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Episode #3Apr 1, 2025· 1:20:30
Too Many Documents, Too Little Time: How iTromsø Saved 80% of Research Time with AI.
Guest: Lars Giske at iTromsø
About this episode
How can a small Local Newsroom in northern Norway take on one of Investigative journalism's biggest challenges — and win?
In this episode, we talk with Lars Adrian Giske, Head of AI at iTromsø, about how his team built Djinn — the Data Journalism Interface for News Gathering and Notification. This AI-powered tool is transforming how journalists work by surfacing the most newsworthy content from massive piles of public documents.
From document overload to AI-powered discovery, Lars shares:
- The real problem behind FOIA delays and public archives
- How Djinn works to identify relevant stories in real time
- Why involving journalists from day one made all the difference
- What happened when they scaled the tool across Polaris Media
- How AI is changing investigative journalism, ethics, and newsroom stress
- Why the human element will always matter — even in an AI-driven future
Hosted by Nils Ove Håland Riise, this conversation dives deep into the future of data-driven journalism, transparency in media, and the rise of AI in local newsrooms — with real-world results that are nothing short of amazing.
- Journalists face massive time waste from public document review
- AI can cut research time by up to 80%
- Localized AI models increase accuracy
- Trust, ethics, and collaboration matter more than ever
- Journalists aren't being replaced — they're being empowered
- The human judgment behind every story is still irreplaceable