Queer In AI: A Case Study in Community-Led Participatory AI

Queer in AI

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Queerness and queer people face an uncertain future in the face of ever more widely deployed and invasive artificial intelligence (AI). These technologies have caused numerous harms to queer people, including privacy violations, censoring and downranking queer content, exposing queer people and spaces to harassment by making them hypervisible, deadnaming and outing queer people. More broadly, they have violated core tenets of queerness by classifying and controlling queer identities. In response to this, the queer community in AI has organized Queer in AI, a global, decentralized, volunteer-run grassroots organization that employs intersectional and community-led participatory design to build an inclusive and equitable AI future. In this paper, we present Queer in AI as a case study for community-led participatory design in AI. We examine how participatory design and intersectional tenets started and shaped this community's programs over the years. We discuss different challenges that emerged in the process, look at ways this organization has fallen short of operationalizing participatory and intersectional principles, and then assess the organization's impact. Queer in AI provides important lessons and insights for practitioners and theorists of participatory methods broadly through its rejection of hierarchy in favor of decentralization, success at building aid and programs by and for the queer community, and effort to change actors and institutions outside of the queer community. Finally, we theorize how communities like Queer in AI contribute to the participatory design in AI more broadly by fostering cultures of participation in AI, welcoming and empowering marginalized participants, critiquing poor or exploitative participatory practices, and bringing participation to institutions outside of individual research projects. Queer in AI's work serves as a case study of grassroots activism and participatory methods within AI, demonstrating the potential of community-led participatory methods and intersectional praxis, while also providing challenges, case studies, and nuanced insights to researchers developing and using participatory methods.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023
PublisherAssociation for Computing Machinery
Number of pages14
ISBN (Electronic)9781450372527
StatePublished - Jun 12 2023
Externally publishedYes
Event6th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023 - Chicago, United States
Duration: Jun 12 2023Jun 15 2023

Publication series

NameACM International Conference Proceeding Series


Conference6th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


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