Sanction teardown · D. South Dakota, USA · 2025-11-17
Mattson & Dostal v. Rosebud Electric Cooperative et al.
What happened
In D. South Dakota, 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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Fabricated (Case Law)Defendants flagged numerous fictitious case citations and incorrect case citations in Plaintiffs' response brief; Plaintiffs later filed a Notice of Corrected Citations and the Court noted the issue.
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False Quotes (Case Law)Defendants identified non-existent quotations and misquoted case law in Plaintiffs' brief; Plaintiffs filed corrections and the Court reviewed the submissions, declining sanctions.
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
Warning
Additional detail
Defendants' reply identified fictitious cases, incorrect citations, and non-existent quotations in Plaintiffs' response brief. Plaintiffs filed a Notice of Corrected Citations; the Court noted formatting that suggested use of generative AI but declined to sanction the pro se plaintiffs, advising compliance with Rule 11 in future filings.
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/1062/Mattson__Dostal_v._Rosebud_USA_17_November_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).