For instance, rejecting behavior as not being abusive because it is outside the scope of our classification can cause substantial harm to victims (Blackwell et al., 2017), tacitly involving the NLP community in algorithmic bias that sanctions certain forms of abuse.
categorization is particularly thorny: a broad categorization is likely too computationally inefficient, yet a narrow categorization risks further marginalizing affected community members and can lead to lasting harm.