{ "name": "Federal Court AI Orders Tracker", "url": "https://openbankruptcyproject.org/research/ai-court-tracker/", "publisher": "Open Bankruptcy Project", "license": "CC BY 4.0", "generated": "2026-04-28T15:35:15.842169+00:00", "entries": [ { "id": "mata-v-avianca-2023", "court": "U.S. District Court, Southern District of New York", "circuit": "2d Cir.", "judge": "Hon. P. Kevin Castel, U.S.D.J.", "order_type": "sanctions_order", "date_issued": "2023-06-22", "title": "Mata v. Avianca, Inc.: Opinion and Order on Sanctions", "case_citation": "Mata v. Avianca, Inc., 678 F. Supp. 3d 443 (S.D.N.Y. 2023)", "docket_no": "1:22-cv-01461", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$5,000 jointly and severally on respondents Steven A. Schwartz, Peter LoDuca, and Levidow, Levidow & Oberman, P.C., paid into Registry of the Court within 14 days; ordered to send letters to each judge falsely identified as author of fake opinions, attaching the Order, June 8, 2023 hearing transcript, and the April 25 Affirmation containing the fabricated opinion attributed to that judge.", "triggering_conduct": "Submission of a brief in opposition to defendant's motion to dismiss containing six fabricated case opinions generated by ChatGPT, Varghese v. China Southern Airlines, Shaboon v. EgyptAir, Petersen v. Iran Air, Martinez v. Delta Air Lines, Estate of Durden v. KLM Royal Dutch Airlines, and Miller v. United Airlines, none of which exist. After defense counsel and the court flagged the citations as undiscoverable, plaintiff's counsel produced ChatGPT-generated 'copies' of the opinions to substantiate them, doubling down on the fabrications.", "holding_summary": "Court held that respondents acted with subjective bad faith sufficient for sanctions under Fed. R. Civ. P. 11. Use of generative AI tools does not relieve attorneys of the independent duty to verify the authenticity of cited authority before submission.", "source_url": "https://law.justia.com/cases/federal/district-courts/new-york/nysdce/1:2022cv01461/575368/54/", "source_type": "published_reporter", "verification_status": "primary_source_verified", "tags": "first_major_sanction, hallucinated_citations, rule_11, attorney, civil", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, personal_injury, aviation", "bankruptcy_relevance": "secondary", "framework_tag": "subjective_bad_faith_rule_11", "internal_corpus_use": "filing_verification, ust_review_threshold" }, { "id": "starr-ndtx-standing-order-2023", "court": "U.S. District Court, Northern District of Texas", "circuit": "5th Cir.", "judge": "Hon. Brantley Starr, U.S.D.J.", "order_type": "standing_order", "date_issued": "2023-05-30", "title": "Mandatory Certification Regarding Generative Artificial Intelligence", "case_citation": "n/a (judge-specific standing requirement)", "docket_no": "n/a", "disclosure_required": "true", "disclosure_scope": "Every attorney appearing before the court must file a certificate attesting either (1) no portion of the filing was drafted by generative AI, or (2) any AI-drafted language has been checked for accuracy by a human being using print reporters or traditional legal databases. Coverage extends to quotations, citations, paraphrased assertions, and legal analysis.", "sanctions_imposed": null, "triggering_conduct": "Issued in response to growing concern over generative-AI tools producing fabricated citations and authorities. Cited Mata v. Avianca dynamics as motivating example.", "holding_summary": "Standing order requires AI-disclosure certification on every filing; non-compliant filings will be struck. Attorneys remain responsible under Rule 11 for the contents of any filing they sign regardless of AI involvement.", "source_url": "https://www.txnd.uscourts.gov/judge/judge-brantley-starr", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "first_standing_order, disclosure_requirement, certification, attorney, pro_se", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "all_civil_in_court", "bankruptcy_relevance": "secondary", "framework_tag": "mandatory_certification", "internal_corpus_use": "disclosure_certification, model_for_w_d_mo_d_kan" }, { "id": "park-v-kim-2dcir-2024", "court": "U.S. Court of Appeals for the Second Circuit", "circuit": "2d Cir.", "judge": "Panel (per curiam disciplinary referral)", "order_type": "disciplinary_referral", "date_issued": "2024-01-30", "title": "Park v. Kim: Order Referring Counsel for Disciplinary Proceedings", "case_citation": "Park v. Kim, 91 F.4th 610 (2d Cir. 2024)", "docket_no": "22-2057", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Referral to Court's Grievance Panel for further investigation and consideration of referral to admission committee.", "triggering_conduct": "Attorney Jae S. Lee cited two fabricated cases in appellate brief, including Bourguignon v. Coordinated Behavioral Health Services, which did not exist. Lee acknowledged she 'encountered difficulties in locating a relevant case' and turned to ChatGPT, which generated the citation.", "holding_summary": "Citation to a nonexistent case suggests conduct that falls below the basic obligations of counsel. Use of generative AI tools does not excuse an attorney from separately ensuring that submissions to the court are accurate or legally tenable.", "source_url": "https://caselaw.findlaw.com/court/us-2nd-circuit/115760381.html", "source_type": "published_reporter", "verification_status": "primary_source_verified", "tags": "circuit_court, hallucinated_citations, disciplinary_referral, attorney, civil", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, medical_malpractice", "bankruptcy_relevance": "secondary", "framework_tag": "circuit_disciplinary_referral", "internal_corpus_use": "circuit_court_filings, disciplinary_threshold" }, { "id": "couvrette-v-wisnovsky-2025", "court": "U.S. District Court, District of Oregon", "circuit": "9th Cir.", "judge": "[district judge, pending PACER/CourtListener docket pull]", "order_type": "sanctions_order", "date_issued": "2025-12 (exact day pending docket pull)", "title": "Couvrette v. Wisnovsky: Order on Motion for Sanctions and Dismissal", "case_citation": "[pending docket pull]", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Approximately $110,000 total: $80,000 in opposing-side attorney fees plus $15,000 in fines against lead attorney Stephen Brigandi (San Diego, pro hac vice for plaintiff); approximately $14,000 in sanctions against local counsel Timothy Murphy (Oregon). Plaintiff's claims dismissed. Matter referred to Oregon State Bar.", "triggering_conduct": "Across three separate briefs on cross-motions for summary judgment over a five-month period (January-May 2025), plaintiff's briefing included 15 AI-generated fake case citations and eight fabricated quotations. Pattern escalated: Jan 2025 = 2 fake citations; April 2025 = 7 fictitious citations; May 2025 = 16 invented references. Local counsel was sanctioned alongside lead counsel for failure to vet filings he co-signed.", "holding_summary": "Court dismissed plaintiff's claims, imposed approximately $110,000 in monetary sanctions and fee-shifting, and referred the matter to the Oregon State Bar after finding attorneys repeatedly submitted briefs containing AI-fabricated authorities. Local counsel held jointly accountable for AI-fabricated content in co-signed filings, even where lead counsel drafted the briefs.", "source_url": "https://www.abajournal.com/news/article/oregon-federal-judge-hands-down-110000-penalty-for-ai-errors", "source_type": "secondary_aggregator (ABA Journal); primary docket pull pending", "verification_status": "facts_corroborated_multi_source, primary docket pull pending", "tags": "9th_circuit, hallucinated_citations, dismissal, attorney, civil, large_sanction, local_counsel_liability, escalation_pattern, bar_referral", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, inheritance, business", "bankruptcy_relevance": "secondary", "framework_tag": "local_counsel_liability", "internal_corpus_use": "co_signer_liability, multi_attorney_filings" }, { "id": "whiting-v-city-of-athens-ca6-2026", "court": "U.S. Court of Appeals for the Sixth Circuit", "circuit": "6th Cir.", "judge": "[panel, pending opinion pull]", "order_type": "sanctions_order", "date_issued": "2026-03 (per JDJournal coverage 2026-03-16; exact day pending opinion pull)", "title": "Whiting v. City of Athens: Sanctions Order", "case_citation": "Whiting v. City of Athens, 2026 WL 710568 (6th Cir. 2026)", "docket_no": "Case Nos. 24-5918/5919, 25-5424", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$15,000 each in punitive fines to court registry against attorneys Van R. Irion and Russ Egli ($30,000 total, reportedly the