Once the embeddings are trained, the gender protected attribute can be simply removed from the vector representation, therefore eliminating any gender bias present in it. The transformations proposed by both<cite> Bolukbasi et al. (2016)</cite> and Zhao et al. (2018b) are downstream task-agnostic. This fact is used in the work of Gonen and Goldberg (2019) to showcase that, while apparently the embedding information is removed, there is still gender information remaining in the vector representations.