Making Trouble: Techniques for Queering Data and AI Systems

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.

Año de publicación:

2024

Keywords:

• AI Systems
• Algorithmic Systems
• data
• design
• Human-in-the-Loop (HITL)
• Machine Learning
• Queering
• Queering-the-Loop

Fuente:

scopus