Sanction teardown · First-tier Tribunal, UK · 2026-03-16
David Jeffs v London Borough of Lewisham
What happened
In First-tier 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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False Quotes (Legal Norm)Applicant relied on an invented wording of regulation 7(5); Tribunal pointed out the Regulation's actual wording does not state the service rule the Applicant quoted.
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Fabricated (Case Law)Applicant cited a non-existent case titled 'Regent Management Ltd v Daejan Investments Ltd'; Tribunal found this case did not exist and was likely invented/adapted by AI.
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Misrepresented (Case Law)Applicant cited Daejan Investments Ltd v Benson [2013] UKSC 14 but relied on principles irrelevant to the issues; Tribunal found the case did not support Applicant's submissions as cited.
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Misrepresented (Case Law)Applicant cited Lambeth LBC v Kelly [2022] UKUT 290 (LC) for a point outside its scope; Tribunal held the case related to dispensations under s20ZA and was not relevant as relied upon.
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Misrepresented (Case Law)Applicant cited Collingwood v Carillion House Eastbourne Limited [2021] UKUT 246 (LC) but Tribunal found it concerned a different procedural issue and was not applicable to the Applicant's argument.
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
Cost-related relief refused in part because of AI misuse
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/2154/Jeffs_v._Levisham_UK_16_March_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).