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When Claude Hallucinates in Court: The Latham & Watkins Incident and What It Means for Attorney Liability

ByRicardo

There is a specific form of irony that the authorized career not often will get to witness in such pristine kind. In May 2025, Latham & Watkins a agency that routinely payments over $2,000 an hour for its companions and counts Anthropic amongst its purchasers filed a court docket declaration in Concord Music Group v. Anthropic that contained fabricated quotation particulars. The citations weren’t invented by a sleep-deprived affiliate pulling an all-nighter. They had been generated by Claude, the very AI mannequin that Latham & Watkins was in court docket defending.

Sit with that for a second.

The lawyer arguing that Claude shouldn’t be a copyright infringement machine used Claude to format a authorized quotation in an energetic case and Claude bought the authors incorrect, the title incorrect, and no person caught it till opposing counsel began digging. The irony isn’t simply scrumptious. It’s instructive. Because what occurred inside that submitting is a near-perfect X-ray of the structural drawback that AI poses for authorized observe: not that AI is clearly incorrect, however that it’s convincingly, plausibly, professionally incorrect in ways in which evade even skilled human evaluate.

The Anatomy of the Incident

To perceive the authorized publicity, it’s important to perceive precisely how the error occurred — as a result of it wasn’t sloppy. It was systematic.

The sequence was this: a Latham colleague discovered what seemed to be a supporting tutorial supply through Google Search. Dukanovic then requested Claude to format a correct authorized quotation for that supply, offering the proper URL. Claude returned a quotation with the correct publication yr and the proper hyperlink — however the incorrect title and incorrect authors. When the group ran its handbook quotation test, they verified the hyperlink resolved appropriately. They didn’t confirm whether or not the metadata Claude generated for that hyperlink was correct. The declaration containing these errors was filed. Opposing counsel observed. A federal court docket bought concerned.

What makes this technically vital is that Claude didn’t hallucinate a phantom supply — it discovered an actual one and then misdescribed it. This is definitely more durable to catch than a totally fabricated quotation, as a result of the URL resolves, the paper exists, the yr is true. The error is embedded on the degree of metadata, not existence. It’s the authorized equal of citing an actual statute from the incorrect jurisdiction.

The court docket subsequently mandated specific disclosure of AI utilization and human verification necessities for future filings. The choose’s response was proportionate however pointed. This wasn’t dismissed as a technical glitch. It was handled as knowledgeable failure.

Rule 11 and the Architecture of Attorney Responsibility

Here is the place the incident stops being a narrative about one agency and turns into a structural query about your complete career.

Rule 11 of the Federal Rules of Civil Procedure requires attorneys to certify with their signature that each factual competition in a submitting has evidentiary assist and that the submitting shouldn’t be submitted for improper functions. That signature shouldn’t be ceremonial. It is knowledgeable illustration that the lawyer has exercised affordable diligence to confirm what they’re placing earlier than the court docket.

The drawback is that Rule 11 was written for a world the place fabrication required intent or gross carelessness. An legal professional who invented a case quotation was both mendacity or catastrophically negligent. But Claude doesn’t fabricate with intent. It fabricates with confidence. The output is formatted, fluent, correctly punctuated, and returned in milliseconds. There is not any stylistic inform, no hesitation marker, no sign that the mannequin is working on the fringe of its competence. The professional-looking wrapper of the output is exactly what makes it harmful.

In Gauthier v. Goodyear Tire & Rubber Co., determined in the Eastern District of Texas in late 2024, a plaintiff’s legal professional submitted a short containing citations to 2 nonexistent instances and a number of fabricated quotations additionally generated by Claude. When the court docket issued a show-cause order, the legal professional admitted he had used Claude with out verifying the output. The sanctions had been comparatively gentle: a $2,000 penalty, obligatory CLE on AI in authorized observe, and an obligation to share the order together with his present employer. But the court docket’s reasoning was unambiguous — the legal professional’s skilled obligation beneath Rule 11 doesn’t diminish as a result of an AI generated the content material. The verification obligation doesn’t switch to the machine. It stays with the lawyer.

This is the constitutional core of the issue. Rule 11 requires certification. Certification requires diligence. Diligence requires verification. But verification, in the context of AI-generated authorized content material, is now not a routine proofreading train. It is a technical competency activity one which many practitioners are neither educated for nor culturally inclined to carry out.

The Duty of Competence in the Age of Plausible Output

The American Bar Association’s Model Rule 1.1 requires attorneys to offer competent illustration, which incorporates “the authorized data, ability, thoroughness, and preparation fairly vital for the illustration.” The ABA’s 2012 Comment 8 to this rule added that competent attorneys should “preserve abreast of modifications in the legislation and its observe, together with the advantages and dangers related to related know-how.”

That remark, added over a decade in the past, was understood on the time to cowl issues like e-discovery software program and encrypted communications. Nobody was fascinated about giant language fashions. But in 2025, it has change into the operative textual content for a brand new style of malpractice publicity.

The key phrase in Comment 8 is dangers. A reliable legal professional utilizing AI shouldn’t be merely one who is aware of easy methods to immediate Claude successfully. It is one who understands the class of errors that AI produces, the situations beneath which these errors change into extra probably, and the verification protocols essential to catch them. The Latham incident illustrates exactly the hole between surface-level AI literacy (“I understand how to ask Claude to format a quotation”) and useful AI competence (“I do know that Claude can confidently return metadata errors on actual sources, and I’ve a protocol to catch that”).

Importantly, almost 75% of attorneys cited accuracy as their largest concern about AI instruments, based on the ABA’s 2024 Legal Technology Survey Report. But concern and competence should not the identical factor. The identical survey steered widespread adoption of AI instruments for authorized analysis and drafting regardless of that said anxiousness which suggests attorneys are, collectively, apprehensive about one thing they’re continuing to make use of anyway, with out essentially creating the precise verification abilities that may tackle their fear.

