Doubao denies Hengdian extras data fed ByteDance models

Doubao public relations lead Liu Xing pushed back publicly on October 28 against a widely circulated claim that Hengdian and ByteDance had fed the portraits and voices of 150,000 film extras into a ByteDance model, calling the story seriously inaccurate. The response was picked up by multiple Chinese outlets the same day, and the real question at its center is not whether film production should use AI but who owns the data in the Hengdian film AI platform, how it is licensed, and what it is used for.

According to Liu, the Hengdian film AI service platform is intended as public digital infrastructure: it turns assets such as the studio's physical locations into high-quality datasets so that production crews can scout, prepare and shoot more efficiently, while lowering the barrier for smaller film companies to use AI and giving more creators a chance to make their work well. That positioning differs fundamentally from the rumor, which described a bulk transfer of extras' likenesses and voices into training data.

The division of roles was spelled out as well. Liu said Volcano Engine is the technical support provider on the project, that all data assets belong to Hengdian or the parties that authorized them, and that any use of a person's likeness or voice requires that person's consent. He also stated plainly that the project's data will not be used to train ByteDance models.

Those statements mark out the three boundaries that matter most in AI data disputes: who holds ownership, how consent is obtained before use, and what the data is ultimately used for. A film studio and its extras are close to a worst-case setting for this, since the material is full of identifiable faces and voices, and any ambiguity about purpose can turn an industry partnership into a public controversy.

In a broader sense, this kind of public clarification has become routine for Chinese model developers. As scrutiny of data provenance and licensing chains intensifies, vendors increasingly have to separate their role as technology provider from the data holder's role, and to say explicitly which data stays out of the training set. The value of the response is less in refuting one rumor than in putting the project's compliance framework on the record.

What to watch now is whether that framework survives contact with verifiable detail: whether the consent mechanism is transparent to the people involved, whether the dataset's permitted uses are set out in writing, and how quickly the platform actually ships in scouting, preparation and shooting. For the film industry, a working public dataset really could lower the cost of using AI, but only if every likeness and voice can be traced back to clear consent.