How to Make Artificial Intelligence Less Biased

As artificial intelligence spreads into more areas of public and private life, one thing has become abundantly clear: It can be just as biased as we are. AI systems have been shown to be less accurate at identifying the faces of dark-skinned women, to give women lower credit-card limits than their husbands, and to be more likely to incorrectly predict that Black defendants will commit future crimes than whites. Racial and gender bias has been found in job-search ads, software for predicting health risks and searches for images of CEOs. How could software designed to take the bias out of decision making, to be as objective as possible, produce these kinds of outcomes? After all, the purpose of artificial intelligence is to take millions of pieces of data and from them make predictions that are as error-free as possible.