Queer zineographies: materializing tactics for resisting AI and data systemsShow others and affiliations
2026 (English)In: DIS '26: Proceedings of the 2026 Designing Interactive Systems Conference, ACM Digital Library, 2026, p. 1574-1592Conference paper, Published paper (Refereed)
Abstract [en]
CSS ConceptsAs AI and data systems often falter when encountering queer identities and knowledge, reinforcing existing oppressions, queer people have resisted such systems and their normalizing tendencies. This pictorial explores tactics of queering AI through a collaborative zine-making project (i.e. zineography) that challenges generative AI and data systems. We share how we workshopped and materialized queering tactics in zine spreads; analyzed these spreads according to materials, content, and tone; and visualized our analysis as thematic collages. We contribute: (1) tangible characteristics of queering AI and data systems (i.e. materials, tones, and aesthetics); and (2) design opportunities for using zineographies as a radical method for building and collectively sharing knowledge about a marginalized community, including recommendations for enacting queer zineographies. By materializing queering tactics through zine-making, we invite embodied, action-oriented critiques that question dominant techno-solutionist movements and trace queer possibilities outside of their normalizing narratives.
Place, publisher, year, edition, pages
ACM Digital Library, 2026. p. 1574-1592
Keywords [en]
AI Systems, Algorithmic Systems, Data, Machine Learning, Queer HCI, Queering, Zineography, Zines
National Category
Gender Studies
Identifiers
URN: urn:nbn:se:umu:diva-256629DOI: 10.1145/3800645.3812834Scopus ID: 2-s2.0-105042834937ISBN: 9798400725630 (electronic)OAI: oai:DiVA.org:umu-256629DiVA, id: diva2:2086539
Conference
ACM conference on Designing Interactive Systems, DIS 2026, Singapore, Singapore, June 13-17, 2026
2026-07-142026-07-142026-07-14Bibliographically approved