What was hallucinated

Fabricated: Case Law | Mother's briefs included multiple cited cases that the court found do not exist; the court attributed the errors to AI-assisted drafting. || Misrepresented: Legal Norm | Mother relied on Indiana Code §31-17-2-16 for authority to appoint a parenting coordinator, but the court found the statute does not govern that point (misapplied legal norm).

Details

The court observed that Mother's briefs included many cited authorities that do not exist and that one statute she cited was not on point. Mother admitted using Chat GPT to prepare pleadings. The court affirmed the trial court's orders and warned litigants to verify AI-generated citations.

Sanction teardown · CA Indiana, USA · 2025-10-30

In re: the Marriage of Melinda Johnson v. Sabastian Johnson

What happened

In CA Indiana, USA, a filing relied on ChatGPT to help draft legal argument. The court identified the following problems with the citations in that filing:

Fabricated (Case Law)

Mother's briefs included multiple cited cases that the court found do not exist; the court attributed the errors to AI-assisted drafting.
Misrepresented (Legal Norm)

Mother relied on Indiana Code §31-17-2-16 for authority to appoint a parenting coordinator, but the court found the statute does not govern that point (misapplied legal norm).

Which AI tool

ChatGPT. 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

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/1004/In_re_the_Marriage_of_Melinda_Johnson_USA_30_October_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

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