got Drew Hemment and Jake together at ZKM in 2018.
Soon after Drew, as commisioner for Edinburgh Futures Institute and its Experiential AI research group, commisioned Jake to develop their project which resulted in the first iteration of Zizi, "Queering the Dataset" was projected at InSpace CityScreen during the 2019 Edinburgh Fringe Festival.
The ongoing collaboration and the audience's desire for seeing Zizi dance created a new opportunity to develop the project. With the addition of Me The Drag Queen to the artistic team as performer and director of Drag, Jake explored deepfake technology and motion capture to give Zizi a body.
Originally thought as a live act starring 'Zizi & Me' navigated the pandemic by shifting towards an online show 'The Zizi Show', showcasing the resilience that digital technologies can provide the culture sector with. This shift saw the cast expand from Me to 13 Drag performers, supporting them through the stop of life shows and stablishing a unique and empowering relationship between data subjects and their digital counterparts.
With the return of life shows Jake, Zizi & Me continue exploring deepfake as a performative and artistic tool in Zizi & Me
Credits / Collaborators
Jake Elwes - Artist, Coder & Producer
Me - Director of Drag
Alexander Hill - Web & Development
Toby Elwes - Camera & Lighting
Charlie Baker - Sound Mixing
The Apple Tree - Filming Location (LGBTQ+ Cabaret Venue)
In Collaboration with Edinburgh Futures Institute
Drew Hemment - Project Director & Curator
Suzy Glass & Janet Archer - Producers
Sarah Bennett - Researcher
