MIT CSAIL researchers propose automated method for debiasing AI algorithms

Bias in algorithms is more common than you might think. An academic paper in 2012 showed that facial recognition systems from vendor Cognitec performed 5 to 10 percent worse on African Americans than on Caucasians, and researchers in 2011 found that models developed in China, Japan, and South Korea had difficulty distinguishing between Caucasians and East Asians. In another recent study, popular smart speakers made by Google and Amazon were found to be 30 percent less likely to understand non-American accents than those of native-born users. And a 2016 paper concluded that word embeddings in Google News articles tended to exhibit female and male gender stereotypes. The good news is, researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (MIT CSAIL) are working toward a solution.