As the word embedding model is a fundamental component in many NLP systems, mitigating bias in embeddings plays a key role in the reduction of bias that is propagated to downstream tasks (e.g., (Zhao et al., 2018a)).
it is debatable if debiasing word embeddings is a philosophically right step towards mitigating bias in NLP.