largest federal appellate AI-related sanction as of March 2026), plus joint responsibility for appellees' full attorney fees on appeal and double costs.", "triggering_conduct": "Counsel cited 24+ fake citations across appellate briefing, including citations whose Federal Reporter references actually corresponded to two unrelated 10th Circuit cases (one on unfair competition, one on a guilty plea), neither addressing the propositions cited. Citations also lacked the language quoted in the brief and failed to support the propositions advanced. Both attorneys had prior discipline for lack of candor to the tribunal; misconduct spanned three cases.", "holding_summary": "Sixth Circuit imposed $15,000-per-attorney punitive fines plus fee-shifting and double costs after finding fabricated citations across multiple briefs. Court explicitly justified the elevated sanction amount on the ground that 'smaller fines have plainly been inadequate, as is evidenced by the continuous stream of cases raising the same problems,' signaling escalation in appellate-level AI-hallucination sanctions.", "source_url": "https://www.lawnext.com/2026/03/sixth-circuit-slaps-steep-sanctions-on-two-lawyers-for-fake-citations-and-misrepresentations-in-appellate-briefs.html", "source_type": "secondary_aggregator (LawSites); primary opinion pull pending", "verification_status": "facts_corroborated_multi_source, primary opinion pull pending", "tags": "circuit_court, hallucinated_citations, large_sanction, repeat_misconduct, attorney, escalation_signal", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, civil_rights", "bankruptcy_relevance": "secondary", "framework_tag": "appellate_escalation_signal", "internal_corpus_use": "appellate_filings, repeat_misconduct_escalation" }, { "id": "watson-or-coa-2025", "court": "Oregon Court of Appeals (state intermediate appellate)", "circuit": "n/a (state court, included as scope expansion because the per-infraction rate framework has been adopted in subsequent federal orders)", "judge": "[panel, pending opinion pull]", "order_type": "sanctions_order", "date_issued": "2025-12 (exact day pending opinion pull)", "title": "Sanctions Order Against Gabriel A. Watson", "case_citation": "[pending opinion pull]", "docket_no": "[pending opinion pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$2,000 total. Court established a per-infraction rate framework: $500 per fabricated citation \u00d7 2 citations = $1,000; plus $1,000 per fabricated quotation \u00d7 1 quotation = $1,000.", "triggering_conduct": "Portland attorney Gabriel A. Watson filed brief citing two nonexistent cases and one fabricated quotation. Watson initially attempted to attribute the error to his assistant having mistakenly filed a 'draft/placeholder' brief; later acknowledged and apologized for the AI-generated errors. Court rejected the explanation as not constituting a 'clear explanation' of how the errors occurred.", "holding_summary": "Oregon Court of Appeals characterized the proliferation of AI-generated sketchy legal documents as 'a very grave situation' and established a per-infraction sanctions framework: $500 per fabricated citation, $1,000 per fabricated quotation. The framework has been cited in subsequent federal sanctions orders adopting analogous per-infraction calculation.", "source_url": "https://www.chronline.com/stories/very-grave-situation-oregon-court-slaps-attorney-with-2000-fine-for-ai-errors,392197", "source_type": "secondary_aggregator (Daily Chronicle / NW Sidebar); primary opinion pull pending", "verification_status": "facts_corroborated_multi_source, primary opinion pull pending", "tags": "state_court, oregon, hallucinated_citations, per_infraction_rate, framework_setter, attorney", "category": "judicial", "branch": "judicial", "jurisdiction_level": "state", "subject_matter": "civil", "bankruptcy_relevance": "secondary", "framework_tag": "per_infraction_rate", "internal_corpus_use": "sanctions_calibration, citation_verification" }, { "id": "vaden-cit-standing-order-2023", "court": "U.S. Court of International Trade", "circuit": "Federal Circuit (appeals from CIT)", "judge": "Hon. Stephen Alexander Vaden, U.S. Court of International Trade", "order_type": "standing_order", "date_issued": "2023-06-08", "title": "Order on Artificial Intelligence (cases assigned to Judge Vaden)", "case_citation": "n/a (judge-specific standing order)", "docket_no": "n/a", "disclosure_required": "true", "disclosure_scope": "Two-prong requirement for any submission containing text drafted with the assistance of a generative AI program based on natural-language prompts (including but not limited to ChatGPT and Google Bard): (1) DISCLOSURE NOTICE, must identify the program used and the specific portions of text that were AI-drafted; (2) CONFIDENTIALITY CERTIFICATION, must certify that use of the program has not resulted in disclosure of any confidential or business-proprietary information to any unauthorized party.", "sanctions_imposed": null, "triggering_conduct": "Issued in response to growing concern over generative-AI tools producing fabricated citations AND, distinctly from other early standing orders, the inadvertent disclosure of business-proprietary information through AI prompt inputs (e.g., where confidential trade data is included in prompts and effectively transmitted to third-party AI providers).", "holding_summary": "Standing order pioneers the **confidentiality / business-proprietary disclosure-risk framework** for judicial AI governance. Distinct from Starr (accuracy/Rule 11 framework) and Baylson (broad-scope verification framework). Vaden's framework recognizes a second category of AI-use risk beyond hallucination: that prompt inputs may transmit otherwise-protected litigation information to third-party AI providers.", "source_url": "https://www.cit.uscourts.gov/sites/cit/files/Order%20on%20Artificial%20Intelligence.pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "specialty_court, court_of_international_trade, standing_order, disclosure_requirement, certification, confidentiality_framework, business_proprietary_risk, framework_setter", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "international_trade, customs", "bankruptcy_relevance": "none", "framework_tag": "confidentiality_disclosure_risk", "internal_corpus_use": "case_strategy_data_handling, ai_prompt_confidentiality" }, { "id": "fuentes-ndil-standing-order-2023", "court": "U.S. District Court, Northern District of Illinois", "circuit": "7th Cir.", "judge": "Hon. Gabriel A. Fuentes, U.S. Magistrate Judge", "order_type": "standing_order", "date_issued": "2023-05-31 (revised effective date)", "title": "Standing Order for Civil Cases Before Judge Fuentes (revised to add AI section)", "case_citation": "n/a (judge-specific standing order)", "docket_no": "n/a", "disclosure_required": "true", "disclosure_scope": "Any party using any generative AI tool to conduct legal research or to draft documents for filing must DISCLOSE in the filing that AI was used. Disclosure must include the specific AI tool and the manner in which it was used. NO separate certification regime is created, order anchors enforcement in existing Rule 11.", "sanctions_imposed": "null (enforcement via Rule 11 sanctions for noncompliance with the underlying duty to ensure citations exist and arguments are warranted)", "triggering_conduct": "Issued during the May-June 2023 wave of judicial response to AI-hallucination filings. Fuentes' approach distinct from same-period orders by Starr (N.D. Tex.) and Baylson (E.D. Pa.) in declining to create a new certification regime.", "holding_summary": "Standing order establishes the **Rule 11-grounded framework** for judicial AI governance: rather than creating a new AI-specific certification regime, the order reaffirms that existing Rule 11 obligations apply to AI-assisted filings. Order language: 'Just as the Court did before the advent of AI as a tool for legal research and drafting, the Court will continue to presume that the Rule 11 certification is a representation by filers, as living, breathing, thinking human beings, that they themselves have read and analyzed all cited authorities to ensure that such authorities actually exist...' Holds explicitly that 'mere reliance on an AI tool' does NOT constitute reasonable inquiry under Rule 11.", "source_url": "https://www.ilnd.uscourts.gov/_assets/_documents/_forms/_judges/Fuentes/Standing%20Order%20For%20Civil%20Cases%20Before%20Judge%20Fuentes%20rev%27d%205-31-23%20(002).pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "7th_circuit, standing_order, disclosure_requirement, no_certification, rule_11_framework, framework_setter, magistrate_judge", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "all_civil_in_court", "bankruptcy_relevance": "secondary", "framework_tag": "rule_11_grounded_no_new_certification", "internal_corpus_use": "rule_11_compliance, no_certificate_jurisdictions" }, { "id": "baylson-edpa-standing-order-2023", "court": "U.S. District