Sanction teardown · Fair Work Commission, Australia · 2025-01-20
Candice Dias v Angle Auto Finance
What happened
In Fair Work Commission, Australia, 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:
-
Fabricated (Case Law)in relation to Kenny v Business Council of Australia [2015] FCAFC 75 it had been unable to find a case of that name and citation, with the citation being for a different case,
-
Misrepresented (Case Law)in relation to Yorke v Lucas [2015] FWCFB 6592, there did not appear to be a decision of the Full Bench of the Commission with that name or citation and while there was a High Court case with that name, it dealt with accessorial liability under the Trade Practices Act;
-
Fabricated (Case Law)in relation to Cowan v Fairfax Media Publications Pty Ltd [2015] FWC 1399, the case could not be located;
-
Fabricated (Case Law)in relation to Gibbons v Newcastle City Council [2016] FWCFB 3638 there did not appear to be a decision of the Full Bench of the Commission with that name or citation.
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.
Check a brief before you file it → · See our live false-verify rate
Source: https://www.austlii.edu.au/cgi-bin/viewdoc/au/cases/cth/FWC/2025/47.html, via Damien Charlotin's public AI Hallucination Cases Database (CC0).