Bias is an overloaded word. It has multiple meanings, from mathematics to sewing to machine learning, and as a result it’s easily misinterpreted. When people say an AI model is biased, they usually mean that the model is performing badly. But ironically, poor model performance is often caused by various kinds of actual bias in the data or algorithm. Machine learning algorithms do precisely what they are taught to do and are only as good as their mathematical construction and the data they are trained on. Algorithms that are biased will end up doing things that reflect that bias. To…

This story continues at The Next Web