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Meta faces lawsuit over AI and face-recognition training data

Families Sue Meta Over Alleged Use of Photos for Facial Recognition and AI

A proposed class action filed in federal court in Chicago accuses Meta of using Facebook and Instagram photos without consent to develop facial-recognition technology and train generative artificial intelligence systems.

The plaintiffs, parents and children from Illinois and California, allege that Meta extracted biometric information in violation of privacy laws in both states. They contend that images may have been used to create “faceprints” for NameTag, an unreleased feature designed for Meta’s smart glasses, and to train the company’s Emu and Muse Image models.

Code for NameTag was found in Meta’s AI companion app, although the feature was not available to consumers. The system was designed to convert faces captured by smart glasses into biometric signatures and compare them with data stored on a user’s phone. Meta later removed the code and said it was not creating a universal or central facial database.

The complaint acknowledges that Meta has not disclosed which images, if any, supplied biometric data for NameTag. It cites employee comments, patents, and descriptions of Meta’s AI training practices as evidence. Meta said Facebook and Instagram content helped train Emu, while a Muse Image feature that generated images based on public Instagram accounts was withdrawn after criticism.

Meta called the lawsuit meritless and said it has been transparent about its use of information. The company emphasized that NameTag has not been released and that no decision has been made about the feature.

The class could include millions of people whose images appeared on Meta platforms or were submitted to its AI systems since September 4, 2021. Plaintiffs seek damages and injunctive relief.

Meta previously paid $650 million to settle an Illinois biometric privacy case and $1.4 billion to resolve allegations in Texas. The lawsuit is at an early stage, and its claims have not been adjudicated.

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