Invisible Women: How a lack of research can reinforce inequality

Invisible Women: How a lack of research can reinforce inequality

Invisible Women

Design involves decisions – often, a lot of them. What should the product do? What should the service provide? Should we offer this feature? Which screen/option should come first? Even in design projects that have a lot of non-negotiable constraints, there will still be hundreds of decisions up for grabs. So how is one option chosen over another?

Ideally, decisions should be made based on a detailed, evidence-based understanding of what all known and potential users need, so that anybody using that product or service can do so with ease. What Caroline Criado Perez’s detailed and fascinating book Invisible Women: Exposing data bias in a world designed for men shows very clearly is that this process of collecting data and understanding users happens much more rarely than it should and that the design decisions that result from this lack of research can range from foolish to life-threatening.

Through a range of different examples, she demonstrates just how often design decisions are made to suit one type of person – the ‘standard’ male – resulting in designs that are not only difficult and inconvenient for women to use, but which often reinforce inequality and put lives in danger. Women, for example, are 47% more likely than men to be seriously injured in a car crash and 17% more likely to die because vehicle safety standards are based on crash tests run almost exclusively with test dummies based on male physiology. The fact that women are considered to be ‘out of position’ drivers because they tend to drive with their seats closer to the steering wheel than men, due to their shorter legs, reveals the underlying assumption that men are ‘correct’ and women are in some way out of the ordinary.

Another more frivolous but striking example of this ‘othering’ of half the population is Apple’s ‘comprehensive’ health tracker, launched in 2014. Somewhere along the way, designers of this product decided that users would like to track their molybdenum and copper levels – arguably something relevant to a very small proportion of users. They didn’t, however, think of tracking a major element of the health and wellbeing of billions of people – periods. Thus, they created a health tracker that is very ‘comprehensive,’ perhaps overly so, but only if you’re male.

The many different examples that Criado Perez illustrates so well in her book have drawn responses of shock and anger from both women and men, as well as the obvious question, ‘How does this happen?’ The answer, from my experience as a user researcher, is that it happens because people design for people like them. This is as much true for women as for men, but because men tend to dominate in all the areas Criado Perez mentions – vehicle design, public policy, software development, medical research – the world ends up being built for and around men. Because women aren’t there, making the decisions, adding their voice, saying ‘what about…?’ their specific needs are either considered to be extra, an afterthought, modifications to the male standard – or they’re not even considered at all. Given that half the population so often gets left out of these design decisions it really isn’t hard to see how smaller groups of people with other needs, due to disabilities, for example, get totally forgotten.

How does such inequality change? It’s pretty simple really – through thorough, careful and detailed research. As Criado Perez emphasises, the root of the problem is data bias – any research that does exist is either based entirely on men, or lumps men and women together in such a way as to hide the specific differences between them. You can’t design for someone’s needs if you don’t know what those needs are. And you find out those needs by observing, asking, investigating and analysing.

What Criado Perez’s book illustrates very well is that design decisions rarely involve a value-free choice between equally valid options. Design decisions have far-reaching effects. They can make a product more attractive, usable or successful, but they can also make people’s lives more difficult, frustrating and dangerous. Designers can create and reinforce inequalities by failing to examine their own assumptions and continuing to ignore and exclude people who don’t fit the norm, or they can effect real change in what they create and make life safer and easier for everyone, no matter who they are or what their ability level is. That’s a difficult goal to achieve, but it is possible with the right research that gives the right data. With the right data, decisions can be made based on the needs of all users, not just those who happen to be in the room or who happen to fit the standard.


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