‘Black box’ no more: This system can spot the bias in those algorithms

Between recent controversies over Facebook’s Trending Topics feature and the U.S. legal system’s “risk assessment” scores in dealing with criminal defendants, there’s probably never been broader interest in the mysterious algorithms that are making decisions about our lives. That mystery may not last much longer. Researchers from Carnegie Mellon University announced this week that they’ve developed a method to help uncover the biases that can be encoded in those decision-making tools. Machine learning algorithms don’t just drive the personal recommendations we see on Netflix or Amazon. Increasingly, they play a key role in decisions about credit, healthcare, and job opportunities, among other things. [ CIO.com and Drexel to honor 50 analytics innovators. Nominate your analytics project today! ] So far, they’ve remained largely obscure, prompting increasingly vocal calls for what’s known…


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