Researchers tackle racial, gender bias in artificial intelligence Toronto Star

When Timnit Gebru was a student at Stanford University's prestigious Artificial Intelligence Lab, she ran a project that used Google Street View images of cars to determine the demographic makeup of towns and cities across the U.S. While the AI algorithms did a credible job of predicting income levels and political leanings in a given area, Gebru says her work was susceptible to bias -- racial, gender, socio-economic. She was also horrified by a ProPublica report that found a computer program widely used to predict whether a criminal will reoffend discriminated against people of colour. So this year, Gebru, 34, joined a Microsoft Corp. team called FATE -- for Fairness, Accountability, Transparency and Ethics in AI. The program was set up three years ago to ferret out biases that creep into AI data and can skew results.