The report states that the feature, known internally as “Name Tag”, would allow users to identify people they are looking at and receive information about them through the company’s AI assistant. 

If approved, it would be a big step in how Meta integrates artificial intelligence into wearable devices.

Company discussions about the feature began early last year. Executives have weighed how to release a tool that carries what the report describes as “safety and privacy risks”. The final decision has not been confirmed, and plans could still change.

An internal memo quoted in the report shows that Meta once considered rolling out “Name Tag” to attendees at a conference for the visually impaired before making it widely available. That launch did not happen.

The same document also says the company has thought carefully about timing. “We will launch during a dynamic political environment where many civil society groups that we would expect to attack us would have their resources focused on other concerns,” the document reads.

Meta had explored adding facial recognition to the first version of its Ray-Ban smart glasses in 2021. At the time, the company dropped the idea, pointing to technical limits and ethical issues. 

Now, after stronger sales of its smart glasses and closer ties between technology firms and the current US administration, the proposal has returned to the table.

According to the report, Mark Zuckerberg sees facial recognition as a way to make the company’s AI assistant more useful and to distinguish its glasses from competing products.

Meta has not publicly confirmed when or if the feature will be released.

Aiming to tackle “celeb-bait” scams, the trial, set to begin in December, will enrol around 50,000 public figures whose Facebook profile pictures will be compared to images used in suspected scam ads.

If a match is found, Meta will block the offending advertisement. Celebrities involved will be notified and given the option to opt out of the programme. 

The initiative will be implemented globally, with exceptions in regions such as the UK, the EU, South Korea, and select U.S. states where regulatory clearance is still pending.

Monika Bickert, Meta’s vice president of Content Policy, noted that this new feature is one of the company’s tactics to protect public figures from scams that exploit their likeness without consent. “We aim to provide as much protection as possible,” Bickert stated, adding that public figures can easily opt-out if they prefer not to participate.

The announcement follows a challenging period for Meta in addressing privacy issues. In 2021, the company shut down its previous facial recognition system, due to societal concerns, and more recently faced a $1.4 billion fine in Texas over accusations of improperly collecting biometric data.

Despite these setbacks, Meta is pushing forward with this targeted use of facial recognition technology, aiming to strike a balance between fighting the growing threat of scam ads and respecting privacy boundaries. 

Meta has promised to delete all facial data used in the comparison process immediately, ensuring that it will not be stored or reused for other purposes.

In addition to tackling scams, the company is also testing the use of facial recognition to help users regain access to compromised accounts, ensuring a more secure alternative to traditional document-based verification methods. 

Below are various tech solutions that can be employed to combat kidnapping in Nigeria:

1. GPS Tracking and Monitoring:

The implementation of GPS trackers in vehicles and wearable devices for individuals can enable real-time tracking and reporting in case of kidnappings. For instance, individuals can trigger an alert through their wearable GPS device if they are being kidnapped, enabling authorities to track and respond quickly.

2. Mobile Apps for Reporting and Response:

Developing mobile apps to report kidnappings and suspicious activities can provide a direct channel for individuals to seek help and for authorities to respond swiftly. These apps could also provide real-time updates on security situations and safe zones.

3. Drone Surveillance:

Utilizing drones equipped with cameras and sensors for surveillance in high-risk areas can aid in gathering critical intelligence on kidnappers’ movements and hideouts. This information can be vital in planning and executing strategic rescue missions.

4. Biometric Identification Systems:

Biometric technology such as facial recognition and fingerprint scanning can aid in identifying and tracking down kidnappers, as well as verifying victims’ identities to facilitate their safe return to their families.

5. Public Awareness Campaigns:

Using social media platforms, messaging apps, and digital tools to disseminate information and resources can raise awareness about the risks of kidnapping.

These campaigns can educate the public on safety measures and provide support for at-risk communities.

These examples showcase how technology can be leveraged to tackle the kidnapping epidemic in Nigeria, offering a multifaceted approach to address this pressing issue.

With the implementation of these tech solutions, there is a potential to significantly reduce the prevalence of kidnappings and improve the safety and security of communities.

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Recording and recalling faces is so intuitive that there is even a condition called prosopagnosia, which occurs when someone struggles to remember faces.

Not surprisingly, scientists have discovered our brains have areas dedicated solely to managing information about faces.

Humans are very social creatures, and we rely on quickly identifying friends from foes in a group of faces.

Ever since we invented computers, we’ve aimed to endow them with the same abilities. Today, we have computers that understand human speech, translate languages, and recognise our faces.

Facial recognition biometrics are today more accurate than the human eye can ever be.

Facial recognition is already used extensively to identify individuals, help prevent crimes such as fraud and make it easier for people to authenticate and access services through their digital identity. We already unlock our phones with a glance nearly 400 times a day.

Imagine if we could pop into the doctor’s office or breeze through airports using our faces to unlock everything, safely and securely.

Until recently, there have been two key limitations around facial recognition. The first is scale. Finding a face amongst thousands, millions, or billions without any reference, like an ID, to narrow the search, is like looking for a needle in a haystack. It’s very intensive and time-consuming, sometimes more so than what makes the process worthwhile.

Then there are important privacy concerns. For such a system to work fast, it often relies on other personal data, such as your ID, e-mail, or mobile number. If someone were to access that data used alongside your photo, they could learn a lot about you.

Exciting new developments in this space are resolving these issues. Specifically, a technology called CryptoNets using fully homomorphic encryption is changing how fast and securely computers can identify a face. It’s a very technical breakthrough, so let’s keep it simple.

CryptoNets uses artificial intelligence and new types of encryption to deliver on two fronts. It is very fast, locating a face among countless others in milliseconds without the need to have any other data to narrow the search.

It is also highly efficient, requiring far fewer computing resources than other types of facial recognition when making one-to-many comparisons or the traditional one-to-one face comparisons.

The technology is also great for privacy. Information encrypted through CryptoNets becomes anonymized data and no longer contains personal information. It is useless without the system, which itself doesn’t need to decrypt the information to use it.

So, there is no point in stealing that personal information. Notably, CryptoNets technology converts material such as photos or voiceprints into a different data format that cannot be used outside the CryptoNets context.

The result is a new biometric technology that is much faster, far more secure, naturally compliant with personal information laws such as POPIA and GDPR, and applicable to different forms of recognition.

CrytoNets technology also supports voice, fingerprints and so on. And because of how it works, CryptoNets can quickly identify someone using only one element, such as a photo (no need to give your ID number every time you verify yourself), and does so in near real-time, so it works even in large crowds.

Now, many of us become nervous when we think of facial recognition. There is always scope for abuse and mistakes. But facial recognition is not going away – it’s just too helpful. So, we should instead ask how we can make it more responsible and respectful of our privacy.

CryptoNets technology achieves privacy and efficiency goals with incredible results. As it grows more popular, it will improve biometric recognition of all types while keeping our personal information safer. It aligns nicely with a wave of improvements in the sector that promotes better ethics and greater accuracy.

Facial recognition is controversial for many reasons. These are being resolved through breakthroughs such as CryptoNets. From fraud prevention to opening your front door with your voice, it will improve many aspects of our lives in fantastic ways without compromising our safety and privacy.

Digital identity orchestration Company, Contactable, will be the first organization in Africa to pioneer this technology as part of its extended product offerings in the market.