Invisible Women: Data Bias in a World Designed for Men

It is not a new phenomenon that women are absent from historical accounts, film, literature, science, and “everywhere” (xv). Though not necessarily intentional, this absence impacts women’s lives.

Now, given societal reliance on data, the context has changed. The absence of women in data sets causes biases in artificial intelligence. In particular, data systems fail to factor in women’s experiences with respect to the body, the unpaid care burden, and male violence against women. The male body and men’s life experiences are presented as gender neutral when, in fact, they are not.

Perez distinguishes sex, or a person’s biological characteristics, and gender, which includes the “social meanings we impose upon those biological facts” (xvii). The data gap arises because of gender, not sex—problems arise from thinking of humanity as male.

After highlighting the many ways in which maleness is the universal standard, Perez then demonstrates how women are consequentially negatively impacted.

In the narrative of human development and evolution, there is a persistent bias. Evolutionary theory over-emphasizes the importance of hunting, but for a long time assumed that women had never been warriors despite physical evidence to the contrary.