Machine learning approaches this problem by providing the neural network many example (training) images labeled as images of “a person wearing glasses”. The neural network learns the relationship between images and their labels, and extracts data patterns, or features, that it needs to focus on to make a determination. One of the reasons AI systems are considered a black box is because it is often difficult to describe mathematically what criteria the systems are actually using to make their predictions, including potential biases.