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Merz v. Kalama

Court
W.D. Washington
Jurisdiction
USA
Decided
2025-02-25
AI tool
Unidentified
Outcome
—
Monetary penalty
None reported

What was hallucinated

Misrepresented: Legal Norm | Plaintiff claimed AI said no motion to amend was required because a scheduling order set an amendment deadline; the Court clarified Rule 15 governs and still requires leave to amend. || Misrepresented: Legal Norm | Plaintiff implied the clerk’s office told him he need not seek leave to amend due to the scheduling order; the Court stated the clerk’s office does not give legal advice and Rule 15 applies.

Sanction teardown · W.D. Washington, USA · 2025-02-25

Merz v. 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:

  • Misrepresented (Legal Norm)
    Plaintiff claimed AI said no motion to amend was required because a scheduling order set an amendment deadline; the Court clarified Rule 15 governs and still requires leave to amend.
  • Misrepresented (Legal Norm)
    Plaintiff implied the clerk’s office told him he need not seek leave to amend due to the scheduling order; the Court stated the clerk’s office does not give legal advice and Rule 15 applies.

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.

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://storage.courtlistener.com/recap/gov.uscourts.wawd.337376/gov.uscourts.wawd.337376.24.0.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

Source: https://storage.courtlistener.com/recap/gov.uscourts.wawd.337376/gov.uscourts.wawd.337376.24.0.pdf

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