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Queering the Audits: Community-Based Auditing of AI Harms to Queer Communities — arXiv:2611.00345

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.00345
License (as archived): CC0-1.0
Archived: 2026-11-03T18:22:34.407Z
SHA-256 of the archived text: ba30c168a05ecc32ed4020d39e35d9b8ee10c83d2fb57609c8b5389950bbd032
Stable URL of this page: https://metraipolis.com/documento/dc_44d587ffc2ac

How to cite

Queering the Audits: Community-Based Auditing of AI Harms to Queer Communities — arXiv:2611.00345 — arXiv (en), https://arxiv.org/abs/2611.00345 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_44d587ffc2ac (Metraipolis archive dc_44d587ffc2ac, sha256 ba30c168a05ecc32ed4020d39e35d9b8ee10c83d2fb57609c8b5389950bbd032)

BibTeX

@misc{dc44d587ffc2ac,
  title = {Queering the Audits: Community-Based Auditing of AI Harms to Queer Communities — arXiv:2611.00345},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.00345},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_44d587ffc2ac; sha256 ba30c168a05ecc32ed4020d39e35d9b8ee10c83d2fb57609c8b5389950bbd032},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.00345. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

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.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.CL, nuovi lavori del giorno).
Categorie arXiv: Computation and Language (cs.CL) ; Computers and Society (cs.CY).
Pagina del lavoro: https://arxiv.org/abs/2611.00345 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T18:10:07.880Z dalla pagina https://arxiv.org/list/cs.CL/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).