Abstract

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 & 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.

摘要

Zizi 项目是艺术家 Jake Elwes 与 Me The Drag Queen 以及伦敦变装表演界成员合作创作的一系列艺术和表演作品。这些作品目前包括《Zizi: Queering the Dataset》（2019 年）、《Zizi & Me》（2020 年；正在进行中）和《The Zizi Show》（2020 年），它们处于变装表演和人工智能 (AI) 的交叉点，玩弄和质疑面部识别软件、深度伪造技术和机器学习算法。我考虑Zizi 项目作为酷儿人工智能表演新兴领域先锋工作的一个例子。该项目介入了围绕人工智能和机器学习的复杂对话，包括用于训练这些系统的数据集中缺乏对不同身份和社区的表示，以及创建包括酷儿和跨性别者身体和身份的数据集的复杂性。然而，为了利用变装表演向观众揭露和揭开这些复杂的技术系统的神秘面纱，我建议出现酷儿形式的艺术创作和表演，从而突破变装和所使用技术的界限。最终，Zizi 项目阐明了变装和酷儿的未来，其中数字和现实以日益复杂的方式相互作用，探索多样性、包容性和访问的概念，这些概念涉及什么算作变装、什么算作酷儿以及实际上什么算作人类等基本问题。