Sanction teardown · Birmingham Employment Tribunal, UK · 2024-06-15
Dr C Mallon v Steer Energy Solutions Limited
What happened
In Birmingham Employment Tribunal, UK, 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:
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Fabricated (Case Law)The tribunal stated that the claimant’s AI-generated submissions created non-existent case law and precedent, rendering the submissions unreliable and confusing; no individual fabricated authority was identified in the judgment.
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
The claimant was ordered to pay £7,500 in costs; the AI-generated submissions were cited as contributing to unreasonable conduct and wasted costs, but no separate penalty was imposed specifically for hallucination. (monetary penalty: 1 .)
Additional detail
The claimant submitted lengthy correspondence and attachments relying on several unidentified AI generators. The tribunal found that the submissions were often highly unreliable and literally created non-existent case law and precedent, causing confusion and additional work. The court treated this approach as part of the claimant’s unreasonable conduct in the proceedings and reaffirmed a £7,500 costs order, while making no separate sanction specifically for the fabricated authorities.
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/3028/Dr_C_Mallon_v_Steer_Energy_Solutions_Ltd_-_1403759_2021_-_Recon.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).