Sanction teardown · D. Arizona, USA · 2025-03-11
Arnaoudoff v. Tivity Health Incorporated
What happened
In D. Arizona, USA, a filing relied on ChatGPT to help draft legal argument. The court identified the following problems with the citations in that filing:
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Fabricated (Case Law)Plaintiff’s objection repeatedly cited nonexistent cases, which the Court labeled as fake cases and agreed to disregard after Defendants flagged the issue.
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Fabricated (Case Law)To argue that lack of counsel made the settlement involuntary, Plaintiff relied on nonexistent case law; the Court found no such authority exists.
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Misrepresented (Case Law)Plaintiff cited Alcaide v. Thomas as supporting her position on unenforceability, but the case actually held the parties were bound by their settlement.
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Fabricated (Case Law)Plaintiff admitted she used ChatGPT and external tools that produced erroneous, fake case citations in her objections.
Which AI tool
ChatGPT. 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
Court ignored fake citations and granted motion to correct the record
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/369/Arnaoudoff_v._Tivity_Health_Incorporated_D._Arizona_USA_March_11_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).