Making Trouble: Techniques for Queering Data and AI Systems
Anh-Ton Tran, Annabel Rothschild, Kay Kender, Ekat Osipova, Brian Kinnee, Jordan Taylor, Louie Søs Meyer, Oliver L. Haimson, Ann Light, Carl DiSalvo
Abstract
This one day workshop will explore queering as a design technique for troubling data and AI systems, ranging from quotidian personal data to recent Generative AI tools. By surfacing numerous instances of queering data or AI, we will come together to develop an archive of techniques for queering or artful subversion. From this archive, participants will select a technique and develop a speculative prototype or artifact via critical making. In doing so, we resist techno-determinism and conventional narratives of AI harms and benefits by tracing queer possibilities outside these categories.
Topics & Concepts
Computer scienceData scienceInnovative Human-Technology InteractionInformation Systems Theories and ImplementationEthics and Social Impacts of AI