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RYJZ and Commissioner of Taxation (Taxation)

Court
ART Australia
Jurisdiction
Australia
Decided
2026-02-12
AI tool
Implied
Outcome
—
Monetary penalty
None reported

What was hallucinated

Fabricated: Case Law | Applicant relied on 'Cheung v FCT [2021] AATA 3851'; Tribunal and Commissioner found no record of that case and treated it as a fabricated citation, noting possible AI use. || Fabricated: Case Law | Applicant relied on 'Dwyer v FCT [2018] AATA 456'; Tribunal and Commissioner found no record of that case and treated it as a fabricated citation, noting possible AI use.

Sanction teardown · ART Australia, Australia · 2026-02-12

RYJZ and Commissioner of Taxation (Taxation)

What happened

In ART Australia, 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)
    Applicant relied on 'Cheung v FCT [2021] AATA 3851'; Tribunal and Commissioner found no record of that case and treated it as a fabricated citation, noting possible AI use.
  • Fabricated (Case Law)
    Applicant relied on 'Dwyer v FCT [2018] AATA 456'; Tribunal and Commissioner found no record of that case and treated it as a fabricated citation, noting possible AI use.

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.damiencharlotin.com/documents/1851/RYJZ_and_Commissioner_of_Taxation_Taxation_2026_ARTA_182_12_February_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

Source: https://www.damiencharlotin.com/documents/1851/RYJZ_and_Commissioner_of_Taxation_Taxation_2026_ARTA_182_12_February_2026.pdf

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