  The goal of question answering (QA) is to answer any question. However, major
QA datasets have skewed distributions over gender, profession, and nationality.
Despite that skew, model accuracy analysis reveals little evidence that
accuracy is lower for people based on gender or nationality; instead, there is
more variation on professions (question topic). But QA's lack of representation
could itself hide evidence of bias, necessitating QA datasets that better
represent global diversity.
