The following study aims to determine whether discrimination contributes to the low percentage of women in math and science careers by designing an experiment to isolate discrimination’s potential effects. Without provision of information about candidates other than their appearance, men are twice more likely to be hired for a mathematical task than women. The study shows that implicit stereotypes (as measured by the Implicit Association Test) predict not only the initial bias in beliefs but also the suboptimal updating of gender-related expectations when performance-related information comes from the subjects themselves.