Court, Eastern District of Pennsylvania", "circuit": "3d Cir.", "judge": "Hon. Michael M. Baylson, U.S.D.J. (Senior Judge)", "order_type": "standing_order", "date_issued": "2023-06-06", "title": "Standing Order: In Re: Artificial Intelligence (\"AI\") in Cases Assigned to Judge Baylson", "case_citation": "n/a (judge-specific standing order)", "docket_no": "n/a", "disclosure_required": "true", "disclosure_scope": "If any attorney for a party, or a pro se party, has used Artificial Intelligence, they MUST disclose that AI has been used in any way in the preparation of the filing, AND CERTIFY that each and every citation to the law or the record in the paper has been verified as accurate. Coverage uses the umbrella phrase 'AI' to describe a variety of advanced technologies, NOT limited to generative AI.", "sanctions_imposed": null, "triggering_conduct": "Issued in same May-June 2023 wave alongside Starr, Vaden, and Fuentes orders. Baylson's order distinguished by deliberately broad scope.", "holding_summary": "Standing order pioneers the **broadest-scope framework** for judicial AI governance: requirement applies to *any* AI use in filing preparation, generative or otherwise, with mandatory accuracy verification of every citation to law or record. Among the early-wave standing orders, Baylson's is the most expansive in coverage, characterized by commentators as 'the most unusual of these early orders' for sweeping all AI under disclosure and certification obligations rather than carving the requirement to generative tools alone.", "source_url": "https://www.paed.uscourts.gov/sites/paed/files/documents/procedures/Standing%20Order%20Re%20Artificial%20Intelligence%206.6.pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "3d_circuit, standing_order, disclosure_requirement, certification, broad_scope_framework, all_AI, senior_judge, framework_setter", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "all_civil_in_court", "bankruptcy_relevance": "secondary", "framework_tag": "broadest_scope_any_ai", "internal_corpus_use": "verification_per_citation, all_ai_disclosure" }, { "id": "rajan-djn-2026", "court": "U.S. District Court, District of New Jersey", "circuit": "3d Cir.", "judge": "Hon. Kai N. Scott, U.S.D.J.", "order_type": "sanctions_order", "date_issued": "2026-04 (week of Inquirer report 2026-04-27; exact day pending docket pull)", "title": "Sanctions Order Against Raja Rajan (Second Instance)", "case_citation": "[pending docket pull]", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$5,000 (April 2026, second sanction against Rajan for AI-hallucinated brief content). Prior sanction of $2,500 imposed for first instance. Court warned that a third instance would result in referral to the Pennsylvania disciplinary board (Rajan is licensed in PA, not NJ; appeared in NJ federal court on a non-litigation-practice basis to assist his brother).", "triggering_conduct": "Cherry Hill, NJ attorney Raja Rajan filed brief containing AI-hallucinated citations in federal civil matter. Second instance of same conduct after prior $2,500 sanction. Rajan stated he had not litigated cases in years and picked up the matter to assist his brother and former business partner who was accused of deceiving an investor for a million-dollar loan.", "holding_summary": "Court imposed escalating monetary sanction ($5,000, doubled from prior $2,500) against attorney for repeat filing of AI-hallucinated briefs and warned that a third instance would trigger referral to the attorney's licensing-state disciplinary board. Notable for the cross-jurisdictional disciplinary escalation framework: federal court in non-licensing state imposes monetary sanction and signals referral to the state where the attorney is admitted.", "source_url": "https://www.inquirer.com/news/new-jersey/ai-legal-research-court-filings-halluciations-sanctions-court-20260427.html", "source_type": "secondary_aggregator (Philadelphia Inquirer / Bloomberg Law); primary docket pull pending", "verification_status": "facts_corroborated_multi_source, primary docket pull pending", "tags": "3d_circuit, hallucinated_citations, repeat_offender, escalation, cross_jurisdiction_referral, attorney, low_practice_volume", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, fraud", "bankruptcy_relevance": "secondary", "framework_tag": "cross_jurisdictional_referral", "internal_corpus_use": "repeat_offender_escalation, cross_state_disciplinary" }, { "id": "crabill-co-opdj-2023", "court": "Colorado Office of Presiding Disciplinary Judge", "circuit": "n/a (state attorney discipline)", "judge": "Hon. Bryon M. Large, Presiding Disciplinary Judge", "order_type": "disciplinary_referral", "date_issued": "2023-11-22", "title": "People v. Zachariah C. Crabill: Stipulation to Discipline", "case_citation": "People v. Crabill, 23PDJ067 (Colo. OPDJ Nov. 22, 2023)", "docket_no": "23PDJ067", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Suspension of one year and one day, with 90 days actively served and the remainder stayed upon successful completion of a two-year probation period. Violations: Colorado Rules of Professional Conduct 1.1 (competence), 1.3 (diligence), 3.3(a)(1) (candor toward tribunals), 8.4(c) (dishonesty / misrepresentation).", "triggering_conduct": "Attorney drafted and filed a motion to set aside judgment in a civil case using case law obtained from ChatGPT, without reading the cases or verifying the citations were accurate. Before the hearing, attorney discovered the cited cases were either incorrect or fictitious. After the court flagged the citations, attorney made false statements to the judge attributing the errors to a legal intern, who in fact had no involvement.", "holding_summary": "Disciplinary court approved stipulated suspension establishing the state-bar disciplinary framework for AI-driven citation hallucinations: filing AI-generated authorities without verification implicates competence and diligence rules; subsequent dishonesty about the source of the errors implicates candor and misrepresentation rules. The compounding-misconduct pattern (AI hallucination plus deception about origin) is what drove the actual-suspension component beyond what citation-only conduct typically merits.", "source_url": "https://www.coloradolegalregulation.com/wp-content/uploads/PDJ/Decisions/Crabill,%20Stipulation%20to%20Discipline,%2023PDJ067,%2011-22-23.pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "state_bar_discipline, hallucinated_citations, suspension, attorney, candor_violation, framework_setter, compounding_misconduct", "category": "disciplinary", "branch": "judicial", "jurisdiction_level": "state", "subject_matter": "state_bar_discipline", "bankruptcy_relevance": "secondary", "framework_tag": "compounding_misconduct", "internal_corpus_use": "candor_violation_compounding, ai_plus_dishonesty_pattern" }, { "id": "cohen-sdny-furman-2024", "court": "U.S. District Court, Southern District of New York", "circuit": "2d Cir.", "judge": "Hon. Jesse M. Furman, U.S.D.J.", "order_type": "opinion", "date_issued": "2024-03-20", "title": "United States v. Cohen: Order Declining Sanctions on AI-Hallucinated Citations", "case_citation": "United States v. Cohen, S.D.N.Y. (Furman J., Mar. 2024)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "NONE imposed. Court declined to sanction either Michael Cohen (former Trump attorney; pro se litigant in his post-prison supervision matter) or his attorney David M. Schwartz.", "triggering_conduct": "Cohen included three fabricated case citations in a brief seeking early termination of supervised release. Citations were generated by Google Bard, which Cohen reportedly believed was a 'super-charged search engine' rather than a generative-text service. Cohen forwarded the citations to Schwartz, who incorporated them into the filing without independent verification.", "holding_summary": "Court found the false citations 'embarrassing and certainly negligent' but declined to impose sanctions, finding neither Cohen nor Schwartz acted in 'bad faith.' Holding establishes the GOOD-FAITH FRAMEWORK for AI-hallucination cases: where the filer demonstrates a genuine misunderstanding of the AI tool's capabilities (rather than reckless disregard), Rule 11 sanctions may not lie. This is a doctrinal counterpoint to Mata v. Avianca's subjective-bad-faith finding on similar facts; together they bracket