Science may have cured biased AI

Scientists at Columbia and Lehigh Universities have effectively created a method for error-correcting deep learning networks. With the tool, they've been able to reverse-engineer complex AI, thus providing a work-around for the mysterious'black box' problem. Deep learning AI systems often make decisions inside a black box – meaning humans can't readily understand why a neural-network chose one solution over another. This exists because machines can perform millions of tests in short amounts of time, come up with a solution, and move on to performing millions more tests to come up with a better solution. The researchers created DeepXplore, software that exposes flaws in a neural-network by tricking it into making mistakes.