Mark Zuckerberg’s Meta Set to Experiment Facial Recognition to Boost security on Facebook and Instagram
Meta is reinstating facial recognition technology to its platforms, more than three years after Facebook discontinued its “face recognition” tool because of significant concerns over the technology.
The social media giant disclosed this on its official page seen by Newsng on Tuesday.
Meta said it will enrol approximately 50,000 prominent personalities in a pilot that will automatically compare their Facebook profile photos to those used in suspected scam adverts.
If the photos match and Meta suspects the advertising is fraudulent, it will ban them.
The celebs will be notified of their enrolment and given the option to opt-out if they do not wish to participate, according to the business.
“Now, we’re testing a new way of detecting celeb-bait scams.
“If our systems suspect that an ad may be a scam that contains the image of a public figure at risk for celeb bait, we will try to use facial recognition technology to compare faces in the ad to the public figure’s Facebook and Instagram profile pictures.
“If we confirm a match and determine the ad is a scam, we’ll block it.
“We immediately delete any facial data generated from ads for this one-time comparison, regardless of whether our system finds a match, and we don’t use it for any other purpose.”
The trial will be launched globally beginning in December, except for some big jurisdictions where it does not have regulatory authorisation, such as the United Kingdom, the European Union, South Korea, and the US states of Texas and Illinois, according to the business.
Meta had already experienced hurdles in implementing facial recognition, with privacy activists citing fears that such data may be used for harmful purposes if it falls into the wrong hands.
In 2021, Meta completely shut down its facial recognition operations on Facebook, as part of a broader policy shift aimed at distancing the site from past problems.
We earlier reported that Meta has launched a new artificial intelligence model called the “Self-Taught Evaluator,” which aims to dramatically reduce human involvement in AI training and evaluation.
