A journalist seen from behind, standing between a pinboard of editorial questions — What happened, Why does it matter, What's the context — and a dissolving cloud of AI-generated fragments including headlines, summaries, and search results

Field Note 02: Why Humans Must Own the Narrative

ByIFMS AT GMBH

The information hierarchy that has governed knowledge work since the 1980s — Data, Information, Knowledge, Wisdom — has a blind spot. It has no place for narrative. This issue adds the missing layer, draws the line AI must not cross, and explains why the boundary is about accountability, not capability.

In every conversation about how AI will affect a newsroom and journalism, the same questions come up sooner or later: “Will AI now create journalism? Will AI take over the jobs of journalists? Will audiences even be able to tell the difference?” What follows is a debate about the exact nature of slop that AI tools produce, from good to bad to downright ugly. The better question — the urgent and necessary question — is: “What are the uniquely human responsibilities in an AI-enabled newsroom?”

The hierarchy with a blind spot

For the answer, we need to turn to information science, which has used a four-layer hierarchy since the 1980s, codified by Russell Ackoff, and which fits most knowledge work. There is Data, Information, Knowledge, Wisdom. 

  • Data — raw facts, numbers, transcripts. 
  • Information — data organised into context. 
  • Knowledge — information integrated into explanatory structures.
  • Wisdom — judgment good enough to act on. 

The model fits most knowledge work, but it does not fit journalism. Narrative is missing.

Narrative is more than facts or numbers. It is more sophisticated than contextualised information. But it is not yet wisdom. Narrative is deliberately structured knowledge — verified facts shaped through editorial judgment into a coherent account of a subject that helps a reader understand what happened, why it matters, and how the pieces and players connect. Sequencing. Causality, framing, and intentional emphasis.

Narrative is not a by-product of reporting. It is reporting. Narrative is the foundation of storytelling, and storytelling is one of the oldest human ways to bring people together, to capture attention, make people think, laugh, cry, or wonder. Insert that layer where it belongs and the hierarchy reads: Data, Information, Knowledge, Narrative, Wisdom. DIKNW.  

The uniquely human responsibility sits at the narrative layer of this sequence. The reason it sits there has to do with accountability — which is the part of this conversation AI most threatens to dissolve.

Frequency is not reasoning

Journalists who frame a story can be asked why and be held to account. Why this angle, but not that? Why is the headline cast as a provocation rather than a question when the circumstances of the story are unclear? Why does one voice carry the third paragraph and another the seventh? Journalists can answer. Their reasoning can be examined, values debated, and judgment overturned. If they are wrong, they can be challenged on the grounds they used. There is a chain of accountability journalism runs on. 

An AI system can be asked questions. But the chain of reasoning is less clear. An AI tool does not have ethical grounds, it has patterns. Asked why it framed a story the way it did, the most accurate answer it can give is: because text shaped this way appeared in the material I was trained on. That is not a reason. It is a frequency. And the system that produced it is, by acknowledged design, a black box. Even its makers cannot fully explain why a particular output emerged from a particular input. The opacity is not a bug to be patched. It is the technology.

Confine the black box

AI’s black box is not going to open; at least, for the time being. The response must be to confine it to the layers of work where its opacity is manageable, and to keep it out of the layer where opacity destroys what journalism is. AI can sit at data, information, and the assistive end of knowledge — places where its outputs can be checked against verifiable sources and corrected if wrong. It must not sit at narrative, where decisions must be accountable. They must be human.

Everything in the architecture I am developing rests on this distinction. The structured knowledge base. A two-layer separation between knowledge creation and AI-assisted distribution. An editorial firewall between them. Defences against the slow drift toward content that extracts attention but is not additive to audience value (otherwise known as enshittification). The next issues will work through the architecture piece by piece. The hierarchy is the map. What follows is the territory.

Until next time,

Dietmar