Google researchers develop a test for machine learning bias - SiliconANGLE

A team of researchers at Google Inc. has developed a method for testing whether or not machine learning algorithms inject bias, such as gender or racial bias, into their decision-making processes. For some time, concerns have been raised about the possibility that machine learning algorithms are injecting bias into applications such as advertising, credit, education, employment and justice. Recent examples include a crime prediction algorithm that targeted black neighborhoods and an online advertising platform that was found to show highly paid executive jobs to men more often than women. "Decisions based on machine learning can be both incredibly useful and have a profound impact on our lives," said Moritz Hardt, a senior research scientist at Google, who co-authored the paper, Equality of Opportunity in Supervised Learning. "Despite the demand, a vetted methodology for avoiding discrimination against protected attributes in machine learning is lacking."