Legal AI Ethics: Competence, Detection, and the New Compliance Expectation

Legal AI Ethics: Competence, Detection, and the New Compliance Expectation

In an analysis of Noland v. Land of the Free, L.P., Joe Stephens explains in Bloomberg Law how legal AI ethics have expanded beyond competent internal use to now include the detection of misuse by opposing parties. The California Court of Appeals ruled that using fabricated citations generated by AI tools can have serious consequences. This case highlights an emerging compliance standard: attorneys must verify opposing citations with the same diligence they apply to their own work.

Stephens points out that the plaintiff’s counsel used generative tools to “enhance” an appellate brief, which resulted in widespread fabrication of citations. Ultimately, the court imposed a $10,000 sanction on that attorney and referred the matter to the State Bar. However, when the opposing counsel sought to recover fees, the court denied their request because they had not identified the false authorities themselves. This decision tied the diligence required in citation verification to the ability to recover legal fees, indicating that detecting inaccuracies is part of an attorney’s professional responsibility.

This ruling stands in contrast to California’s existing ethical framework, as Stephens explains with reference to Rules 8.3 and 8.4(c). Although no specific rule mandates screening for AI-related misconduct, the court found that failing to uncover fabricated citations constituted a lapse in diligence that undermined both the adversarial process and judicial efficiency. It remains uncertain whether courts outside California have reached similar conclusions.

Several key takeaways emerge from this case. First, verifying all opposing citations has become a practical necessity, even if this requirement is not explicitly stated. Second, attorneys who discover fabricated content must report it promptly to preserve their right to recover fees. Lastly, this ruling indicates that proactive scrutiny is increasingly part of legal AI ethics, reflecting a judiciary unwilling to bear the burdens created by unverified or AI-generated filings.