Peter Toren

Trade secrets occupy a unique position among the major forms of intellectual property. Patents, copyrights, and trademarks are, by design, defined and publicly registered, and can be consulted to determine exactly what is claimed. In contrast, trade secrets depend on their being undisclosed. This creates a structural problem the moment a trade secret owner goes to court. Because they are secret, they cannot be identified in public filings without destroying the very subject matter of the plaintiff’s claim. On the other hand, defendants must understand what the secrets are and what they’ve allegedly misappropriated. In addition, the court needs to know what the case is about to manage it.

The U.S. Court of Appeals for the Ninth Circuit in Comet Technologies USA, Inc. v. XP Power, LLC, overturned Comet Technologies’ $40 million trade secret verdict against XP Power and ordered a new trial, finding that the district court erroneously instructed the jury that the defendant bore the burden of proving that Comet’s trade secrets were readily ascertainable by proper means. The court held that the error was not harmless because the instructions were not accurate as a whole, and nothing in the jury’s verdict shed light on how it would have ruled under a correct instruction. The case is notable both for clarifying what “readily ascertainable” means and for spotlighting a burden-of-proof distinction between the Defend Trade Secrets Act (DTSA) and the California Uniform Trade Secrets Act (CUTSA) that practitioners should not overlook.

The U.S. Supreme Court has been asked to grant certiorari to resolve whether the Defend Trade Secrets Act (DTSA) permits an unjust enrichment award without any showing of actual loss resulting from the defendant’s misappropriation of trade secrets. The defendant in Tata Consultancy Services Ltd. v. Computer Sciences Corp. has petitioned for certiorari, arguing that actual loss is a prerequisite for an unjust enrichment award. The petition challenges a Fifth Circuit decision affirming a $56 million unjust enrichment award and a $112 million punitive award in favor of Computer Sciences Corp. (“CSC”), measured by the costs Tata Consultancy Services (TCS) avoided through its trade secret theft rather than by any proven actual loss to CSC.

Two recent federal district court decisions highlight the significant risks of sharing confidential information with a generative AI platform. In Trinidad v. OpenAI, the court dismissed the plaintiff’s trade secret claims under the Defend Trade Secrets Act (DTSA) because the plaintiff had voluntarily disclosed her allegedly proprietary frameworks to OpenAI while using ChatGPT to create them.Then, Judge Rakoff in United States v. Heppner held that documents created using publicly available generative AI are not protected by the attorney-client privilege—in part because communications memorialized through an AI platform are not confidential when the platform is not contractually bound to keep them secret.

Whether the plaintiff has adequately identified the trade secrets that have allegedly been misappropriated is a commonly litigated and critical issue under the Defend Trade Secrets Act (DTSA). Unlike other types of intellectual property—such as patents, copyrights, and trademarks—where the property has already been identified and registered, trade secrets by definition are secret and cannot be identified publicly without destroying the subject matter of the plaintiff’s legal claim. Yet defendants still need to know what secrets they have allegedly misappropriated, and the court needs to know what the case is about.