Facing Obstacles Head-on For all its potential, facial recognition technology must address fundamental challenges before an algorithm reaches a camera or mobile device. According to one study, face recognition systems are 5-10 percent less accurate when trying to identify African Americans compared to white subjects.
What’s more, female subjects were more difficult to recognize than males, and younger subjects were more difficult to identify than adults. As such, algorithm developers must focus more on the content and quality of the training data so that data sets are evenly distributed across demographics. Testing the face recognition system, a service currently offered by the National Institute of Standards and Technology (NIST), can improve accuracy.