the scienter spectrum for AI-citation misconduct.", "source_url": "https://www.courthousenews.com/judge-wont-sanction-michael-cohen-over-ai-generated-fake-legal-cases/", "source_type": "secondary_aggregator (Courthouse News / ABA Journal); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "2d_circuit, hallucinated_citations, no_sanctions, good_faith_framework, scienter, framework_setter, criminal_supervised_release", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "criminal, supervised_release", "bankruptcy_relevance": "secondary", "framework_tag": "good_faith_no_sanctions", "internal_corpus_use": "good_faith_defense_threshold, scienter_distinction" }, { "id": "noland-cal-coa-2025", "court": "California Court of Appeal", "circuit": "n/a (state intermediate appellate)", "judge": "[panel, pending opinion pull]", "order_type": "sanctions_order", "date_issued": "2025-09 (exact day pending opinion pull)", "title": "Noland v. Land of the Free, L.P.: Order on AI-Fabricated Citations", "case_citation": "Noland v. Land of the Free, L.P. (Cal. Ct. App. Sept. 2025) (first published state appellate opinion on AI-hallucinated citations)", "docket_no": "[pending opinion pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$10,000 sanction against appellant's counsel. Court declined to award attorneys' fees, costs, or sanctions payable to respondent because respondent's counsel failed to alert the court to the fabricated citations and appeared unaware of them until the court issued an order to show cause.", "triggering_conduct": "Appellant's counsel filed two appellate briefs replete with fabricated quotations and citations generated by AI tools.", "holding_summary": "California's first published appellate opinion on AI-fabricated citations. Establishes two distinct doctrines: (1) the $10,000 monetary-sanction baseline for state appellate AI-citation misconduct, consistent with the Watson per-infraction-rate framework but as a flat amount; and (2) the FAIL-TO-DETECT-OPPOSING-AI doctrine, holding that opposing counsel who fails to identify and report an adversary's AI-fabricated citations forfeits otherwise-available attorneys' fee awards. The latter is a novel duty-of-vigilance framework expanding the AI-detection obligation beyond one's own filings to opposing-counsel filings.", "source_url": "https://www.mcguirewoods.com/client-resources/alerts/2025/9/california-appellate-court-issues-10k-sanctions-in-states-first-published-opinion-on-ai-hallucinated-case-citations/", "source_type": "secondary_aggregator (McGuireWoods alert / LawSites / ABA Journal); primary opinion pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "state_court, california, hallucinated_citations, framework_setter, fail_to_detect_doctrine, first_published_opinion, duty_of_vigilance, attorney_fees_forfeiture", "category": "judicial", "branch": "judicial", "jurisdiction_level": "state", "subject_matter": "civil", "bankruptcy_relevance": "secondary", "framework_tag": "fail_to_detect_opposing_ai", "internal_corpus_use": "duty_of_vigilance, opposing_counsel_review" }, { "id": "fivehouse-v-us-ednc-2025", "court": "U.S. District Court, Eastern District of North Carolina", "circuit": "4th Cir.", "judge": "Hon. Robert T. Numbers II, U.S. Magistrate Judge", "order_type": "sanctions_order", "date_issued": "2025-12 (show-cause order; final disposition pending)", "title": "Fivehouse v. United States: Show-Cause Order on AUSA AI-Fabricated Citations", "case_citation": "Fivehouse v. United States (E.D.N.C. 2025) (TRICARE for Life GLP-1 coverage challenge)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Show-cause hearing held in Raleigh; final disposition pending. Court signaled that monetary sanctions, suspension from the court, and contempt remain available remedies; expressed it was heartened by remedial steps the U.S. Attorney's Office is reportedly taking.", "triggering_conduct": "Assistant U.S. Attorney Rudy Renfer signed and filed a brief on behalf of the United States that contained fabricated quotations, misstated case law holdings, and at least two invented quotations attributed to the Code of Federal Regulations. At the show-cause hearing, Renfer stated that after accidentally overwriting a prior draft, he felt panicked and had AI rewrite the brief, then filed it believing he had reviewed it. Pro se plaintiff Derence Fivehouse, a retired Air Force colonel and former staff judge advocate, identified the fabrications by reading the cited authorities and finding the quoted language did not appear there.", "holding_summary": "First high-profile federal-prosecutor AI-hallucination sanctions matter, with a Department of Justice attorney as the sanctioned actor. Establishes the GOVERNMENT-ATTORNEY FRAMEWORK: federal prosecutors face the same Rule 11 and candor-toward-tribunal duties as private counsel when filing AI-assisted briefs, and may be subject to monetary sanctions, court suspension, or contempt for AI-fabricated authorities. Notable additional pattern: pro se litigant, here an experienced military lawyer, detected the fabrications, paralleling the broader AI-detection-by-pro-se phenomenon documented elsewhere.", "source_url": "https://news.bloomberglaw.com/us-law-week/federal-prosecutor-used-fabricated-quotes-false-cites-in-filing", "source_type": "secondary_aggregator (Bloomberg Law / FindLaw); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "4th_circuit, federal_prosecutor, government_attorney, hallucinated_citations, show_cause, framework_setter, pro_se_detector, doj", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, administrative_law, military_benefits", "bankruptcy_relevance": "secondary", "framework_tag": "government_attorney_no_immunity", "internal_corpus_use": "ust_government_attorney_pattern, miller_doj_posture, pro_se_detector_role" }, { "id": "in-re-martin-ndil-bkrtcy-2025", "court": "U.S. Bankruptcy Court, Northern District of Illinois", "circuit": "7th Cir.", "judge": "[bankruptcy judge, pending docket pull]", "order_type": "sanctions_order", "date_issued": "2025 (exact date pending docket pull)", "title": "In re Martin: Order Imposing Sanctions on Debtor's Counsel for AI-Hallucinated Citations", "case_citation": "In re Martin, 670 B.R. 636 (Bankr. N.D. Ill. 2025) (debtor Marla Martin's 8th Chapter 13 filing)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$5,500 monetary sanction, jointly and severally on attorney Thomas E. Nield and The Semrad Law Firm. Required attendance by Mr. Nield and one additional senior attorney at a National Conference of Bankruptcy Judges plenary session on AI.", "triggering_conduct": "In a brief filed in debtor Marla Martin's eighth Chapter 13 filing (September 2024), debtor's counsel cited at least four cases for propositions that did not exist and quoted statements that were not in the underlying decisions. Attorney Thomas E. Nield admitted he had used ChatGPT to generate portions of the legal argument and citations without verifying the existence or substance of the cited cases.", "holding_summary": "First published bankruptcy-court opinion sanctioning attorney AI misuse (per ABI characterization). Establishes the BANKRUPTCY-COURT FRAMEWORK for AI-hallucinated citations under Bankruptcy Rule 9011 (the bankruptcy-court analog to Fed. R. Civ. P. 11). Court emphasized that 'at this point in time, in 2025, the risk of AI hallucinations is (and should be) widely known in the profession,' implicitly raising the duty-of-verification floor for bankruptcy practitioners. Notable additional pattern: sanctions imposed on a high-volume consumer-bankruptcy law firm (Semrad), connecting AI-misconduct sanctions to the bankruptcy mill operating model.", "source_url": "https://www.duanemorris.com/articles/bankruptcy_court_issues_first_published_opinion_limits_use_ai_1125.html", "source_type": "secondary_aggregator (Duane Morris LLP / ABI / Bloomberg Law); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "7th_circuit, bankruptcy_court, hallucinated_citations, semrad_law_firm, bankruptcy_mill, rule_9011, framework_setter, first_bankruptcy_ai_opinion, repeat_filer_chapter_13", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "bankruptcy, chapter_13", "bankruptcy_relevance": "primary", "framework_tag": "bankruptcy_rule_9011_ai_duty", "internal_corpus_use": "bankruptcy_mill_pattern, semrad_law_firm_specific, bankruptcy_filing_verification, rule_9011_compliance" }, { "id": "in-re-jackson-hospital-mdal-bkrtcy-2025", "court": "U.S. Bankruptcy Court, Middle District of Alabama", "circuit": "11th Cir.", "judge": "[bankruptcy judge, pending docket pull]", "order_type": "sanctions_order", "date_issued": "2025 (exact date pending docket pull)", "title": "In