For word representations,<cite> Bolukbasi et al. (2016)</cite> and Caliskan et al. (2017) show that word embeddings encode societal biases about gender roles and occupations, e.g. engineers are stereotypically men, and nurses are stereotypically women. As a consequence, downstream applications that use these pretrained word embeddings also reflect this bias.