TRAIN Act Introduces First Federal Standards for AI Training Transparency

Representatives Madeleine Dean (D-PA) and Nathaniel Moran (R-TX) have introduced bipartisan legislation that would empower creators to discover if their copyrighted works were used to train generative AI models without permission. The Transparency and Responsibility for Artificial Intelligence Networks (TRAIN) Act represents the first federal attempt to create statutory transparency requirements for AI training data.

New Legal Framework for Copyright Protection

The TRAIN Act would establish the first federal statutory definition of "generative AI models" as AI systems that "emulate the structure and characteristics of input data in order to generate derived synthetic content," including text, images, video, and audio content.

Under the proposed framework, copyright owners could use federal court subpoena power to compel AI developers to disclose training materials. The process requires:

• A sworn affidavit attesting to good faith belief that copyrighted works were used without authorization
• Certification that the subpoena serves solely to protect copyright owner's rights
• Evidence that requests are made in good faith to avoid sanctions

Once served, developers must "expeditiously disclose" the requested copies or records to copyright owners or their authorized representatives.

Enforcement Mechanisms and Protections

The legislation includes balanced enforcement provisions to prevent abuse while ensuring compliance:

For Developers: If AI companies fail to comply with subpoenas, courts may apply a rebuttable presumption that they did use the copyrighted works in question—potentially strengthening copyright owners' infringement cases.

For Copyright Owners: Those who seek subpoenas in bad faith face potential sanctions under Federal Rule of Civil Procedure 11, providing safeguards against frivolous requests.

Industry Impact and Implications

This legislation addresses growing tensions between AI companies and creative industries over training data usage. Major AI developers like OpenAI, Anthropic, and Google have faced multiple lawsuits from authors, artists, and publishers claiming unauthorized use of copyrighted materials.

The TRAIN Act would provide creators with investigative tools to build stronger copyright infringement cases while potentially forcing AI companies to be more transparent about their data acquisition practices.

Key Takeaways:

• First Federal Definition: Creates statutory definition of generative AI models for legal purposes
• Investigative Power: Gives copyright owners subpoena authority to investigate AI training data usage
• Balanced Approach: Includes protections against both non-compliance and bad faith requests
• Industry Accountability: Could force AI developers to implement better tracking of training data sources

If enacted, the TRAIN Act would significantly expand transparency obligations for AI developers while providing creators with powerful new tools to protect their intellectual property rights in the age of generative artificial intelligence.

Read the full article on National Law Review