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Sometimes, but not as a rule for every game or every AI system. What a model was trained on depends on its developer, task, dataset, rights arrangements, and jurisdiction. Roblox says some of its systems can use creator content from users who have not opted out, and warns that training data may include material subject to third-party intellectual-property rights. KRAFTON, by contrast, said its inZOI systems used selected images and models it described as commercially permitted, along with motion data it owned or collected. Those are company disclosures, not independent audits.
It also matters that two questions are different: whether a copyrighted work was included in training, and whether that particular use infringed copyright. The first is about the data; the second depends on facts and the law that applies.
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What does it mean to say a game AI was trained on copyrighted work?
Training is the process of using data to develop or adjust a model so it can perform a task, such as generating an image, suggesting code, creating a 3D asset, or turning video into motion. A training set may contain many kinds of material, and different systems from the same company can use different sources.
“Copyrighted” describes a work’s legal status; it does not by itself establish whether a developer had permission to use it, whether an exception applies, or whether the use infringed anyone’s rights. Conversely, a company’s statement that it used permitted material is a description of its approach, not a court ruling or a work-by-work verification of every item.
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So the useful question is not simply “Does game AI use copyrighted work?” It is: Which model, for which task, trained on what data, under which rights basis, and under which jurisdiction’s law? An image generator and a motion-generation system can have different training sources even when they appear in the same game.
What has Roblox disclosed about its training data?
Roblox says its public generative AI systems draw on several categories of data, with the sources varying by system. Its documentation covers creator-facing tools including Code Assist, Material Generator, Assistant, Texture Generator, and Avatar Setup. Roblox also says training data can include material subject to third-party intellectual-property rights. Roblox’s AI data-sharing documentation is a source-category disclosure, not a public inventory of each work used in each model.
Data categories Roblox identifies
- Publicly accessible repositories containing permissively licensed or public-domain material.
- Non-public data obtained from third-party providers through commercial arrangements.
- Platform activity and creator material where the user has not opted out of sharing.
- Internally generated material, including synthetic data.
- Material from annotation services and contractors.
Roblox says its training material may include text and audio text, visual content, annotations, ratings, and preference data. Depending on the system type and version, training may range up to over 3 million distinct assets. That is Roblox’s maximum-range statement in its current Creator Hub documentation, accessed in 2026; it is not a count for every model or a claim that every asset is a creator upload.
What Roblox says creators can control
Roblox’s stated sharing defaults depend on when the content was published. For games, avatar items, and paid assets published before July 10, 2024, sharing is off by default; for those published on or after that date, sharing is on by default. Roblox says that if a creator stops sharing, it removes the content from the training dataset within 30 days and updates models trained using that data within 365 days.
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Those are Roblox’s platform-specific settings and timelines, not a general rule for other games or services. They also do not identify the particular model or works that may have used a given item. The documentation supports a careful statement: Roblox says some creator material may be used when users have not opted out, and that some training data may have third-party IP rights attached. It does not establish the legal status of every item or independently verify each source.
What did KRAFTON say about the AI in inZOI?
In a notice dated May 13, 2025, KRAFTON described separate datasets for three inZOI technologies. The distinctions matter: it did not describe one shared corpus for every AI feature. The figures below are the company’s own disclosures, not independently audited dataset counts.
| inZOI technology | Data KRAFTON said it used | Rights basis described by KRAFTON |
|---|---|---|
| Text-to-image | 20 million publicly available images | Selected images released under Creative Commons licenses permitting commercial use and modification |
| 3D-printing AI | Approximately 46,000 high-quality 3D models | Models owned by KRAFTON or sourced from datasets it said were permitted for commercial use |
| Video-to-motion | Primarily over 1.7 million motion-data samples | Data KRAFTON said it owned and collected, supplemented by a limited number of publicly available open-license datasets |
KRAFTON’s notice gives more task-specific detail than a general statement that a game “uses AI.” Still, the announcement reflects KRAFTON’s account of its sources. A commercial-use license claim does not, on its own, resolve every question about the provenance of each underlying work, the exact terms attached to it, or how those terms apply to a particular use.
