Skip to search boxSkip to navigationSkip to main content

Making Trouble: Techniques for Queering Data and AI Systems

  • Anh-Ton Tran
    ,
  • Annabel Rothschild
    ,
  • Kay Kender
    ,
  • Ekat Osipova
    ,
  • Brian Kinnee
    ,
  • Jordan Taylor
  • Georgia Institute of Technology
    ,
  • Vienna University of Technology
    ,
  • University of Washington
    ,
  • Carnegie Mellon University
    ,
  • University of Michigan
    ,
  • University of Sussex
Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Open access

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Conference article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 381-384 (4 pages)

Journal (Volume, Issue Number)

Proceedings of the Designing Interactive Systems Conference

Publication milestones

  • Published - 01/07/2024

Publication status

Published - 01/07/2024

Publication IDs

  • Scopus: 85198903258

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.

Publication metrics

PlumX, opens in new tab

Captures
6
Citations
7

Related Event

Title

ACM Conference on Designing Interactive Systems

Event type

Conference

Degree of recognition

Local event

Date

01/07/2024 - 05/07/2024

Location

IT University of CopenhagenCopenhagenDenmark