Meta Sued Over Training Data for Its AI and Face-Recognition Systems

| Source: Wired AI

Tags: Meta, NameTag, BIPA, biometric-data, class-action, Emu, face-recognition, training-data

A federal class action filed in Chicago alleges Meta illegally harvested Facebook and Instagram photos—without consent—to build NameTag face recognition for its Ray-Ban smart glasses and to train Emu and Muse Image AI models, violating Illinois and California biometric privacy laws.

Details

A federal class action filed in Chicago by Illinois and California parents and children alleges that Meta violated state biometric privacy laws by extracting biometric data from users' Facebook and Instagram photos without notice or consent. The suit targets two systems: NameTag, an unreleased face-recognition feature for Meta's smart glasses, and generative AI models Emu and Muse Image, which Meta has publicly acknowledged training on platform photos. The NameTag allegations build on a June WIRED investigation that found the feature's code secretly embedded in the Meta glasses companion app—which had over 50 million downloads—even though the feature was never activated for users. The app was designed to convert faces captured by the glasses into biometric signatures and compare them against a local faceprint database that received updates from Meta. The lawsuit contends those faceprints may derive from Facebook and Instagram profile images, citing employee claims and a Meta patent on face matching against platform photos. The Emu and Muse Image claims center on Meta's own public statements: CPO Chris Cox described platform images as a 'data advantage' for AI training. Muse Image briefly allowed generating images from others' public Instagram accounts before Meta pulled the feature within days, and the suit cites this as part of a broader pattern of consent failures. Meta denies wrongdoing, saying it is 'not building a universal face database' and will act transparently if NameTag ever ships. Illinois BIPA suits can carry statutory damages of ,000–,000 per violation—at social-media scale, the potential liability is substantial.