Sanction teardown · W.D. Washington, USA · 2026-02-13
Merz v. City of Kalama
What happened
In W.D. Washington, 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)Merz relied on Caruso v. Local Union 690, 107 Wn.2d 524, 529-30 (1987) to support a 'per se' defamation assertion; court found the citation misleading because the cited pages do not contain the 'per se' language Merz attributed to it.
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Fabricated (Case Law)Merz cited 'Sorensen v. City of Bellingham, 15 Wn. App. 2d 730, 733, 478 P.3d 1110 (2020)' which was inaccurate/fabricated; Merz later admitted he intended to cite Norg v. City of Seattle, 200 Wn.2d 749 (2023); court noted the inaccuracy but declined to dismiss on that basis.
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
Not specified in source record.
Additional detail
Merz corrected the Sorensen citation, saying he intended to cite Norg v. City of Seattle, 200 Wn.2d 749 (2023). The court declined to dismiss based solely on the inaccurate citation, noted the replacement authority was not closely analogous, and proceeded to dismiss the claims on the merits.
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/1612/Merz_v_City_of_Kalama_USA_13_February_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).