Amazon Research Award supports developing algorithms that tackle unfairness in recommendation engines

Why would a recommendation engine not suggest computer science classes to a female college student interested in that field of study?

According to Bert Huang, assistant professor of computer science in the College of Engineering and a faculty member at the Discovery Analytics Center, there are a few reasons. The engine may have trained from data representing the existing gender imbalance in computer science, unfair patterns may have inadvertently emerged from the mathematical nature of its learning algorithm and model, or there may be a less-visible or harder-to-detect process in place.  Click here to read more about Bert’s work.