re Jackson Hospital: Public Reprimand and Fee Award for AI-Hallucinated Citations", "case_citation": "In re Jackson Hospital (Bankr. M.D. Ala. 2025)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Gordon Rees Scully Mansukhani LLP paid $55,721.20 in fees sought in the Motions for Sanctions, without contesting a hearing. Senior counsel publicly reprimanded by the bankruptcy court. (Notable: the firm is among the 100 largest American law firms by Bloomberg Law's accounting.)", "triggering_conduct": "Senior counsel at Gordon Rees Scully Mansukhani filed briefs containing citations that did not stand for the propositions cited, did not contain the quotes attributed to them, or did not exist at all. A supplemental brief 'obdurately clung' to prior positions and 'continued to miscite authorities,' compounding the misconduct.", "holding_summary": "Establishes the BIGLAW BANKRUPTCY-PRACTICE FRAMEWORK: large law firms practicing in bankruptcy court face the same Rule 9011 duties as solo practitioners and small firms, and pre-paying sanctions to avoid a hearing does not insulate counsel from public reprimand. The supplemental-brief 'obdurately clung' language signals an additional doctrinal element: failure to retract or correct after notice may itself constitute compounding misconduct, paralleling the Crabill compounding-misconduct framework.", "source_url": "https://news.bloomberglaw.com/bankruptcy-law/bankruptcy-judge-reprimands-ex-gordon-rees-lawyer-for-ai-citations", "source_type": "secondary_aggregator (Bloomberg Law / Reason.com); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "11th_circuit, bankruptcy_court, hallucinated_citations, gordon_rees, biglaw, public_reprimand, rule_9011, framework_setter, supplemental_brief_doubling_down, compounding_misconduct", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "bankruptcy, biglaw_practice", "bankruptcy_relevance": "primary", "framework_tag": "biglaw_rule_9011_no_insulation", "internal_corpus_use": "bankruptcy_filing_verification, biglaw_responder_pattern, supplemental_brief_correction_duty" }, { "id": "solis-kenosha-county-wi-2026", "court": "Kenosha County Circuit Court (Wisconsin)", "circuit": "n/a (state trial court)", "judge": "Hon. David Hughes, Kenosha County Circuit Court Judge", "order_type": "sanctions_order", "date_issued": "2026-02-06", "title": "Sanctions Order Against District Attorney Xavier Solis for AI-Hallucinated Citations and Failure to Disclose AI Use", "case_citation": "(State criminal prosecution against defendants Christain Garrett and Cornelius Garrett, Kenosha County Cir. Ct. Feb. 2026)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Sanctions imposed against District Attorney Xavier Solis for undisclosed AI use and false citations. Court DISMISSED ALL 74 CRIMINAL CHARGES against defendants Christain Garrett and Cornelius Garrett, without prejudice (charges may be refiled).", "triggering_conduct": "Defense attorneys identified that the DA's reply brief in a burglary prosecution 'appears to be riddled with what are called AI hallucinations, including bogus, AI-generated case citations.' One citation was related to construction contract disputes in Nebraska (irrelevant to a Wisconsin burglary case); another was described as 'purely imaginary.' DA Solis did not disclose the use of AI in the filing.", "holding_summary": "First documented case of CHARGES DISMISSED as a remedy for prosecutor AI-hallucination misconduct. Establishes the CRIMINAL-PROSECUTION FRAMEWORK: undisclosed AI use plus fabricated citations in a state criminal case can result in dismissal of charges (without prejudice to refiling), not merely monetary sanctions. Significant in pairing with the Renfer/Fivehouse federal AUSA case as a parallel signal that government attorneys, including elected prosecutors, are not insulated from AI-hallucination consequences and that consequences can extend to underlying case dispositions, not just attorney discipline.", "source_url": "https://wislawjournal.com/2026/02/09/judge-sanctions-kenosha-da-for-ai-use-in-court-filing/", "source_type": "secondary_aggregator (Wisconsin Law Journal / Reason.com / Fox6 / WPR); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "state_court, wisconsin, criminal_prosecution, prosecutor_misconduct, hallucinated_citations, undisclosed_ai_use, charges_dismissed, framework_setter, government_attorney", "category": "judicial", "branch": "judicial", "jurisdiction_level": "state", "subject_matter": "criminal, state_prosecution", "bankruptcy_relevance": "none", "framework_tag": "criminal_dismissal_remedy_undisclosed_ai", "internal_corpus_use": "government_attorney_pattern, miller_doj_posture, undisclosed_ai_use_doctrine" }, { "id": "ramirez-sdind-erisa-2025", "court": "U.S. District Court, Southern District of Indiana", "circuit": "7th Cir.", "judge": "Hon. Mark J. Dinsmore, U.S. Magistrate Judge", "order_type": "sanctions_order", "date_issued": "2025 (recommendation; final disposition pending)", "title": "Recommended Sanctions Against Attorney Rafael Ramirez for AI-Hallucinated Citations in ERISA Briefs", "case_citation": "(ERISA matter, S.D. Ind. 2025)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Magistrate Judge Dinsmore recommended a $15,000 personal sanction against attorney Rafael Ramirez of Rio Hondo, Texas, for filing three separate briefs containing AI-generated fake citations in violation of Federal Rule of Civil Procedure 11.", "triggering_conduct": "Three separate briefs filed in an Indiana ERISA matter, each containing AI-generated fabricated citations. The repeated-filing pattern across three briefs indicated a sustained Rule 11 violation rather than an isolated lapse.", "holding_summary": "Recommendation establishes the REPEATED-INSTANCE-WITHIN-CASE FRAMEWORK for Rule 11 sanctions: where AI-fabricated citations appear in multiple briefs across the same matter, the appropriate sanction scales from per-citation rates toward a substantial flat amount reflecting the sustained nature of the misconduct. Distinguishes from single-brief cases (Watson at $2,000, Mata at $5,000) by treating the pattern itself as an aggravator, in line with the Whiting cross-case escalation framework but applied within a single case.", "source_url": "https://news.bloomberglaw.com/litigation/lawyer-sanctioned-over-ai-hallucinated-case-cites-quotations", "source_type": "secondary_aggregator (Bloomberg Law); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "7th_circuit, sdind, erisa, hallucinated_citations, rule_11, repeated_instance_within_case, magistrate_recommendation, framework_setter, attorney", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, erisa, employee_benefits", "bankruptcy_relevance": "secondary", "framework_tag": "repeated_instance_within_case_aggravator", "internal_corpus_use": "multiple_filing_pattern_risk, rule_11_repeated_misconduct" }, { "id": "monk-edtex-goodyear-2024", "court": "U.S. District Court, Eastern District of Texas", "circuit": "5th Cir.", "judge": "Hon. Marcia Crone, U.S.D.J.", "order_type": "sanctions_order", "date_issued": "2024-11-25 (per JDJournal coverage; exact day pending docket pull)", "title": "Gauthier v. Goodyear Tire & Rubber Co.: Sanctions Order on Plaintiff's Counsel for AI-Hallucinated Citations", "case_citation": "Gauthier v. Goodyear Tire & Rubber Co., No. 1:23-CV-00281 (E.D. Tex. 2024)", "docket_no": "1:23-CV-00281", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "$2,000 fine against plaintiff's lawyer Brandon Monk. Court additionally required Monk to attend a course on generative AI in the legal field as a condition of the sanctions order.", "triggering_conduct": "Plaintiff's counsel Brandon Monk filed a brief in a wrongful-termination matter against Goodyear Tire & Rubber Co. that contained AI-generated fabricated citations.", "holding_summary": "Establishes the EDUCATIONAL-REMEDY FRAMEWORK: monetary sanctions paired with mandatory CLE-style AI course attendance as a corrective sanction. Reflects an emerging judicial recognition that attorney AI competence is a learnable skill and that remediation through education complements monetary deterrence. Subsequent orders (notably In re Martin, requiring NCBJ AI plenary attendance) adopt similar educational components.", "source_url": "https://news.bloomberglaw.com/litigation/texas-attorney-sanctioned-over-ai-generated-citations-in-filing", "source_type": "secondary_aggregator (Bloomberg Law / JDJournal); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "5th_circuit, edtex, hallucinated_citations, rule_11, educational_remedy, mandatory_ai_course, framework_setter, attorney, employment", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "civil, employment, wrongful_termination", "bankruptcy_relevance": "secondary", "framework_tag": "educational_remedy_mandatory_ai_course", "internal_corpus_use": "corrective_sanctions_pattern, ai_competence_remediation" }, { "id": "eo-14110-biden-ai-2023", "court": "n/a (executive branch action)", "circuit": "n/a", "judge": "n/a (executive order issued by President Biden)", "order_type": "executive_order", "date_issued": "2023-10-30", "title": "Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence", "case_citation": "88 Fed. Reg. 75191 (Nov. 1, 2023)", "docket_no": "EO 14110", "disclosure_required": "n/a", "disclosure_scope": "Required federal agencies to develop standards, tests, and tools for AI safety; required developers of dual-use foundation models to share safety test results with the federal government; directed NIST to establish guidelines for AI red-teaming; required CFOs and CIOs to designate Chief AI Officers in federal agencies.", "sanctions_imposed": null, "triggering_conduct": "Issued in response to the rapid public deployment of generative AI systems through 2022-2023 and growing concern over AI risks across national security, civil rights, consumer protection, and labor markets.", "holding_summary": "The most comprehensive U.S. federal-government AI governance instrument issued to date at the time of issuance. Directed over 50 federal entities to take more than 100 specific actions across eight policy areas: safety and security; innovation and competition; supporting workers; equity and civil rights; consumer protection; privacy; federal use of AI; and international leadership. Established the foundational federal-AI policy architecture that subsequent OMB memos (M-24-10), agency guidance, and NIST AI Risk Management Framework operationalized. REVOKED by Executive Order 14179 on January 20, 2025, though many of its operational artifacts (NIST AI RMF, agency Chief AI Officer roles created under it, etc.) persist as freestanding institutional structures.", "source_url": "https://www.federalregister.gov/documents/2023/11/01/2023-24283/safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence", "source_type": "federal_register", "verification_status": "primary_source_verified", "tags": "executive_branch, biden_administration, federal_ai_governance, nist_ai_rmf_predicate, revoked, foundational_ai_policy, federal_register", "category": "executive", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "federal_ai_policy, national_security, civil_rights, consumer_protection, privacy, labor", "bankruptcy_relevance": "none", "framework_tag": "foundational_federal_ai_governance", "internal_corpus_use": "federal_ai_policy_baseline, agency_chief_ai_officer_predicate" }, { "id": "eo-14179-trump-ai-revocation-2025", "court": "n/a (executive branch action)", "circuit": "n/a", "judge": "n/a (executive order issued by President Trump)", "order_type": "executive_order", "date_issued": "2025-01-20", "title": "Executive Order 14179: Removing Barriers to American Leadership in Artificial Intelligence", "case_citation": "(Federal Register publication forthcoming at issuance; pending exact citation)", "docket_no": "EO 14179", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": null, "triggering_conduct": "Issued on Day 1 of the Trump second-term administration as part of a broader rollback of Biden-era executive actions, with stated rationale that prior AI EO regulatory architecture restricted American AI competitiveness.", "holding_summary": "Revokes Executive Order 14110 (Biden's Safe, Secure, and Trustworthy AI). Establishes the DEREGULATORY FEDERAL AI FRAMEWORK: rescinds the federal-government AI safety/security testing requirements, foundation-model developer reporting obligations, and centralized federal AI governance architecture established in EO 14110. Many operational artifacts of EO 14110 (NIST AI RMF as a voluntary framework, agency Chief AI Officer roles) are not directly affected and persist as freestanding institutional structures, but their political-policy backing is removed. Notable for the policy whiplash it creates for federal contractors, AI developers, and agencies that built compliance programs around EO 14110.", "source_url": "https://www.whitehouse.gov/presidential-actions/2025/01/removing-barriers-to-american-leadership-in-artificial-intelligence/", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "executive_branch, trump_administration, federal_ai_governance, deregulation, eo_14110_revocation, policy_whiplash", "category": "executive", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "federal_ai_policy", "bankruptcy_relevance": "none", "framework_tag": "federal_ai_deregulation", "internal_corpus_use": "federal_ai_policy_baseline, policy_volatility" }, { "id": "glyndon-square-llc-bkrtcy-dsc-2025", "court": "U.S. Bankruptcy Court, District of South Carolina", "circuit": "4th Cir.", "judge": "[bankruptcy judge, pending docket pull]", "order_type": "sanctions_order", "date_issued": "2025 (exact date pending docket pull)", "title": "Glyndon Square LLC Adversary Proceeding: Order on AI-Hallucinated Bankruptcy Citations", "case_citation": "(Bankr. D.S.C. 2025) (adversary proceeding by debtors against landlord)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Non-monetary sanctions imposed on debtors' counsel.", "triggering_conduct": "Debtors' counsel filed a motion for preliminary injunction in adversary proceeding against landlord Glyndon Square LLC. The motion cited two bankruptcy cases that did not exist.", "holding_summary": "Establishes the NON-MONETARY-SANCTION FRAMEWORK in bankruptcy court for AI-hallucinated citations: where the misconduct is more isolated (two fabricated cases rather than systemic pattern across multiple briefs), bankruptcy courts may deploy non-monetary remedies (public notation in record, mandatory educational requirements, future filing-conduct strictures) rather than monetary fines. Significant for proportionality analysis: not every bankruptcy AI hallucination triggers In re Martin / In re Jackson Hospital level monetary sanctions.", "source_url": "https://news.bloomberglaw.com/bankruptcy-law/bankruptcy-judges-step-up-sanctions-on-attorneys-misusing-ai", "source_type": "secondary_aggregator (Bloomberg Law); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "4th_circuit, bankruptcy_court, adversary_proceeding, hallucinated_citations, non_monetary_sanctions, rule_9011, proportionality, framework_setter", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "bankruptcy, adversary_proceeding, landlord_tenant", "bankruptcy_relevance": "primary", "framework_tag": "non_monetary_bankruptcy_sanction", "internal_corpus_use": "bankruptcy_filing_verification, proportionality_analysis, adversary_proceeding_pattern" }, { "id": "in-re-prince-usa-sdny-bkrtcy-2026", "court": "U.S. Bankruptcy Court, Southern District of New York", "circuit": "2d Cir.", "judge": "[bankruptcy judge, pending docket pull]", "order_type": "opinion", "date_issued": "2026-04-18", "title": "In re Prince USA: Sullivan & Cromwell Emergency Letter on AI-Generated Hallucinations", "case_citation": "(Bankr. S.D.N.Y. April 2026)", "docket_no": "[pending docket pull]", "disclosure_required": "n/a", "disclosure_scope": "n/a", "sanctions_imposed": "Sanctions disposition pending. Sullivan & Cromwell filed emergency letter on April 18, 2026, asking the court to avoid imposing sanctions after admitting its court filing contained AI-generated hallucinations.", "triggering_conduct": "Sullivan & Cromwell, one of the most prominent BigLaw firms in the United States, admitted in its own filed letter that a brief in this bankruptcy matter contained AI-generated hallucinations including fabricated citations and legal errors. The firm self-reported and filed the emergency letter rather than waiting for opposing counsel or the court to detect the fabrications.", "holding_summary": "Emergency self-disclosure pattern. Significant as a proactive-disclosure framework: where AI-fabricated content is detected post-filing, prompt self-reporting (rather than concealment or doubling-down) is being used by sanctions-aware counsel as a mitigation strategy. Demonstrates that even top-tier BigLaw practices in the highest-profile bankruptcy district are vulnerable to AI-hallucination errors. Outcome will set a precedent for whether self-disclosure mitigates sanctions in BigLaw bankruptcy contexts.", "source_url": "https://news.bloomberglaw.com/bankruptcy-law/bankruptcy-judges-step-up-sanctions-on-attorneys-misusing-ai", "source_type": "secondary_aggregator (Bloomberg Law); primary docket pull