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Arbuckle v. Tanner, 2026 NSCA 62

Court
N.S. C.A.
Jurisdiction
Canada
Decided
2026-08-12
AI tool
Unidentified
Outcome
Adverse Costs Order
Monetary penalty
20000 CAD

What was hallucinated

Fabricated: Exhibits & Submissions | AI appended a certified court transcriber certification page (name, NS registration number and signature of Sue Loney) to the September and October 2025 transcripts that were not certified. || Fabricated: Exhibits & Submissions | AI-produced transcripts contained material inaccuracies and 'phantom testimony' not present in the certified audio-based transcript provided by the respondent.

Details

The self-represented appellant admitted using unspecified AI tools to transcribe and assemble his appeal book. The AI-generated transcripts included material inaccuracies and, according to the appellant, appended a certified court-transcriber certificate (including name, registration number and signature) belonging to Sue Loney. The respondent discovered 39 discrepancies and the transcriber denied certifying those transcripts. The Court found the appellant knowingly filed misleading certifications and uncertified transcripts, rejected reliance on an AI excuse, dismissed the appeal for failure to perfect, and awarded indemnity costs of $20,000.

Sanction teardown · N.S. C.A., Canada · 2026-08-12

Arbuckle v. Tanner, 2026 NSCA 62

What happened

In N.S. C.A., Canada, 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 (Exhibits & Submissions)
    AI appended a certified court transcriber certification page (name, NS registration number and signature of Sue Loney) to the September and October 2025 transcripts that were not certified.
  • Fabricated (Exhibits & Submissions)
    AI-produced transcripts contained material inaccuracies and 'phantom testimony' not present in the certified audio-based transcript provided by the respondent.

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

Adverse Costs Order (monetary penalty: 20000 CAD.)

Additional detail

The self-represented appellant admitted using unspecified AI tools to transcribe and assemble his appeal book. The AI-generated transcripts included material inaccuracies and, according to the appellant, appended a certified court-transcriber certificate (including name, registration number and signature) belonging to Sue Loney. The respondent discovered 39 discrepancies and the transcriber denied certifying those transcripts. The Court found the appellant knowingly filed misleading certifications and uncertified transcripts, rejected reliance on an AI excuse, dismissed the appeal for failure to perfect, and awarded indemnity costs of $20,000.

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/2828/Arbuckle-v.-Tanner-2026-NSCA-62.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

Source: https://www.damiencharlotin.com/documents/2828/Arbuckle-v.-Tanner-2026-NSCA-62.pdf

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