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“A belief in your own personal objectivity, or a belief that you are not sexist, makes you less objective and more likely to behave in a sexist way.”

Can data be sexist?

If data is objective, how can it systematically overlook women?

For centuries, we have spoken of "man" as though he were synonymous with "human." But how does it shape our societies when the default human is only half of humanity?

And what are the consequences of building a world around one experience while overlooking the other?

Invisible Women is an investigation into these blind spots that have unconsciously shaped our reality. Drawing on research spanning medicine, economics, urban planning, artificial intelligence, psychology, public policy, and design, Perez uncovers the hidden gender data gap - and reveals how a world built around the "default human" has repeatedly overlooked half of humanity.

Genres: Social Science, Feminism, Psychology, Data Science, Nonfiction
Pages: ~432, paperback

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