pending", "verification_status": "facts_corroborated_multi_source", "tags": "2d_circuit, bankruptcy_court, sullivan_cromwell, biglaw, self_disclosure, hallucinated_citations, proactive_mitigation, framework_pending, sdny", "category": "judicial", "branch": "judicial", "jurisdiction_level": "federal", "subject_matter": "bankruptcy, biglaw_practice", "bankruptcy_relevance": "primary", "framework_tag": "self_disclosure_mitigation", "internal_corpus_use": "bankruptcy_filing_verification, self_disclosure_pattern, biglaw_responder_pattern" }, { "id": "omb-m-24-10-2024", "court": "n/a (executive branch action)", "circuit": "n/a", "judge": "n/a (issued by Office of Management and Budget)", "order_type": "agency_rule", "date_issued": "2024-03-28", "title": "OMB Memorandum M-24-10: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence", "case_citation": "OMB M-24-10 (Mar. 28, 2024)", "docket_no": "M-24-10", "disclosure_required": "true", "disclosure_scope": "Directs federal executive-branch agencies to: (1) designate a Chief AI Officer (CAIO); (2) establish internal AI governance mechanisms; (3) maintain inventories of AI use cases; (4) adopt minimum risk-management practices for AI systems presumed to be rights-impacting or safety-impacting (presumptive list defined in the memo); (5) implement notice and explanation rights for individuals affected by AI decisions; (6) monitor and evaluate AI performance ongoing.", "sanctions_imposed": null, "triggering_conduct": "Issued by OMB pursuant to EO 14110 to operationalize federal-agency AI governance requirements.", "holding_summary": "Operationalizing companion to EO 14110. Establishes the FEDERAL AGENCY AI GOVERNANCE FRAMEWORK: every federal executive-branch agency must designate a Chief AI Officer, maintain an AI use-case inventory, and apply differentiated risk management to rights-impacting and safety-impacting AI systems. References the NIST AI Risk Management Framework as a key technical reference for agency compliance. Notable persistence layer: even after EO 14110 was revoked, the operational structures created under M-24-10 (CAIO roles, inventories) generally persist as freestanding institutional artifacts; partially superseded by OMB M-25-21 in February 2025.", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2024/03/M-24-10-Advancing-Governance-Innovation-and-Risk-Management-for-Agency-Use-of-Artificial-Intelligence.pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "executive_branch, omb, biden_administration, federal_agency_ai, chief_ai_officer, ai_inventory, risk_management, eo_14110_implementation, partially_superseded", "category": "regulatory", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "federal_ai_policy, agency_governance, civil_rights, public_safety", "bankruptcy_relevance": "none", "framework_tag": "federal_agency_ai_governance", "internal_corpus_use": "federal_ai_policy_baseline, agency_compliance_pattern" }, { "id": "omb-m-25-21-2025", "court": "n/a (executive branch action)", "circuit": "n/a", "judge": "n/a (issued by Office of Management and Budget)", "order_type": "agency_rule", "date_issued": "2025-02 (exact date pending verification)", "title": "OMB Memorandum M-25-21: Accelerating Federal Use of AI through Innovation, Governance, and Public Trust", "case_citation": "OMB M-25-21 (Feb. 2025)", "docket_no": "M-25-21", "disclosure_required": "true", "disclosure_scope": "Reframes federal AI governance from EO 14110 / M-24-10 emphasis on safety/rights-protection toward an emphasis on innovation, public trust, and accelerated federal AI adoption. Maintains some governance structures (Chief AI Officer roles, inventories) while loosening other risk-management constraints.", "sanctions_imposed": null, "triggering_conduct": "Issued by the Trump administration OMB to replace the Biden-era M-24-10 governance framework, consistent with the broader deregulatory posture of EO 14179.", "holding_summary": "Replacement memorandum that reframes federal AI governance toward acceleration and innovation, partially superseding M-24-10. Preserves some operational structures (Chief AI Officer roles, AI use-case inventories) but reorients the policy emphasis from safety/rights-protection to adoption velocity and public trust. Establishes the POLICY-WHIPLASH FRAMEWORK for federal AI compliance officers: agency-level governance structures must accommodate rapid policy reorientation across administrations without complete operational reset.", "source_url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "executive_branch, omb, trump_administration, federal_agency_ai, partial_supersession, policy_whiplash, deregulatory_reorientation", "category": "regulatory", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "federal_ai_policy, agency_governance", "bankruptcy_relevance": "none", "framework_tag": "federal_ai_policy_acceleration", "internal_corpus_use": "federal_ai_policy_baseline, policy_volatility" }, { "id": "nist-ai-rmf-1-0-2023", "court": "n/a (federal agency-issued voluntary framework)", "circuit": "n/a", "judge": "n/a (issued by National Institute of Standards and Technology)", "order_type": "agency_rule", "date_issued": "2023-01-26", "title": "NIST AI Risk Management Framework 1.0 (AI RMF 1.0)", "case_citation": "NIST AI 100-1 (Jan. 26, 2023)", "docket_no": "NIST AI 100-1", "disclosure_required": "false", "disclosure_scope": "Voluntary framework. Provides guidance for organizations to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems. Organized around four core functions: GOVERN, MAP, MEASURE, MANAGE.", "sanctions_imposed": null, "triggering_conduct": "Developed in response to Congressional direction in the National AI Initiative Act of 2020 and growing public/agency concern over AI trustworthiness. Released after 18 months of public consultation and stakeholder input.", "holding_summary": "Establishes the FOUNDATIONAL VOLUNTARY US AI GOVERNANCE FRAMEWORK. Adopted as a key technical reference by federal agencies under EO 14110 / OMB M-24-10. Remains operationally durable across administrations because of its voluntary, technical-reference status (rather than regulatory), survived the Biden-Trump transition unchanged. The four-function GOVERN-MAP-MEASURE-MANAGE structure has become the dominant US analog to international AI governance frameworks (EU AI Act risk categorization, ISO/IEC 23894 AI risk management). Cited by federal agencies, state legislatures (Colorado AI Act), and private-sector compliance programs as the baseline US AI risk-management standard.", "source_url": "https://www.nist.gov/itl/ai-risk-management-framework", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "federal_agency, nist, voluntary_framework, ai_risk_management, trustworthy_ai, durable_across_administrations, foundational", "category": "regulatory", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "ai_risk_management, technical_standards", "bankruptcy_relevance": "none", "framework_tag": "voluntary_ai_risk_management", "internal_corpus_use": "federal_ai_policy_baseline, technical_reference_durability" }, { "id": "colorado-ai-act-sb24-205", "court": "n/a (state legislation)", "circuit": "n/a", "judge": "n/a (signed by Governor Jared Polis)", "order_type": "legislation", "date_issued": "2024-05-17", "title": "Colorado Senate Bill 24-205: Consumer Protections for Artificial Intelligence (Colorado AI Act)", "case_citation": "Colo. Rev. Stat. tit. 6, art. 1, pt. 17 (2024)", "docket_no": "SB24-205", "disclosure_required": "true", "disclosure_scope": "Requires developers and deployers of high-risk AI systems to use reasonable care to protect consumers from known or reasonably foreseeable risks of algorithmic discrimination. Specific obligations include implementing a risk management policy, completing impact assessments, conducting annual deployment reviews, providing consumer notification of AI use in consequential decisions, and providing appeal opportunities. Effective date originally Feb. 1, 2026; extended to June 30, 2026 by SB25B-004.", "sanctions_imposed": "Enforcement by Colorado Attorney General; civil penalties for violations. Specific penalty schedule subject to AG rulemaking under the Anti-Discrimination in AI rulemaking authority.", "triggering_conduct": "Enacted in response to growing legislative concern over algorithmic discrimination in consequential consumer-facing AI decisions (employment, housing, insurance, education, financial services). Modeled in part on EU AI Act risk-categorization approach.", "holding_summary": "FIRST COMPREHENSIVE STATE AI CONSUMER PROTECTION LAW with broad scope (Colorado is the second US state to enact major AI consumer-protection legislation; the first is the subject of jurisdictional debate among practitioners). Establishes the STATE-LEVEL HIGH-RISK