Who Owns AI Model Weights? What the Law Has Not Yet Decided

This is educational information, not legal advice. “Who owns model weights?” sounds like it needs one owner. First it needs three objects separated: training data, the resulting numerical values called weights, and outputs generated when the model is used. Each raises a different legal debate. The most important answer is uncomfortable but precise: courts have not generally decided whether model weights are a copyrighted work, a database, a trade secret, or none of those things.

Training data

Data are the text, images, code, audio and other materials used in training. Depending on the material and country, they can raise copyright, database, contract, privacy or other questions. A work entering training does not prove it sits inside a weights file as a readable library; nor does that remove questions about copying during training.

In the United States, the June 25, 2025 order in Kadrey v. Meta resolved fair-use issues on the record before that court and granted Meta summary judgment. It did not decide who owns all model weights, is not a rule for every lawsuit, and is not EU law. Its procedural scope matters more than a quick headline.

In the European Union, Directive 2019/790 contains text-and-data-mining exceptions: Article 3 concerns specified research uses and Article 4 other uses under conditions, including rights reservations. It is an EU framework for reproductions and extractions; it does not itself answer ownership of weights or replace national application.

Resulting weights

Weights are numerical parameters adjusted through training. They are not the input dataset or a particular answer. This is where confident claims outrun settled law. A company may treat unpublished weights as valuable confidential information. EU Directive 2016/943 protects secret information with commercial value when reasonable steps have been taken to keep it secret. That may matter for a closed model, but depends on facts and applicable law; it does not automatically make every weight a trade secret.

Contract is another route. A licence can grant permission to download, use or redistribute published weights. The Llama 3.3 licence illustrates that mechanism. A licence organises permissions between parties; it does not by itself decide every claim by training-data authors or create a general court ruling on copyright in weights.

Open weights therefore do not mean ownerless weights or rule-free weights. They can mean a rightsholder or licensor permits defined uses on conditions. Closed weights do not prove a specific copyright in every number either: secrecy, contract, security or business strategy may explain the choice.

Outputs

An output is text, image, code or audio generated in use. Its debate is not identical to training or weights. The U.S. Copyright Office, addressing output copyrightability, says protection depends on sufficient human authorship. That U.S. administrative position does not decide ownership of weights and is not an EU rule.

An output can also raise questions about similarity to a work, platform contracts or personal data. None is answered by saying “AI made it” or “the model is open.” Identify the output, alleged source, jurisdiction and invoked right.

A checklist for the next claim

Ask: is the dispute about data, weights or an output? In which country and court? Is the source a complaint, judgment, licence or commentary? What is the date and scope of the decision? If it concerns weights, is copyright, trade secret, contract or another doctrine alleged?

Do not end with a winner prediction. Watch documents that can change the map: judgments reasoning about the specific object, appeals, applicable legislation and licences defining permissions. Until then, “not decided” is not evasive. It is the accurate description of the field.