Invisible Women: Data Bias in a World Designed for Men

How has the gender data gap resulted in harm to women? Using examples from product designs and the medical system, explore the range and types of harm. Does Perez equate these different kinds of harm? Why or why not?

In what ways are women economically penalized for assuming the bulk of responsibilities for care work? How substantial is the economic penalty and why does it matter?

What is the Henry Higgins effect (research the musical My Fair Lady to fully understand the reference)? How does Perez use this term to mock male bias and the exclusion of women from data?

Why is male bias in the tech industry of special concern? What are the possible ramifications of data-poor algorithms for women?

Perez argues that men should not be employed in positions of power over vulnerable women, for instance, as guards in detention centers. How does she support this argument? Would the exclusion of men from such positions violate rights?

How does social class interact with male bias in the workplace to the detriment of poor women?

What is the Yentl syndrome (research the musical Yentl to fully understand the reference)? Why has this been such a problem in medicine? Is it still?

How do systems of taxation increase the poverty of women? What is the cause of this bias?