Journalism has editors. It has fact-checkers. It has copy desks and standards teams. What it doesn’t have, and desperately needs, is a journoturg: someone whose job is to interrogate the structure of a story before it goes live.

Not the facts. Not the grammar. The narrative spine: whose voice leads, what gets staged as conflict, where causality is implied but unproven, and which stakeholders are silently edited out of the frame.

Theatre has had this role for centuries. It’s called a dramaturg, and their job is to stress-test a script’s architecture so the audience receives what the creators think they’re sending. Newsrooms need the same function and AI is uniquely suited to deliver it.

What a Dramaturg Does (and Why Journalism Needs One)

A dramaturg doesn’t write the play. They don’t direct it. They analyze its bones: structure, subtext, power dynamics, and gaps between intention and effect. They ask questions like:​

• Whose perspective controls the narrative?
• What’s being treated as background when it should be foreground?
• Where does the story imply causality that the evidence doesn’t support?
• Who benefits from this framing?

Editors ask Is this accurate? Journoturgs ask Is this true?

The difference matters. A story can be factually accurate, every quote verified, every date correct, and still distort reality through sequencing, character casting, and emotional architecture.​

Where Journalism’s Structural Blindness Lives

Newsrooms are good at catching bad facts. They’re terrible at catching bad frames.

Consider:

• Crime stories that position police as protagonists and victims as props
• Political coverage that treats “both sides” as equally credible when one is provably lying
• Features that bury systemic causes in human-interest packaging
• Breaking news that implies causality through adjacency (“protests turned violent” vs. “police escalated”)

These aren’t fact errors. They’re dramaturgical errors: failures of structure that newsroom workflows aren’t designed to catch.

AI as Journoturg: What It Can Do

AI won’t, and shouldn’t, write news copy. Generative models hallucinate, amplify training-set biases, and can produce fluent nonsense. Turning them loose as authors is ethically reckless.​

But AI excels at pattern recognition, structural analysis, and scale, exactly what journoturgy requires.​

Here’s what an AI journoturg could deliver:

1. Narrative Structure Audit

Map who gets quoted, who’s paraphrased, who’s unnamed. Flag when marginalized voices are relegated to late grafs or reactionary quotes while institutional voices lead.​

2. Frame and Bias Detection

Compare how the same event is covered across outlets. Surface recurring metaphors, hero/villain casting, and implied causality. Show reporters when their draft unconsciously mimics a skewed template.​

3. Fact and Logic Triage

Pre-check claims, dates, entities, and causal chains against trusted databases. Flag high-risk assertions and logical gaps for manual verification.​

4. Omission Detection

Identify missing context: stakeholders not contacted, counterevidence not addressed, alternative explanations not considered.​

The AI doesn’t decide what’s true. It shows journalists where the structure might be lying.

Why This Works and Is Safe

Journoturgy keeps AI in its ethical lane: analysis, not authorship.​

• Humans retain final editorial control
• AI functions as x-ray, not scalpel
• The output is a diagnostic report, not publishable copy
• Journalists decide whether and how to restructure based on AI findings

This aligns with emerging best practices: AI as augmentation tool, transparency about its use, and human accountability for all published work.​

What This Means for Newsrooms

Implementing journoturgy doesn’t require rebuilding workflows. It requires adding one step:

Before publication, run the draft through an AI journoturg and review its structural critique.

Questions it might surface:

• “This story quotes five officials and one community member. Is that proportional to reality?”
• “Paragraph 3 implies X caused Y, but your sourcing only shows correlation.”
• “Three similar stories this week used the same crime/chaos framing. Is that pattern accurate or reflexive?”

Not every flag will be valid. But surfacing the pattern lets editors make conscious choices instead of unconscious ones.

Why Now

AI in journalism is at a crossroads. One path leads to bot-written churn and eroded trust. The other leads to structural rigor and transparency.

Journoturgy offers the better path: AI as partner in narrative truth, not replacement for human judgment.

Theatre learned centuries ago that you can’t trust a story’s architecture without someone whose job is to interrogate it. Journalism is finally catching up.

The dramaturg is here. We just need to let it do its job.