Sanction teardown · Arizona CA, USA · 2026-01-02
Washburn v. Houston
What happened
In Arizona CA, USA, 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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Misrepresented (Case Law)Brief cites Buencamino, Woyton, Reid, Vincent, and Thompson as addressing specific relocation factors, but none of those cases discuss the claimed factors.
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False Quotes (Case Law)Brief attributes quotations to Owen v. Blackhawk that do not appear in that opinion.
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False Quotes (Exhibits & Submissions)Brief purports to quote the amended decree and the May 2023 and November 2024 evidentiary hearing transcripts, but the quoted material does not appear in those records.
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
Bar referral
Additional detail
Appellant Father's counsel submitted an opening brief containing misleading/inaccurate legal citations, mischaracterized case law, fabricated quotations attributed to Owen v. Blackhawk, and false quotations purportedly from the amended decree and hearing transcripts. The appellate court identified these errors, concluded they supported a potential ethics referral, and forwarded the decision to the State Bar for review.
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/1275/Washburn_v._Houston_2_January_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).