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 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. 

Zizi - Queering The Dataset lets us peek inside the machine learning system and visualise what the neural network has (and hasn’t) learnt. The work is a celebration of difference and ambiguity, which invites us to reflect on bias in our data driven society.
*A Style-Based Generator Architecture for Generative Adversarial Networks (2019)

Instagram @zizidrag - machine learning generated captions and looks trained on drag profiles.
Zizi was originally commissioned as a seven channel video installation by Experiential AI at Edinburgh Futures Institute and Inspace.
Presented as site specific video installation with between 3 and 7 projected video channels.

Exhibitions

PRETERNATURAL: Jake Elwes Solo show, Data Lates | Inspace Gallery, Edinburgh 2019
Real-Time Contraints (virtual browser extension, COVID-19), Arebyte Gallery, London, UK, 2019
Fluid Bodies, E-WERK Freiburg, Germany, 2019
You and AI (touring), Onassis Foundation and Future Everything, Gazometro Rome, Italy, 2020
Critical Borders: Radical (Re)visiions of AI, Center for the Future of Intelligence, Cambridge University, UK, 2020
You and AI, Onassis Foundation, Pedion tou Areos Park, Athens, Greece, 2020
The Third Gender, A.K.T, Pforzheim, Germany, 2020
Among the Machines, Zabludowicz Collection, London, 2021
BIAS, Science Gallery Dublin, Dublin, Ireland, 2021
Jake Elwes: Data • Glitch • Utopia (solo show), Gazelli Art House, London, UK, 2022
Riposte - Queer Art Techno Rave, Electrowerkz, London, 2022
UKINTER:ACTIVE - Breaking The Code CPH:DOX, Kunsthal Charlottenborg, Copenhagen, Denmark 2022
The Horror Show! A Twisted Tale Of Modern Britain, Somerset House, London, 2022 - 23
Glitch. Die Kunst Der Störung, Pinakothek der Moderne, Munich, Germany, 2023
Zizi - Queering the Dataset (solo display), Gazelli Art House, Mayfair, London, 2023
Surreal Futures, Max Ernst Museum, Brühl, Germany.2024

Jake Elwes (b.1993) is an artist living in London currently working to queer artificial intelligence with drag performers. Across projects that encompass moving-image installation, sound and performance, Elwes’ work finds unusual ways of demystifying, mapping and subverting technology. Their work searches for poetry and narrative in the successes and failures of digital systems. Works include deepfake drag in The Zizi Project (2019 – ongoing), glitching oppressive algorithms in Machine Learning Porn (2016) and reframing AI generated marsh birds back into nature in CUSP (2019). They have been making art exploring the aesthetics and ethics of machine learning systems since the very first generative AI models in 2016. Elwes’ work also calls for us to challenge who builds these systems and for what purpose, and whether we as artists and queers can reclaim these technologies to build our own digital utopias.

Elwes studied at The Slade School of Fine Art, UCL (2013-17) and their work has been exhibited in museums and galleries internationally, including the Victoria and Albert Museum, London; Pinakothek der Moderne, Munich; Somerset House, London; ZKM, Karlsruhe; Today Art Museum, Beijing; Frankfurter Kunstverein; Fotomuseum Winterthur, Switzerland; Honor Fraser Gallery, LA; Fundacion Telefonica Museum, Madrid; Ars Electronica, Austria; Zabludowicz Collection, London; Sculpture in the City, London; Science Gallery Dublin; RMIT Gallery, Melbourne; Onassis Foundation, Athens; E-WERK Freiburg, Germany; Museum für Naturkunde, Berlin; Nature Morte, Delhi; Centre for the Future of Intelligence, Cambridge and they have been featured on ZDF aspekte, ARD ttt (DE), BBC Radio 4 Front Row, and BBC1’s Kill Your TV - History of Video Art (UK).