Encoding biases into machine learning models, and in general into the constructs we refer to as AI, is nearly inescapable — but we can sure do better than we have in past years. IBM is hoping that a new database of a million faces more reflective of those in the real world will help. Facial recognition is being relied on for everything from unlocking your phone to your front door, and is being used to estimate your mood or likelihood to commit criminal acts — and we may as well admit many of these applications are bunk. But even the good ones often fail simple tests like working adequately with people of certain skin tones or ages.
Bias is one of the known cons of Artificial Intelligence and the only way to address is to add a bigger data set. IBM has released its new Diversity in Faces (DiF) image set, comprised of 1M faces taken from a 100M image data set, to help reduce bias in AI. Read more about it on Techcrunch.