Come To The Deepfake Cabaret Where AI Is No Drag

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Zizi, an installation commissioned by the Edinburgh International Festival and the Edinburgh Futures Institute, is a drag act with an uncanny twist. The show I'm watching on my computer screen features a performer lip-syncing and dancing as they might at any drag or cabaret event. But that performer is actually a deepfake -- one of 13 drag artists (and sometimes a combination of them all at once) who are in fact all real people from London's drag community.

I get to choose the song and the performer, although throughout the act I can cycle between them -- there's Me with her pink beehive and oversized lashes, then Oedopussi Rex with his braided, multicolored beard and Lily Snatchdragon with her magenta shoulder pads and purple bangs. No matter which performer I'm watching, their movements remain the same -- the bodies and faces a messy mash-up of projections anchored onto the underlying deepfake skeleton.

Zizi puts a creative spin on deepfakes and challenges the narrative they're all poised to ruin us. The technology, which easily and convincingly swaps in faces in videos, calls to mind malicious clips in which famous or important people are made to appear to say things they never really said or get inserted into graphic pornography. At their most benign, their uncanniness can leave us confused or elicit a chuckle. At their most harmful, they've been . 

Pick your fighter.

Jake Elwes/The Zizi Show

But while watching the Zizi Show, we're asked to reconsider how we understand them altogether.
Queering the dataset and the internet
There is something inherently fun, playful and tongue-in-cheek about drag that invites people to ask questions about established gender norms and can also encourage them to ask questions about technology, said artist Jake Elwes, the creator of the Zizi Show.

Elwes trained at Slade in London, a "hardcore traditional art school," and from a young age started to teach himself creative software, animation and coding. He's been working with AI for many years now, but until he introduced performers, it was resulting in "quite cold, conceptual art" -- something that can't be said for the Zizi Show.

Elwes first started bringing drag into his work by injecting 1,000 faces of drag performers into a standardized dataset collected by AI researchers of over 50,000 faces -- what he describes as "queering the dataset." The aim was to train neural networks to shift away from representing and understanding only normative identities, and the result was a video installation of seven giant morphing faces at the Edinburgh Festival in 2019.