Does a game’s AI disclosure tell you what its model was trained on?
Not necessarily. A store listing can disclose that AI-assisted material was created during development or that a game generates content live for players, without identifying the full training corpus behind a model.
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Steam’s developer disclosure policy distinguishes between pre-generated AI-assisted content made during development and live-generated content. That distinction helps players understand how AI features appear in a game. It should not be read as a complete training-data inventory, or as proof that the training data was licensed or unlicensed.
For the same reason, a game’s visible AI feature does not reveal its training history by itself. A developer may integrate a third-party model, use a model trained on its own material, or combine sources. Without a disclosure tied to the particular model and its data, the feature’s presence alone does not establish which works were included.
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Does using copyrighted training material automatically mean infringement?
No. Copyright status and infringement are connected, but they are not the same determination. Whether a specific training use is lawful can depend on the source of the material, the facts of how it was obtained and used, and the applicable law. The reviewed official materials do not establish a single worldwide answer for every model or training practice.
The UK government’s report, published March 18, 2026, says generative AI models are often trained on creative works protected by copyright and that public disclosure by developers is limited. It also describes different national approaches. The report says the UK does not currently generally require AI developers to disclose publicly which copyright works were used to develop a model. It describes EU AI Act requirements for providers of general-purpose AI models to publish sufficiently detailed summaries of training material. These points apply to the named jurisdictions and the report’s date; they are not interchangeable global rules.
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A useful distinction when reading a company statement is whether it identifies a source category, a license basis, or a specific corpus. Each answers a different question. “We used commercial-use-permitted data” describes the rights basis the company claims; it does not necessarily disclose every work, establish that every license was valid, or settle how a court would assess the use.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What does U.S. copyright guidance say about AI training?
The U.S. Copyright Office’s AI study includes a May 9, 2025 pre-publication Part 3 report on generative AI training. Its separate Part 2 announcement, dated January 29, 2025, concerns whether AI-assisted or AI-generated outputs can be copyrighted. The Office said that outputs can receive protection where a human author determines sufficient expressive elements. That is an output-authorship question, not a ruling that all training on copyrighted works is lawful or unlawful.
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How should players and creators interpret these disclosures?
Read a disclosure as evidence of what its publisher says, and note its scope. An industry-wide claim needs broader evidence than a company’s statement about one model. An industry association can provide context, but it is not an independent audit of every studio’s data practices.
Video Games Europe’s April 2024 position paper distinguishes earlier machine-learning uses of company-owned telemetry and game data from generative AI trained on creative assets, where copyright questions arise. That is an industry association’s account and position. It does not establish a complete inventory of the training material used across the games industry.
- Look for the named task. Image, texture, code, 3D-model, and motion systems may use different datasets.
- Separate data source from rights status. “Publicly available” does not necessarily mean public domain; an open license can have terms, and owned material is a different category from third-party uploads.
- Check who is making the claim. A developer notice states the developer’s account. A platform policy explains disclosure requirements. Neither automatically verifies a particular corpus.
- Check the date and region. Defaults, policies, and legal requirements can change, and rules differ across jurisdictions.
- Do not infer the corpus from a storefront label. A disclosure about AI-generated or AI-assisted content is not necessarily a list of training works.
As of the official materials cited here, there is no complete, independently verified inventory of training works across the games industry. That limits any defensible industry-wide conclusion: some providers disclose using creator material or data that may have third-party rights, while others describe selected owned or commercially permitted sources. Neither example stands for every game.
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Can AI-generated art in a game be copyrighted in the United States?
Potentially, if a human author contributes enough original expressive choices; the Copyright Office’s January 2025 explanation treats that as a human-authorship question. Protection for an output does not determine whether the model’s training material was lawfully used.
Does “publicly available” mean an image is free to use in training?
No. Public availability describes accessibility, not necessarily copyright status or permission. A license may allow some uses while carrying conditions, so the stated rights basis and the material’s provenance matter.
Does a Steam AI label identify every dataset a game’s AI used?
No. The disclosure distinction concerns AI-assisted material created during development versus content generated live; it does not automatically provide a model’s full training corpus.
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