Sanction teardown · JCC de Tucumán, Argentina · 2026-02-02
Ortiz Fatima Cecilia v. Booking.com y otros
What happened
In JCC de Tucumán, Argentina, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:
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Fabricated (Case Law)Court could not verify the cited precedent; provided links were unclear or redirected to other cases and the decision was not found in databases.
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Fabricated (Case Law)Citation accompanied by SAIJ id/link that corresponded to a different case (Yanson v. Firenze Viajes) and the invoked precedent was not located in databases.
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Fabricated (Case Law)No copy or adequate identification supplied; searches in usual jurisprudential databases failed to locate the cited decision.
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Fabricated (Case Law)Generic citation without sala, jurisdiction or date; not found in consulted jurisprudential databases and no supporting copy provided.
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Fabricated (Case Law)Cited generically without minimal individualization and not located in standard legal databases.
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Fabricated (Case Law)Citation not accompanied by verifiable copy and not found in the reviewed jurisprudential sources.
Which AI tool
an unnamed/unconfirmed AI tool. 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 sanction, bar referral, adverse costs order (monetary penalty: 620000 ARS.)
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.
Check a brief before you file it → · See our live false-verify rate
Source: https://www.damiencharlotin.com/documents/1477/Booking_Juz_Civil___Sanci%C3%B3n_IA.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).