While the seminal work by Bolukbasi et al. (2016a <cite>Bolukbasi et al. ( , 2016b</cite> concerns the identification and mitigation of gender bias in pretrained word embeddings, Zhao et al. (2018) provide insights into the possibilities of learning embeddings that are gender neutral.