Microsoft claims its facial recognition technology just got a little less awful. Earlier this year, a study by MIT researchers found that tools from IBM, Microsoft, and Chinese company Megvii could correctly identify light-skinned men with 99-percent accuracy. But it incorrectly identified darker-skinned women as often as one-third of the time. Now imagine a computer incorrectly flagging an image at an airport or in a police database, and you can see how dangerous those errors could be. Microsoft's software performed poorly in the study.
A team of engineering researchers from the University of Toronto has created an algorithm to dynamically disrupt facial recognition systems. Led by professor Parham Aarabi and graduate student Avishek Bose, the team used a deep learning technique called "adversarial training", which pits two artificial intelligence algorithms against each other. Aarabi and Bose designed a set of two neural networks, the first one identifies faces and the other works on disrupting the facial recognition task of the first. The two constantly battle and learn from each other, setting up an ongoing AI arms race. "The disruptive AI can'attack' what the neural net for the face detection is looking for," Bose said in an interview.
Data brokers already buy and sell detailed profiles that describe who you are. They track your public records and your online behavior to figure out your age, your gender, your relationship status, your exact location, how much money you make, which supermarket you shop at, and on and on and on. It's entirely reasonable to wonder how companies are collecting and using images of you, too. Facebook already uses facial recognition software to tag individual people in photos. Apple's new app, Clips, recognizes individuals in the videos you take.
The Department of Homeland Security (DHS) is trialing a new facial recognition technology at US borders aimed at keeping track of people as the enter and exit the country. Called the Vehicle Face System, the project is being spearheaded by Customs and Border Protection at the Anzalduas Border Crossing, located at the southern tip of Texas, in August, according to the Verge. Sophisticated cameras will take photos of people arriving and departing the US and match them with government documents like visas and passports. The cameras are expected to remain in operation at the crossing for a full year. A customs spokesperson told the Verge that the purpose of the project will be to'evaluate capturing facial biometrics of travelers entering and departing the US and compare those images to photos on file in government holdings'.
The Facial Recognition Technology Is Known to Have Gained a Foothold in Many Industry Verticals and It Keeps on Continuously Charting New Ground. Facial Recognition has gained so much traction in an entire host of verticals and applications (according to Variant Market Research, its market is expected to be worth some $ 15.4 billion by 2024) that most anyone, regardless of the kind of business they are in, should look into whether the technology could come in handy in reaching their business objectives. In part, this is owing to the ability of the Facial Recognition technology to better equip and advance the field of expertise known as Marketing, - something universal and of the utmost importance to most industries. Moreover, Face Recognition can make a dent in precisely those areas of Marketing, in which the now rampant Digital Marketing falls short, or is, simply, irrelevant. What are those areas, how much headway has been made already and what are the potentialities one should be aware of?