Participatory AI Atlas
Participatory auditing / LLM safetyAI safety and participatory auditingParticipation documented

WeAudit

Pittsburgh, United States

ACM paper describes WeAudit as scaffolding user auditors and AI practitioners in auditing workflows.

participatory auditingaccountabilityevaluationauditinggovernancedeployment review
Project documentationEvidence source
Overview
Region
North America
Lead organization
Carnegie Mellon University / UC Berkeley collaborators
Organization type
university / research lab
Technology group
auditing workbenches
Activity status
active
Start year
2026
Last updated
Mar 25, 2026
Participation documentation
Participation mode
participatory auditing + co-production
Participants
user auditors; AI practitioners; researchers
Methods
scaffolded user auditing; tool design; evaluation
AI lifecycle stages
evaluation; auditing; governance; deployment review
Evidence summary
ACM paper describes WeAudit as scaffolding user auditors and AI practitioners in auditing workflows.
Atlas assessment
Core · High confidence · evidence grade A
Uncertainty
Public evidence indicates that stakeholders directly shaped AI design, data, deployment, evaluation, or oversight; residual uncertainty concerns the exact degree of shared decision power rather than project existence.
Project details
Participation group
Participatory Audit
Technology description
auditing workbenches
Funding
Not documented
Region of activity
global
Verification status
Mixed Verified
Links
Project documentationResearch paperEvidence sourceProgram page

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