Getty files US lawsuit against Stable Diffusion maker for copyright infringement

Stock photo database Getty Images has sued Stable Diffusion maker Stability AI in the US. According to Getty, his images were used improperly to develop the Stable Diffusion tool. The company previously started a business in the United Kingdom.

In the suit, filed in a Delaware court, calls Getty Images a “brutal infringement on a staggering scale of Getty Images’ intellectual property.” The stock photo database company claims that Stability AI copied more than 12 million photos from the Getty Images collection, including associated explanations and metadata, for the purpose of training the AI ​​model, without permission or compensation. Getty argues that these actions of Stability AI are aimed at building a competitive business. The stock photo database also states that the output of Stable Diffusion often contains a modified version of a Getty Images watermark, which can cause confusion.

Last month, Getty Images was already a case against Stability AI started at London’s High Court of Justice, although it has not yet officially started. In accordance with that procedure, Getty first sent a letter to Stability AI, after which the Stable Diffusion maker must respond within a certain period. Speaking of this lawsuit, Getty’s CEO said his company wants clarity on its use of copyrighted material for AI purposes. The AI ​​developers usually say that their use falls under fair use.

The case in the US will in any case revolve around the interpretation of the fair use doctrine. Earlier, some artists also filed a collective case against Stability AI, but according to a copyright attorney Getty’s new US case is better than the class action because Getty focuses on the stage where copyrighted images are inserted to train the model.

Due to concerns about copyright infringement or not, Getty previously banned AI-generated imagery from uploading. Stability AI previously decided to introduce an option for rights holders to opt out of Stable Diffusion so that their work is no longer used to train the model.

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