Meta Removes Face-Recognition Code From Smart Glasses

Reporting by WIRED identified an unreleased face-recognition feature called NameTag embedded in the code of the Meta AI companion app, which WIRED says is installed on more than 50 million devices. WIRED and Gizmodo report the code was exploratory and not enabled, and that Meta removed the face-recognition libraries from the latest app build after the story surfaced. Gizmodo reports Meta communications VP Andy Stone called the coverage "intellectually dishonest" and "pure advocacy-driven click bait," while CTO Andrew Bosworth called it "absolutely dishonest"; neither disputed that the code existed. Reporting notes Meta has explored facial recognition for its Ray-Ban smart glasses since at least 2021, and that a New York Times report this year described an internal memo indicating plans to add the feature. Stone told WIRED that "no final decision has been made on what to do here, if anything."
What happened
Reporting by WIRED uncovered an unreleased face-recognition system, reported as named NameTag, embedded but not enabled in the Meta AI companion app, which WIRED says is installed on more than 50 million phones. The system was reportedly designed to identify people seen through Meta's Ray-Ban smart glasses and alert the wearer to their identity. After the reporting, Meta removed the face-recognition libraries from the latest version of the app available for download, per WIRED and Gizmodo. Meta communications VP Andy Stone publicly objected, writing that the coverage was "more than shoddy reporting, it's intellectually dishonest" and "pure advocacy-driven click bait"; CTO Andrew Bosworth called it "incredibly misleading" and "absolutely dishonest," per Gizmodo. Neither disputed that the code existed. Stone told WIRED, "No final decision has been made on what to do here, if anything."
Editorial analysis - technical context
Facial recognition on wearable cameras couples a recognizable set of trade-offs common across vendors: a face-detection and alignment stage, a face-embedding model, and a reference database for matching. On-device matching reduces continuous network exposure but increases local storage and compute; cloud matching lowers device cost but adds telemetry, latency, and legal complexity. False positives, threshold tuning, and dataset bias are recurring failure modes that magnify privacy and safety concerns in always-on or opportunistic capture.
Industry context
Gizmodo and WIRED place the incident in a longer timeline: Meta discussed facial recognition for smart glasses as early as 2021, and a New York Times report this year described an internal memo indicating the company planned to add the feature. Editorial analysis: Prototyping identification features for consumer wearables draws elevated scrutiny because it changes the risk calculus for bystanders; unshipped but present code in widely distributed apps adds reputational and regulatory exposure even when inactive.
What to watch
Watch whether Meta publishes a privacy or technical rationale, whether the code reappears in future builds, and whether regulators or privacy advocates open inquiries. Third-party audits of subsequent app builds can confirm whether removal was complete or temporary. For practitioners, note how platform permissions and app-store review adapt to manage exploratory but sensitive features in consumer apps.
Key Points
- 1WIRED found unreleased NameTag face-recognition code in the Meta AI app (50M+ installs); Meta removed the libraries after the report.
- 2Meta executives publicly disputed the framing - Andy Stone called it "intellectually dishonest" - but did not dispute the code's existence.
- 3Exploratory identity-matching in widely shipped apps is a privacy and regulatory liability even when the feature is inactive.
Scoring Rationale
Unreleased face-recognition code found in an app installed on more than 50 million devices, then pulled after reporting, is a notable privacy and trust incident with real product-governance and regulatory implications for wearable AI. It is not a technical breakthrough, and no feature shipped, so it sits in the mid-notable range rather than higher.
Sources
Public references used for this report.
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