What was hallucinated

Misrepresented: Case Law | Plaintiffs cited Krupski for the proposition that relation-back amendment is mandatory; court found Krupski does not establish that mandatory rule and the plaintiffs overstated the case's holding. || Misrepresented: Case Law | Plaintiffs cited Heller to claim temporary loss of Second Amendment rights is irreparable harm; court held Heller does not state that and plaintiffs improperly extended Elrod (a First Amendment case) to the Second Amendment. || Outdated Advice: Repealed Law | Plaintiffs relied on Oppenheimer for scope of discovery under Rule 26; court noted Oppenheimer has been superseded by statute and reliance on it was misplaced.

Details

"[T]he fact that Plaintiffs … did not "fabricate cases or cite nonexistent decisions" is of no help. When a case cite is "real," an attorney, or for that matter a judge, might see a case they recognize and assume the quote or holding has been accurately represented. That problem is illustrated here; although Chat GPT generated "holdings" that looked like they could plausibly have appeared in the cited cases, in fact it overstated their holdings to a significant degree. And while a litigant might get away with similar overstatements because they could, perhaps, reason their way to showing how a case's stated holding might extend to novel situations, an LLM does not reason in the way a litigant must.To put it in a slightly different way, LLMs do not perform the metacognitive processes that are necessary to comply with Rule 11. LLMs are tools that "emulate the communicative function of language, not the separate and distinct cognitive process of thinking and reasoning." When an LLM overstates a holding of a case, it is not because it made a mistake when logically working through how that case might represent a "nonfrivolous argument for extending, modifying, or reversing existing law or for establishing new law;" it is just piecing together a plausible-looking sentence—one whose content may or may not be true."Court later declined to reconsider this decision (see here).

Sanction teardown · E.D. Michigan, USA · 2025-12-02

Jarrus et al. v. Governor of Michigan et al.

What happened

In E.D. Michigan, USA, a filing relied on ChatGPT Plus to help draft legal argument. The court identified the following problems with the citations in that filing:

Misrepresented (Case Law)

Plaintiffs cited Krupski for the proposition that relation-back amendment is mandatory; court found Krupski does not establish that mandatory rule and the plaintiffs overstated the case's holding.
Misrepresented (Case Law)

Plaintiffs cited Heller to claim temporary loss of Second Amendment rights is irreparable harm; court held Heller does not state that and plaintiffs improperly extended Elrod (a First Amendment case) to the Second Amendment.
Outdated Advice (Repealed Law)

Plaintiffs relied on Oppenheimer for scope of discovery under Rule 26; court noted Oppenheimer has been superseded by statute and reliance on it was misplaced.

Which AI tool

ChatGPT Plus. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.

Outcome

Monetary sanctions (monetary penalty: 600 .)

Additional detail

"[T]he fact that Plaintiffs … did not "fabricate cases or cite nonexistent decisions" is of no help. When a case cite is "real," an attorney, or for that matter a judge, might see a case they recognize and assume the quote or holding has been accurately represented. That problem is illustrated here; although Chat GPT generated "holdings" that looked like they could plausibly have appeared in the cited cases, in fact it overstated their holdings to a significant degree. And while a litigant might get away with similar overstatements because they could, perhaps, reason their way to showing how a case's stated holding might extend to novel situations, an LLM does not reason in the way a litigant must.To put it in a slightly different way, LLMs do not perform the metacognitive processes that are necessary to comply with Rule 11. LLMs are tools that "emulate the communicative function of language, not the separate and distinct cognitive process of thinking and reasoning." When an LLM overstates a holding of a case, it is not because it made a mistake when logically working through how that case might represent a "nonfrivolous argument for extending, modifying, or reversing existing law or for establishing new law;" it is just piecing together a plausible-looking sentence—one whose content may or may not be true."Court later declined to reconsider this decision (see here).

How Citation Safe would have caught this

Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.

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Source: https://www.damiencharlotin.com/documents/1124/Jarrus_v._Gov_of_Michigan_USA_2_December_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).