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Dataset · updated 20 September 2026

The Citation Failure Record

A public, source-cited record of court decisions on AI citation failures in filings, classified by failure type, so that policy can rest on evidence rather than anecdote.

The Institute's charter commits it to keep a public record of AI citation failures in court "so that bar associations, judges, and malpractice carriers can set policy on evidence rather than anecdote." This is that record. Each entry names the case, the court and the date, says what went wrong and what followed, and cites where those facts come from.

What qualifies

An entry qualifies when a court or tribunal has addressed, in a decision, a citation failure in a filing, and the decision or a published source ties the failure to the use of AI. We record only what the cited source states. Where a detail is missing, such as an exact date or the nature of the defect, the field is left empty rather than inferred. A matter is left out altogether until its case name, court and date can be read from a source.

Failure types

Each classified entry carries one failure type.

  • Fabricated authority: a cited case, quotation or citation that does not exist.
  • Misattributed or misquoted holding: a real authority presented as saying something it does not say, or attributed to the wrong court or case.
  • Real case, wrong proposition: a real, accurately quoted case cited for a proposition it does not support.
  • Bad law cited as good: authority that was reversed, overruled, superseded or otherwise no longer usable for the proposition, cited as if it were.
  • Wrong procedural stage or standard: a holding decided under a different stage, standard, burden or forum, cited for something that depended on it (see Right Law, Wrong Stage).
  • Other: a failure the source documents that none of the above describes.

Verification

Every entry cites a primary source, such as the court's order, or a published secondary source, and names the place in the Institute's corpus where the entry is documented. When a secondary source is the only basis, the entry says so, and we replace it with the order once the order has been read. Aggregate figures are quoted exactly as their sources state them, with the source's date and its own definition. The counts measure different things: a database of decisions that address AI use is not a count of fabricated citations.

A seed set, not a census

This first release is small by design. It holds only matters whose details appear in the Institute's own papers and essays, and every classified entry so far is fabricated authority. That skew is a finding about visibility, not frequency. A fabricated citation announces itself: opposing counsel cannot find the case, and the court says so in an order. A real case cited for the wrong proposition, at the wrong stage, or after it stopped being good law announces nothing, which is the argument of Good Law for What? The other failure types are in the taxonomy because the record exists to find them. Proposed entries and corrections are welcome, with the source attached.

Entries (6)

Mata v. Avianca, Inc.

S.D.N.Y. · 22 June 2023

Fabricated authority
What happened
Counsel submitted six "non-existent judicial opinions with fake quotes and citations created by the artificial intelligence tool ChatGPT," then "continued to stand by the fake opinions after judicial orders called their existence into question."
Consequence
A $5,000 sanction imposed jointly and severally on two attorneys and their firm under Rule 11 and the court's inherent power, with letters to each judge falsely identified as the author of a fabricated opinion. The court found bad faith "based upon acts of conscious avoidance and false and misleading statements to the Court."
Source
Primary: Mata v. Avianca, Inc., No. 22-cv-1461 (PKC), Opinion and Order on Sanctions, Dkt. 54 (S.D.N.Y. June 22, 2023) (Castel, J.), 678 F. Supp. 3d 443, https://storage.courtlistener.com/recap/gov.uscourts.nysd.575368/gov.uscourts.nysd.575368.54.0.pdf. Documented in Summary Judgment as the Test Case (JLA draft v2.0), Part 1 and note 12; Good Law for What? (LLJ draft), note 1; Construction vs. Verification in Citation-Bearing Legal AI, section 5.2; The Promise Fulfilled (JCLLT draft), Part 7.

Park v. Kim

2d Cir. · 2024

Fabricated authority
What happened
A reply brief contained "a citation to a non-existent case, which she admits she generated using the artificial intelligence tool ChatGPT."
Consequence
The court referred the attorney to its grievance panel, stating that citation to a non-existent case "suggests conduct that falls below the basic obligations of counsel."
Source
Primary: Park v. Kim, 91 F.4th 610 (2d Cir. 2024) (per curiam). Documented in Summary Judgment as the Test Case (JLA draft v2.0), Part 1, Part 11.1 and note 13. The draft read the opinion through a commercial database and flags its pin cites as unconfirmed against the official reporter, so none are given here.

Whiting v. City of Athens

6th Cir. · 2026

Fabricated authority
What happened
Briefs contained fabricated and misrepresented citations.
Consequence
The court fined two attorneys $15,000 each, plus fees and double costs. The essay reports the court's principle as tool-agnostic: counsel must personally read and verify every citation, however it was generated.
Source
Secondary only: Ross Brodskiy, "The Verification Layer Is a Smoke Alarm, Not a Building Code" (Medium, 20 September 2026), text and source note ("Whiting v. City of Athens (6th Cir. 2026)"); Institute library at /articles/the-verification-layer-is-a-smoke-alarm. The order itself is not yet in the Institute's corpus.

