TRAIN Act Creates Expedited Subpoena Process for Copyright Owners to Investigate AI Training Data

The newly proposed Transparency and Responsibility for Artificial Intelligence Networks Act, or TRAIN Act, sets up a fast-track legal process allowing copyright owners to investigate whether developers used their work to train generative AI models. This is a major procedural shift: if you own the copyright to a novel, a song, or a large database, this bill gives you a direct line to demand records from the company that built the latest text or image generator.

The Fast Track to the AI Black Box

Section 2 of the TRAIN Act amends existing copyright law (Chapter 5 of title 17) to establish a new subpoena mechanism. If a copyright owner—or their representative—has a “subjective good faith belief” that a developer used their copyrighted work as “training material,” they can file a sworn declaration and a proposed subpoena with a U.S. district court clerk. If the paperwork is in order, the clerk must “expeditiously issue and sign” the subpoena, which orders the developer to disclose the relevant records or copies. Crucially, this subpoena can only seek information about the requester’s own copyrighted works, not anyone else’s.

Think of it this way: Right now, if you suspect an AI company used your work, you have to go through the lengthy, expensive process of a full federal lawsuit discovery phase just to get a peek inside the training data. This bill essentially bypasses that, giving copyright holders a relatively quick, low-bar entry point to demand proprietary information. The definition of a “developer” is broad, covering anyone who designs, owns, or “substantially modifies” a generative AI model, or even just curates the training dataset.

The Burden of Proof Shifts to Developers

This is where things get serious for AI developers. The TRAIN Act introduces a powerful enforcement hammer: If a developer fails to comply with the subpoena and hand over the requested records, that failure automatically creates a “rebuttable presumption” that the developer made copies of the copyrighted work. In plain English, if the developer ducks the subpoena, the court assumes they infringed, and the burden flips to the developer to prove they didn't use the work. That’s a significant procedural advantage for the copyright owner in any subsequent lawsuit.

For a small AI startup, this could be a massive headache. Not only must they now comply with a potentially high volume of these expedited subpoenas, but non-compliance means they walk into court already presumed guilty. The bill does offer a protection against abuse, though: if the court finds a subpoena was requested in bad faith, the requester can face sanctions under Rule 11 of the Federal Rules of Civil Procedure.

The Confidentiality Catch

While the bill aims to help copyright owners, it also imposes strict limits on the information they receive. A copyright owner who gets copies or records from a developer under this process “must not disclose that information to any other person without proper authorization or consent.” This means that while individual artists or writers can gain insight into whether their specific work was used, they can't necessarily share that information publicly or with other artists without the developer’s permission. This confidentiality requirement is intended to protect the developer's proprietary training data, but it might limit transparency about what large-scale models are actually being fed. For the average person, this means that while the fight over AI training data heats up, the details of what’s in those massive datasets will likely remain locked down in private legal agreements.