[Submitted on 30 Oct 2026]
Title:Queering the Audits: Community-Based Auditing of AI Harms to Queer Communities
View a PDF of the paper titled Queering the Audits: Community-Based Auditing of AI Harms to Queer Communities, by Organizers of QueerInAI: A Pranav and 8 other authors
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Abstract:AI systems embed majority-group defaults into training data, evaluation metrics, and category definitions, producing documented harms for queer communities including erasure, misclassification, and discrimination. Standard technical audits often rely on aggregate measures and cannot detect harms that be come visible only through the lived experience of affected communities. We conducted a participatory auditing workshop at EurIPS 2025 where 16 queer community members audited four case studies using the 4Cs harm taxonomy (Content, Conduct, Contact, Contract) applied across the AI lifecycle. Participants used structured worksheets and plenary synthesis to classify harms and trace them to their origins in the development pipeline. Across all four cases, participants traced harms to problem definition and data collection, and they identified contractual structures that extract value from vulnerable populations while providing minimal recourse. These findings illustrate that community-informed auditing surfaces concrete, identity-specific harms that aggregate evaluation methods risk overlooking.
Comments: Published in Identity Aware AI workshop at LREC 2026
Subjects:
Computation and Language (cs.CL); Computers and Society (cs.CY)
Cite as: arXiv:2611.00345 [cs.CL]
(or arXiv:2611.00345v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2611.00345
arXiv-issued DOI via DataCite (pending registration)
Journal reference: In Proceedings of the Second Workshop of Identity Aware AI at 2026, pages 66-76, Palma de Mallorca, Spain. European Language Resources Association
Related DOI:
https://doi.org/10.63317/5acrwqmesyw4
DOI(s) linking to related resources
Submission history
From: A Pranav [view email] [v1] Fri, 30 Oct 2026 20:26:03 UTC (405 KB)
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