Artificial intelligence may not be human, but that doesn't make it exempt from the kind of bias almost every person displays. That's because we've been building prejudice into our AI, which learns both the good and the bad from human creators. It's a problem, scientists say, with a hidden benefit: By trying to understand how machines pick up human bias, we might in turn be able to learn how we acquire those biases ourselves. In 2017, Joanna Bryson, a computer scientist and AI specialist at the University of Bath, fed around 840 billion words--from tweets, the US Declaration of Independence, Reddit threads, and many other sources--into a purely statistical machine-learning model to see whether it would form biases based on the implicit linguistic patterns it found. Next, she told the machine to create related clusters of words.