28. SEPTEMBER 2022 The Gender Data Gap — Why Women Are Still Largely Invisible in Data

It’s Time to Address Invisible Women and the Gender Data Gap.

It’s impossible to ignore the gender data gap since the book “Invisible Women” shed light on the issue. Understanding how it came about and impacts women’s lives is essential if we’re to close it. Let’s take a look—and explore why the solution lies in data.

Do you ever find that smartphones are too big for your hand or that your protective mask doesn’t fit properly? Do you often freeze in the office and can only reach the top shelf in the supermarket on tiptoe?

Almost 50% of the population should know precisely what we’re talking about.

The concept of a “gender data gap” was the focus of Caroline Criado-Perez’s book “Invisible Women: Exposing Data Bias in a World Designed for Men“. The topic is vital to any discussion on gender equality yet it’s often still ignored. Criado-Perez describes how women are consistently disadvantaged because of a huge gender bias that exists in data collection, resulting in widespread disadvantages to women that can affect every aspect of their lives. Despite the problem being as old as the collection of data itself, we’ve become so accustomed to it, that it often remains invisible.

This data gap is neither intentional nor sudden, but the result of a simple fact: All data throughout history has regarded men as the standard representation for the whole of humanity, as Criado-Perez explains in her book. In a world largely based on Big Data—whether for product design or spatial planning—this clearly impacts the lives of women and girls, as their opinions and experiences exert no influence.

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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