Gender data bias leads to safety risks for women from "summary" of Invisible Women by Caroline Criado Perez
Gender data bias has real-world consequences, particularly when it comes to women's safety. When information is missing or inadequate, decisions and policies are made based on incomplete data, putting women at risk. For example, crash test dummies used in car safety testing are based on the "average male" body, leading to cars that are less safe for women. This bias is not limited to car safety - even in the design of protective gear such as bulletproof vests and helmets, women are often left out of the equation, making them more vulnerable in dangerous situations. Furthermore, the lack of gender-disaggregated data in healthcare can lead to misdiagnosis and inadequate tr...
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