As a result, women live in a world that is not designed with them in mind. Urban and spatial planning, for example, assume that the male body or male-specific needs are the norm. This can manifest itself in a range of ways—from supermarket shelves being too high or the standard temperature in offices set too cool for most women. The gender data gap can also have more serious consequences: Women are 48% more likely to be seriously injured in a car crash because crash test dummies have a male design.
The problem, however, is not with data itself, but the way that data is collected. The organization of UN Women is advocating for a “data revolution” to increase the volume, speed, and diversity of data collected so that more data on women and girls is available in the future. Making Every Woman and Girl Count is an example of an initiative to close the gender data gap.
“Invisible Women” author Criado-Perez also emphasizes the relevance of diversity in the way data is collected. To identify and prevent discrimination, data collected must be segregated by gender, but that’s a gargantuan task. “It’s not going to be an overnight fix because some of the data sets require collections over decades—but we can start now,” explains Caroline Criado-Perez.
When collecting and handling data, key ethical concepts must always be adhered to. ONE LOGIC* consistently stands by strong principles in Responsible AI and AI Ethics when working with data. Find out more here on how we help ensure that the value derived from data is ethical, sustainable, and without bias. *We’ve been operating as “One Data” since 2023.
So, data is both the problem and the solution: The gender data gap can only be closed with the help of data—if that data takes all genders into account equally. We live in a data-driven world where information has an ever-increasing impact. Combating data bias promotes opportunities for a more equitable future.
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