Smith v. Farwell

Mass. Super. Ct., Suffolk County · 2024

Fabricated authority
What happened
A filing relied on AI-generated fictitious cases.
Consequence
The court imposed $2,000.
Source
Secondary only: The Promise Fulfilled (JCLLT draft), Part 7, "Professional Responsibility: What Competence Now Requires"; paper page at /papers/the-promise-fulfilled. The order itself is not yet in the Institute's corpus.

Garner v. Kadince, Inc.

Utah Court of Appeals · 2025

What happened
The source lists this decision among the sanctions cases that "have focused public attention on hallucinated citations" but does not describe the specific defect in the filing, so no failure type is assigned until the opinion has been read.
Consequence
The court required the attorney to pay opposing counsel's fees, refund the client, and donate to a legal aid organization.
Source
Secondary only: The Promise Fulfilled (JCLLT draft), Part 7, citing Garner v. Kadince, Inc., 2025 UT App 80; paper page at /papers/the-promise-fulfilled. The opinion itself is not yet in the Institute's corpus.

Johnson v. Dunn

N.D. Ala. · 2025

Fabricated authority
What happened
A filing contained AI fabrications; the source gives no further detail about the filing.
Consequence
Attorney disqualification, described in the source as "the first known disqualification for AI fabrications."
Source
Secondary only: The Promise Fulfilled (JCLLT draft), Part 7; paper page at /papers/the-promise-fulfilled. The order itself is not yet in the Institute's corpus.

Aggregates reported in the literature

MeasureValueSource
Decisions in the AI Hallucination Cases database (Damien Charlotin) in which a court addressed established or alleged AI use, accessed 20 September 20262,044Summary Judgment as the Test Case (JLA draft v2.0), Part 1 and note 11: Damien Charlotin, AI Hallucination Cases database, https://www.damiencharlotin.com/hallucinations/ (accessed Sept. 20, 2026). The site displayed a last-updated date of Sept. 19, 2026, without stating that the count corresponds to that date. The compiler states that the database covers decisions in which a court addressed established or alleged AI use in more than a passing reference, excludes mere allegations and the wider universe of fabricated citations, and involves judgment calls on inclusion.
Same database: decisions worldwide in which a court or tribunal found that a party relied on hallucinated content, August 2026approximately 1,980Good Law for What? (LLJ draft), note 2: Damien Charlotin, AI Hallucination Cases (last visited Aug. 28, 2026). "The count is as of August 2026 and is updated periodically."
Same database, as described in the smoke-alarm essay (20 September 2026)passed 1,600 casesRoss Brodskiy, "The Verification Layer Is a Smoke Alarm, Not a Building Code" (Medium, 20 September 2026): "A researcher at HEC Paris keeps a public database of court decisions involving AI-hallucinated material; it passed 1,600 cases this year and the pace is climbing."
Same database: worldwide cases involving AI-fabricated material in legal filings, late 2025486 worldwide, 324 in United States courtsThe Promise Fulfilled (JCLLT draft), Part 7: "As of late 2025, Charlotin's database documents 486 worldwide cases involving AI-fabricated material in legal filings, with 324 in United States courts."
Fabricated citations in a randomized experiment with upper-level law students (Schwarcz et al., SSRN 5162111)18 fabricated citations across 768 graded tasks (127 participants): 3 in the Vincent condition, 4 in the no-AI condition, 11 in the o1-preview conditionSummary Judgment as the Test Case (JLA draft v2.0), Part 6.6 and note 43: Daniel Schwarcz, Sam Manning, Patrick Barry, David R. Cleveland, J.J. Prescott & Beverly Rich, AI-Powered Lawyering, SSRN Working Paper No. 5162111 (posted Mar. 4, 2025), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5162111. Working paper, not peer reviewed as of the date read. "Counts are reported here as counts, not as rates, because the denominators differ by condition and task type."
Hallucination on direct verifiable questions about real federal cases, four general-purpose models (Dahl, Magesh, Suzgun & Ho)at least 58 percentSummary Judgment as the Test Case (JLA draft v2.0), Part 1 and note 10: Large Legal Fictions, 16 J. Legal Analysis 64 (2024). More than 800,000 queries; abstentions counted as non-hallucinations; the authors characterize their reference-free measures as lower bounds.
Incorrect or misgrounded responses from retrieval-grounded commercial legal research tools on an adversarial 202-query set (Magesh et al.)between 17 and 33 percentSummary Judgment as the Test Case (JLA draft v2.0), Part 1 and note 9: Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools, 22 J. Empirical Legal Stud. 216 (2025). Systems queried Mar. 22 to Apr. 22, 2024, and, for one product, May 23 to 27, 2024; figures describe those product versions.