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The Zizi Project  is a series of connected art and performance pieces created by artist Jake Elwes in collaboration with Me The Drag Queen and members of London’s drag performance scene. The works – currently  Zizi: Queering the Dataset  (2019),  Zizi &amp; Me  (2020; ongoing), and  The Zizi Show  (2020) – sit at the intersection of drag performance and Artificial Intelligence (AI), playing with and queering facial recognition software, deepfake technologies, and Machine Learning algorithms. I consider  The Zizi Project  as an example of work at the vanguard of an emergent field of queer AI performance. The project intervenes in complex conversations surrounding AI and Machine Learning, including the lack of representation of diverse identities and communities in datasets used to train these systems and the complexity of creating datasets which include queer and trans bodies and identities. However, in aiming to use drag performance to expose and demystify these complex technological systems to audiences, I propose that queerer forms of art making and performance emerge that push at the boundaries of both drag and the technologies used. Ultimately,  The Zizi Project  articulates drag and queer futures where the digital and the actual interact in increasingly complex ways to explore notions of diversity, inclusion, and access that speak to fundamental questions of what counts as drag, what counts as queer, and, indeed, what count as human.

Kings, Queens, Monsters, and Things: Digital Drag Performance and Queer Moves in Artificial Intelligence (AI)