# Researchers propose community-based audits to uncover AI harms to queer communities

Digest AI · Society & Work · published 2026-11-03T05:00:00Z

Canonical: https://digestai.news/story/researchers-propose-community-based-audits-to-uncover-ai-harms-to-quee

## Summary

A new paper on arXiv argues that standard AI audits miss harms to queer communities because they rely on aggregate data and fail to capture lived experiences. The authors say technical audits often overlook issues like erasure, misclassification, and discrimination because they lack community input.

The study describes a participatory workshop at EurIPS 2025 where 16 queer community members audited four AI case studies using the 4Cs harm taxonomy. Participants identified harms tied to problem definition, data collection, and contractual structures that exploit vulnerable groups. The findings suggest community-informed auditing could reveal harms that traditional methods overlook.

## Key points

- Workshop involved 16 queer community members auditing four AI case studies at EurIPS 2025
- Participants traced harms to problem definition, data collection, and exploitative contracts
- Authors argue standard audits fail to detect identity-specific harms due to lack of community input

## Why it matters

This research highlights gaps in current AI auditing practices, showing how community-led approaches could uncover overlooked harms to marginalized groups.

## Sources

1. [Queering the Audits: Community-Based Auditing of AI Harms to Queer Communities](https://arxiv.org/abs/2611.00345) (arXiv cs.CL, 2026-11-03, primary source)

## Cite

Digest AI, "Researchers propose community-based audits to uncover AI harms to queer communities", 3 November 2026, https://digestai.news/story/researchers-propose-community-based-audits-to-uncover-ai-harms-to-quee

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