What “Verification” Actually Has to Mean Now

The Latham incident exposes a spot in how authorized professionals conceptualize verification. Traditionally, checking a quotation meant confirming the case exists, pulling the related web page, and studying the quote in context. These are duties that reinforce themselves the act of going again to the supply is itself the verification.

But when an legal professional asks Claude to format a quotation for a supply they’ve already discovered, the psychological dynamic shifts. The legal professional has already completed what they contemplate the laborious work (finding the supply). The formatting feels clerical. And as a result of Claude’s output appears appropriate correct journal type, correct URL, believable creator names it doesn’t set off the cognitive alarm bells that an clearly incorrect reply would.

This is the hallucination failure mode that’s hardest to engineer round: not the fabricated phantom, however the believable misdescription. It requires a class of verification that authorized coaching doesn’t at present emphasize — what you may name metadata verification: independently confirming not simply {that a} supply exists, however that the precise descriptive claims the AI makes about that supply (authorship, title, publication date, journal title) match the precise doc, line by line.

For AI-generated authorized citations particularly, this implies: retrieve the supply independently, not through the AI’s hyperlink; cross-reference the creator names in opposition to the byline in the unique doc; confirm the title character by character; affirm the journal title in opposition to the masthead. It is slower than proofreading. It requires extra self-discipline than clicking a hyperlink. And in a career that payments by the hour and prizes effectivity, it introduces friction that companies could also be reluctant to institutionalize.

The Deeper Irony: Defending AI with AI

There is a dimension to this story that authorized commentary has largely let go with out examination: Anthropic was the defendant. Claude was the product at problem. The lawsuit introduced by Concord Music Group and different main music publishers in October 2023 alleged that Anthropic had scraped copyrighted music lyrics to coach Claude with out authorization. The case was, at its core, a dispute about whether or not Claude’s coaching course of revered mental property legislation.

And Latham & Watkins, in defending that case, used Claude to assist put together court docket filings and these filings contained AI-generated errors that required court docket intervention.

This shouldn’t be merely ironic. It is epistemically vital. It means that even the authorized groups most deeply embedded in AI litigation, most educated about AI’s limitations, most incentivized to make use of AI rigorously in an AI-adjacent case, are nonetheless prone to the identical verification failures which might be sanctioning much less refined practitioners throughout the nation. If Latham can not construct a dependable AI verification protocol right into a high-stakes case the place the AI’s personal maker is the consumer, the profession-wide problem is significantly bigger than bar associations and legislation faculty curricula have but acknowledged.

What Comes Next And What Needs To

Courts are responding, erratically. Several federal districts have issued standing orders requiring disclosure of AI-assisted drafting in filings. The court docket in Concord Music mandated each disclosure and human verification. Judge Michael Wilner of California fined a legislation agency $31,000 after discovering that just about a 3rd of the citations in a short had been AI-fabricated. These should not remoted disciplinary incidents — they’re the early form of a brand new jurisprudence round AI skilled accountability.

What the career wants, and doesn’t but have in any systematic kind, is a technical taxonomy of AI failure modes translated into verification protocols. Rule 11 compliance in the AI period can’t be happy by a basic instruction to “double-check AI output.” It requires attorneys to know, particularly, that: reasoning fashions hallucinate at increased charges on doc summarization than commonplace fashions; that metadata errors are much less visually salient than phantom-citation errors; that confidence in AI output shouldn’t be correlated with accuracy; and that formatting duties carry as a lot hallucination danger as drafting duties.

Law faculties should not instructing this. Bar associations are issuing steerage at a tempo that lags the know-how by roughly eighteen months. And legislation companies are deploying AI instruments in client-facing work whereas constructing verification protocols which might be, at greatest, variations of pre-AI proofreading habits.

The Latham & Watkins incident will probably be remembered as probably the most clarifying knowledge level of 2025 for AI and authorized observe not as a result of it concerned a rogue actor or a spectacular failure, however as a result of it was peculiar. It was a reliable legal professional, at an elite agency, utilizing a succesful AI software, in a believable manner, and producing an error that the entire group missed. That ordinariness is the purpose. The query the career should now reply shouldn’t be whether or not AI will create legal responsibility publicity for attorneys. It already has. The query is whether or not the response might be critical sufficient to match the chance.

Sources

  • The Register — Anthropic’s legislation agency blames Claude hallucinations for errors (May 2025): https://www.theregister.com/2025/05/15/anthopics_law_firm_blames_claude_hallucinations/
  • NexLaw Blog — AI Hallucination: The Silent Threat to Legal Accuracy in the U.S. (2026): https://www.nexlaw.ai/weblog/ai-hallucination-legal-risk-2025/
  • Baker Botts — Trust, But Verify: Avoiding the Perils of AI Hallucinations in Court (Dec. 2024): https://www.bakerbotts.com/thought-leadership/publications/2024/december/trust-but-verify-avoiding-the-perils-of-ai-hallucinations-in-court
  • Suprmind — AI Hallucination Rates & Benchmarks in 2026: https://suprmind.ai/hub/ai-hallucination-rates-and-benchmarks/
  • Spellbook — Why Lawyers Are Switching to Claude AI (2026 Guide): https://www.spellbook.authorized/be taught/why-lawyers-are-switching-to-claude
  • CPO Magazine — 2026 AI Legal Forecast: From Innovation to Compliance (Jan. 2026): https://www.cpomagazine.com/data-protection/2026-ai-legal-forecast-from-innovation-to-compliance/
  • National Law Review — 85 Predictions for AI and the Law in 2026: https://natlawreview.com/article/85-predictions-ai-and-law-2026

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