Sanction teardown · N.D. Alabama, USA · 2026-05-21
Jackie L. Miller v. Regions Bank
What happened
In N.D. Alabama, USA, a filing relied on ChatGPT to help draft legal argument. The court identified the following problems with the citations in that filing:
-
False Quotes (Case Law)Purported quotation attributed to Batson v. Salvation Army regarding FMLA adverse action, but the court could not find the quoted language in the cited Eleventh Circuit opinion and concluded it was fabricated.
-
False Quotes (Case Law)Purported quotation attributed to Holly v. Clairson Indus., but the court's search found no such language in the opinion; court concluded the quotation was fabricated.
-
False Quotes (Case Law)Purported quotation attributed to EEOC v. St. Joseph’s Hosp., Inc., but the court could not locate the quoted passage in that opinion or other authority; court concluded the quotation was fabricated.
-
False Quotes (Case Law)Purported quotation attributed to Breen v. Dep’t of Transp., but the court found no such language in the cited D.C. Cir. opinion and concluded the passage was invented.
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
DQ from case and court (6 months); Bar Referral
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/2169/Miller_v._Regions_Bank_USA_21_May_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).