Should factitious citations draw a show-cause order, sanctions are not yet imposed

A court ordered Rich to show cause why she should not be sanctioned, including with the imposition of a fine, after a brief in Clark v. Social Security, Commissioner of included factitious citations, according to CourtListener RECAP dockets: generative AI and sanctions or hallucinations. The docket says Rich used generative artificial intelligence in preparing the plaintiff’s brief. It also says the court had ordered the show-cause response after the brief raised the citation problem. The immediate event is therefore a court process directed at a filing and the person responsible for it, not a sanction against an AI tool or a finding about an AI-native legal provider.

That distinction matters because AI assistance does not remove the consequences attached to bad legal work. In Clark, the use of generative artificial intelligence appears alongside a court order requiring an explanation for factitious citations and exposing a fine as a possible result. The workflow may have involved AI, but the accountability mechanism remains human and institutional: a court examines the filing and can require the person who submitted it to answer. CourtListener: AI and sanctions (opinions) describes Douglas v. Deutsche Bank National Trust Co., Published Order as a cautionary tale about the misuse of artificial intelligence and its consequences for attorneys. CourtListener RECAP dockets: generative AI and sanctions or hallucinations also reports a filing in Macias v. CCADC that disclosed OpenAI Codex assistance and included a certification of personal checking for accuracy, including citations. Those matters point in the same direction: AI can change how legal work is produced without changing the consequences attached to inaccurate work or the need for review.

Clark proves that a court can connect AI-assisted briefing with a show-cause process over factitious citations. It does not prove that sanctions have already been imposed, that a fine will follow, or that every use of AI in a brief produces the same result. The order reported in the docket is preliminary in the relevant sense: it demands an explanation. A stronger reading would require a later order stating whether Rich was sanctioned, whether a fine was imposed, and what findings the court made about the citations and the review of the brief. The case also says nothing about the performance of an AI-native firm as a business model. The order concerns a particular filing and a particular response process. Treating it as proof that AI cannot be used in legal work would go beyond the event; treating it as proof that AI use does not eliminate accountability is the narrower conclusion the order supports.

The next fact to watch is the court’s disposition of the show-cause process in Clark v. Social Security, Commissioner of: an order imposing or declining sanctions, identifying any fine, and explaining the treatment of the factitious citations. A separate filing that states how AI-assisted portions and citations were personally checked, as in Macias v. CCADC, would show a review procedure being made explicit rather than assumed. We will score the stronger position only if courts continue to attach concrete consequences to inaccurate AI-assisted work while distinguishing disclosed, checked assistance from unsupported output.