Facebook has its own version of Apple’s Face ID. If you get locked out of your Facebook account, the company is testing a way to regain access by using your face to verify your identity. That could be especially useful if you’re somewhere that you can’t receive two-factor authentication SMS, like on a plane or while traveling abroad, or if you lose access to your email account.
Social media researcher Devesh Logendran (a pseudonym) sent a screenshot of the feature to TNW’s Matt Navarra. We asked Facebook about it and got this confirmation:
“We are testing a new feature for people who want to quickly and easily verify account ownership during the account recovery process. This optional feature is available only on devices you’ve already used to log in. It is another step, alongside two-factor authentication via SMS, that were taking to make sure account owners can confirm their identity.”
If the feature proves reliably helpful to users and isn’t fooled by hackers, Facebook could potentially roll it out to more people.
Over the years Facebook has tried a number of novel ways to help you get back into a locked account. In some cases it asks you to identify photos of your friends to prove you’re you. Or it’s tried allowing you to designate several “trusted friends” who receive a code that you can ask them for to unlock your account.
While Facebook has experienced some backlash to facial recognition for photo tag suggestions in the past, this feature would only use the technology to privately help you out. Therefore it shouldn’t engender as big of privacy concerns, though obviously anything related to biometric data can give people pause. But if it means you can get back to your messages and News Feed, or repair damage done by a hacker, many people are likely to be comfortable to use their face to Facebook.
Apple is keen to replace the iPhone’s fingerprint scanning system with more secure 3-D facial-recognition technology, according to Bloomberg.
The company’s goal to do away with Touch ID, its fingerprint identity sensor that has been used to unlock iPhones models launched since 2013, is expected to occur in time for the launch of the iPhone 8, due to be released later this year. People familiar with the product’s development claim that the new facial-recognition technology will feature a 3-D sensor capable of scanning faces and unlocking iPhones within a few hundred milliseconds.
The sensor will also be used to authenticate payments and launch secure apps and has reportedly been designed so that users don’t have to hold the device close to their face — laying the phone flat on a table is sufficient enough to gain access. Bloomberg’s sources add that Apple’s facial-recognition technology, which is still in development and may not be ready in time to feature on the new iPhone, is more secure than Touch ID as it takes in more data points.
Apple is also said to be in process of testing eye-scanning technology to supplement its new system. By using 3-D sensors, it hopes to avoid running into the same issues that dogged Samsung (SSNLF). The South Korean company’s Galaxy G8 smartphone featured iris scanners that could be breached by placing a printed photo copy of the user’s eyes in front of it.
Aside from introducing a face-unlocking feature, Apple’s new iPhone is set to include an artificial intelligence chip. Called the Apple Neural Engine, the chip’s ability to handle tasks, such as image recognition and typing suggestions, is expected to improve battery life. The iPhone 8 will also feature screens capable of displaying content at a higher frame rate.
The addition of these complex features has led to concerns that the iPhone 8’s launch date might be delayed and hindered by costly production issues. Some analysts are also concerned that the expected retail price of $1,000 may put consumers off buying it.
A business school in Paris will soon begin using artificial intelligence and facial analysis to determine whether students are paying attention in class. The software, called Nestor, will be used two online classes at the ESG business school beginning in September. LCA Learning, the company that created Nestor, presented the technology at an event at the United Nations in New York last week.
The idea, according to LCA founder Marcel Saucet, is to use the data that Nestor collects to improve the performance of both students and professors. The software uses students’ webcams to analyze eye movements and facial expressions and determine whether students are paying attention to a video lecture. It then formulates quizzes based on the content covered during moments of inattentiveness. Professors would also be able to identify moments when students’ attention waned, which could help to improve their teaching, Saucet says.
At first, the technology will only be used for students who watch lectures remotely, though Saucet hopes to eventually launch an in-class version that would send real-time notifications to students whenever they’re not paying attention. Speaking to journalists during a demonstration at ESG’s Paris campus last month, Saucet said the technology could vastly improve the performance of students who take massive open online courses, or MOOCs.
“The problem with MOOCs is that they don’t work,” Saucet said. “It’s been 10 years that we’ve been trying e-learning, and in the US it’s been 25 years. And it doesn’t work.”
A press release from the UN’s World Council of Peoples, which hosted last week’s event, described the launch of Nestor as the “first AI led class,” though that’s not entirely accurate. The software is not capable of actually teaching a course, and it’s not the first time that schools have experimented with similar technologies. The IE Business School in Madrid recently created a WOW Room (the acronym stands for “Window on the World”), where professors stand before a wall of screens and lecture students who tune in from afar. Like Nestor, the system uses “emotion recognition systems” to measure students’ attention.
Advocates for AI in education say the technology could be used as a digital tutor that would adapt to a student’s individual needs, and help foster more effective studying habits. Such software could also help teachers by providing quantitative feedback on the effectiveness of their teaching, advocates say. Some researchers have even raised the prospect of AI acting as a “lifelong learning companion” that would accompany students for years.
But AI programs rely on massive troves of personal data, and there are concerns over how such data would be treated. A personalized learning program launched in New York by InBloom, a data analytics company, collapsed in 2014 amid growing concerns over how data on students would be used and protected from hackers.
Saucet says Nestor won’t store any of the video footage it captures and that his company has no plans to sell any other data the software collects. (His company sells its software to schools.) The data would also be encrypted and anonymized, he says. In addition to facial recognition and analysis, the software can integrate with students’ calendars to suggest possible study times, and track their online behavior to pick up on patterns. If a student typically spends their weeknights watching YouTube videos, for example, Nestor could suggest that they instead spend that time studying. Saucet acknowledges, however, that it will ultimately be up to each school to decide how to treat and store such data.