AI FRAMEWORK: risk categorization, mandatory impact assessments, consumer notification rights, and appeal mechanisms for algorithmic decisions affecting employment, housing, financial services, education, and other consequential domains. Influential template for subsequent state AI legislation. Notable for the multi-step delayed effective date (originally Feb 2026, extended to June 30 2026), reflecting industry compliance-readiness concerns.", "source_url": "https://leg.colorado.gov/bills/sb24-205", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "state_legislation, colorado, consumer_protection, algorithmic_discrimination, high_risk_ai, foundational_state_law, eu_ai_act_inspired, polis_administration", "category": "legislative", "branch": "legislative", "jurisdiction_level": "state", "subject_matter": "consumer_protection, employment, housing, insurance, financial_services, algorithmic_discrimination", "bankruptcy_relevance": "secondary", "framework_tag": "state_high_risk_ai_consumer_protection", "internal_corpus_use": "state_ai_law_baseline, algorithmic_discrimination_doctrine" }, { "id": "ftc-rite-aid-2023", "court": "U.S. District Court, Eastern District of Pennsylvania (consent order venue)", "circuit": "3d Cir.", "judge": "n/a (FTC consent order)", "order_type": "agency_rule", "date_issued": "2023-12-19", "title": "FTC v. Rite Aid Corporation: Consent Order on AI Facial Recognition Misuse", "case_citation": "FTC v. Rite Aid Corp., No. 2023190 (FTC consent order Dec. 19, 2023)", "docket_no": "FTC No. 2023190", "disclosure_required": "true", "disclosure_scope": "Consent order requires Rite Aid to: (1) NOT use any Facial Recognition or Analysis System for 5 years; (2) implement comprehensive information-security program; (3) provide redress to harmed consumers; (4) report annually to FTC on compliance.", "sanctions_imposed": "FIVE-YEAR BAN on Rite Aid using any facial recognition or analysis system. Comprehensive information-security program required. Consumer redress obligations. Reporting requirements.", "triggering_conduct": "FTC alleged that Rite Aid violated Section 5 of the FTC Act by failing to implement reasonable procedures to prevent harm to consumers in its use of AI-based facial recognition technology, which falsely tagged consumers (particularly women and people of color) as shoplifters. Deployment occurred in hundreds of stores from 2012-2020 without reasonable safeguards.", "holding_summary": "FTC's FIRST ENFORCEMENT ACTION against a company for AI bias and unfair AI use. Establishes the FEDERAL AI BIAS ENFORCEMENT FRAMEWORK under FTC Act Section 5: AI deployment without reasonable bias-mitigation safeguards constitutes an unfair practice subject to FTC enforcement. Notable five-year facial-recognition ban (rather than monetary fine alone) sets a remedial pattern of capability restrictions for AI misuse. Cited as foundational precedent by EEOC, CFPB, and state AGs in subsequent AI-bias enforcement matters. Settlement context: Rite Aid was in Chapter 11 bankruptcy at the time, which influenced the negotiated remedial structure.", "source_url": "https://www.ftc.gov/news-events/news/press-releases/2023/12/rite-aid-banned-using-ai-facial-recognition-after-ftc-says-retailer-deployed-technology-without", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "ftc, federal_enforcement, ai_bias, facial_recognition, capability_restriction, section_5, foundational_precedent, rite_aid, consumer_protection", "category": "regulatory", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "consumer_protection, ai_bias, facial_recognition, retail", "bankruptcy_relevance": "primary", "framework_tag": "ftc_ai_bias_unfair_practice", "internal_corpus_use": "federal_ai_enforcement_baseline, bankruptcy_intersection_with_ai_enforcement, rite_aid_bankruptcy_overlap" }, { "id": "eeoc-ai-hiring-guidance-2023", "court": "n/a (federal agency technical-assistance document)", "circuit": "n/a", "judge": "n/a (issued by Equal Employment Opportunity Commission)", "order_type": "agency_rule", "date_issued": "2023-05-18", "title": "EEOC Technical Assistance: Title VII Application to AI-Based Employment Selection Procedures", "case_citation": "EEOC Technical Assistance Document (May 18, 2023)", "docket_no": "EEOC TA 2023-05-18", "disclosure_required": "false", "disclosure_scope": "Non-binding technical assistance. Confirms that the Uniform Selection Guidelines on Employee Selection Procedures apply equally to AI-based selection tools used in hiring, promoting, and firing decisions. Applies the Four-Fifths Rule (80%) for preliminary disparate-impact analysis.", "sanctions_imposed": null, "triggering_conduct": "Issued in response to widespread employer adoption of AI-based hiring and selection tools and growing concern over algorithmic disparate impact under Title VII of the Civil Rights Act of 1964.", "holding_summary": "Establishes the EEOC AI HIRING DISPARATE-IMPACT FRAMEWORK: AI-based employment selection tools are subject to the same Title VII disparate-impact analysis as traditional selection procedures. The Uniform Guidelines' Four-Fifths Rule (a selection rate for protected-class members below 80% of the most-selected group's rate triggers preliminary adverse-impact finding) applies to algorithmic outputs. Foundational technical-assistance document for federal employment-AI compliance. Subsequently reversed in part by the Trump-administration EEOC in 2025 (per K&L Gates analysis), creating policy-volatility patterns parallel to the EO 14110 / 14179 whiplash.", "source_url": "https://www.eeoc.gov/sites/default/files/2024-04/20240429_What%20is%20the%20EEOCs%20role%20in%20AI.pdf", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "eeoc, federal_agency, ai_hiring, title_vii, four_fifths_rule, disparate_impact, employment_law, partial_reversal_2025, policy_whiplash", "category": "regulatory", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "employment, ai_hiring, civil_rights, disparate_impact", "bankruptcy_relevance": "none", "framework_tag": "eeoc_ai_disparate_impact", "internal_corpus_use": "federal_ai_employment_baseline, four_fifths_rule_application" }, { "id": "cfpb-ai-mortgage-avm-rule-2024", "court": "n/a (federal agency rulemaking)", "circuit": "n/a", "judge": "n/a (issued by Consumer Financial Protection Bureau)", "order_type": "agency_rule", "date_issued": "2024-06-24", "title": "CFPB Final Rule on AI in Automated Valuation Models for Home Mortgage Appraisals", "case_citation": "12 C.F.R. Pt. 1026 (CFPB 2024)", "docket_no": "(Federal Register publication forthcoming)", "disclosure_required": "true", "disclosure_scope": "Final rule requires mortgage originators and secondary market issuers using automated valuation models (AVMs) to: (1) ensure a high level of confidence in valuation estimates; (2) protect against data manipulation; (3) avoid conflicts of interest; (4) require random sample testing and reviews; (5) comply with applicable nondiscrimination laws.", "sanctions_imposed": "Enforcement under CFPB authority; civil money penalties for violations of the rule and the underlying consumer-protection statutes.", "triggering_conduct": "Promulgated under section 1473(q) of the Dodd-Frank Wall Street Reform and Consumer Protection Act in response to growing use of AI/algorithmic AVMs in mortgage lending and concerns about algorithmic bias in home valuations.", "holding_summary": "Establishes the CONSUMER-FINANCE AI VALIDATION FRAMEWORK: federal regulation of AI/algorithmic systems used in consumer mortgage decisions through quality-control, bias-mitigation, and conflict-of-interest requirements. Notable as one of the first federal regulations directly imposing technical quality-control duties on AI deployment in a specific consumer-finance domain (rather than general-purpose guidance). Implements Dodd-Frank section 1473(q) and applies long-standing fair-housing nondiscrimination principles to algorithmic valuation.", "source_url": "https://www.consumerfinance.gov/about-us/blog/cfpb-approves-rule-to-ensure-accuracy-and-accountability-in-the-use-of-ai-and-algorithms-in-home-appraisals/", "source_type": "court_website", "verification_status": "primary_source_verified", "tags": "cfpb, federal_agency, ai_mortgage, automated_valuation_models, dodd_frank, nondiscrimination, consumer_finance, fair_housing", "category": "regulatory", "branch": "executive", "jurisdiction_level": "federal", "subject_matter": "consumer_finance, mortgage, fair_housing, algorithmic_discrimination", "bankruptcy_relevance": "secondary", "framework_tag": "ai_consumer_finance_validation", "internal_corpus_use": "federal_ai_consumer_finance_baseline, mortgage_ai_compliance_pattern" } ] }