The robot that became racist: AI that learnt from the web finds white-sounding names 'pleasant' and black-sounding names are 'unpleasant'

Humans look to the power of machine learning to make better and more effective decisions. However, it seems that some algorithms are learning more than just how to recognize patterns - they are being taught how to be as biased as the humans they learn from. Researchers found that a widely used AI characterizes black-sounding names as'unpleasant', which they believe is a result of our own human prejudice hidden in the data it learns from on the World Wide Web. Researchers found that a widely used AI characterizes black-sounding names as'unpleasant', which they believe is a result of our own human prejudice hidden in the data it learns from on the World Wide Web Machine learning has been adopted to make a range of decisions, from approving loans to determining what kind of health insurance, reports Jordan Pearson with Motherboard. A recent example was reported by Pro Publica in May, when an algorithm used by officials in Florida automatically rated a more seasoned white criminal as being a lower risk of committing a future crime, than a black offender with only misdemeanors on her record.