Should factitious citations enter an AI-assisted brief, show cause follows

On September 24, the court in Clark v. Social Security, Commissioner of ordered Rich to show cause as to why she should not be sanctioned, including with the imposition of a fine, for including factitious citations in a plaintiff’s brief, according to CourtListener: AI and sanctions (opinions). The same entry says the brief utilized generative artificial intelligence and that Rich responded to the show cause order. The immediate event is therefore not a sanction already imposed, but a court requiring an explanation before deciding whether sanctions, including a fine, should follow.

That distinction is the point. Generative AI can change how a brief is produced, but it does not remove the consequences attached to what the brief puts before a court. A filing with factitious citations still creates a court-facing problem, and the court’s response in Clark shows that AI use can become part of the path to accountability rather than a shield against it. The position is strongest here in its narrow form: a court has connected AI-assisted drafting with an order demanding an answer about defective legal work. It does not yet establish that every use of AI produces a sanction, or that AI-assisted work is generally unreliable.

Clark proves that one brief led to one show cause order. It does not prove that Rich will ultimately be fined, that the citations were all generated by AI, or that a broader category of AI-assisted legal work is defective. CourtListener: AI and sanctions (opinions) reports that the court ordered Rich to show cause and that the brief contained factitious citations; the order itself is enough to establish the procedural consequence, not the final penalty. The stronger reading would require a later sanctions order, or repeated orders showing that AI-assisted filings regularly produce the same result. A separate report from Legaltech News (Law.com) supplies a related but different example: a newly filed lawsuit in the Superior Court of New Jersey, Gloucester County concerns an AI-powered meeting tool that allegedly captured and distributed information in ways users never intended. That report broadens the category of possible AI-related harm, but it does not turn the Clark order into proof about AI-native legal delivery. The two matters instead support a limited conclusion: changing the production tool does not cancel the legal consequences of the resulting work or information handling.

The next fact to watch is a sanctions order in Clark v. Social Security, Commissioner of stating whether the court imposes a fine or another sanction after the show cause process. That order would confirm that the consequence moved from procedural scrutiny to an actual penalty. If the court declines to sanction Rich, the order would narrow the lesson without erasing it: the AI-assisted brief would still have triggered judicial review over factitious citations. We would score the stronger claim only after completed matters show both the quality of the work and the consequence of getting it wrong.