Face recognition code was found in Meta AI

June 5, 2026

by Alimat Aliyeva

The Meta AI application has revealed indications of potential
facial recognition development for Meta Platforms Ray-Ban smart
glasses, reigniting concerns over data privacy and personal
information protection, AzerNEWS reports.

Journalists from Wired analyzed the Meta AI app code for Ray-Ban
and Oakley smart glasses and discovered references to a possible
facial recognition system reportedly called “NameTag,” which has
not been officially announced by the company.

According to the findings, the application—downloaded more than
50 million times—contains components linked to several AI models.
One is designed to detect and recognize faces, another to adjust
facial positioning within the frame, and a third to convert this
data into a format that can be compared with stored templates on a
user’s smartphone.

It is suggested that, if activated, the feature could allow
glasses wearers to receive real-time notifications when familiar
individuals appear in their field of view. In a later version of
the app, this functionality may have been internally rebranded as
“Connections.”

A Meta spokesperson, Ryan Daniels, responding to the Wired
report, stated that the discovered code elements only reflect
early-stage experimentation and do not confirm any publicly
released product. He emphasized that the technology has not been
deployed to users and that no final decision has been made
regarding its implementation.

The company also reiterated that, should such a feature be
introduced, it would be designed with privacy safeguards, including
transparency measures and the absence of a centralized facial
database.

Interestingly, the debate comes at a time when wearable AI
devices are rapidly evolving into “always-on” assistants. Industry
analysts note that while such technology could make everyday
interactions more seamless—such as remembering names in social or
professional settings—it also raises complex ethical questions
about consent, surveillance, and the normalization of real-time
identity tracking in public spaces

  

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