We live in a time when data is being collected by every single device that we use, research in science and technology is reaching new frontiers and scientists are starting to train algorithms to make the decisions for us using the data that is available. Caroline Criado-Pérez’s Invisible Women: Data Bias in a World Designed for Men is a powerful book that questions the practices through which this data has been collected as well the data itself, highlighting the many areas in our society that does not have gender segregated data. Read the synopsis below to gain a glimpse of some of the situations being data collected from women might have helped make better decisions.
Imagine a world where your phone is too big for your hand, where your doctor prescribes a drug that is wrong for your body, where in a car accident you are 47% more likely to be seriously injured, where every week the countless hours of work you do are not recognised or valued. If any of this sounds familiar, chances are that you’re a woman.
Invisible Women shows us how, in a world largely built for and by men, we are systematically ignoring half the population. It exposes the gender data gap – a gap in our knowledge that is at the root of perpetual, systemic discrimination against women, and that has created a pervasive but invisible bias with a profound effect on women’s lives.
Award-winning campaigner and writer Caroline Criado Perez brings together for the first time an impressive range of case studies, stories and new research from across the world that illustrate the hidden ways in which women are forgotten, and the impact this has on their health and well-being. From government policy and medical research, to technology, workplaces, urban planning and the media, Invisible Women reveals the biased data that excludes women. In making the case for change, this powerful and provocative book will make you see the world anew.
Why I chose to read Invisible Women
I pick up books not because of the gender of the authors who wrote it or their ethnicity. I want to read books because they all have stories to tell. Yes, if I focused on gaining more understanding in certain genres or supporting certain groups of the population, I would learn a lot more about them. However, the subject matter is what draws me to a book.
So, even though this book is about the lack of data collected from women as well as the times when women are not consulted in major areas of the society, I picked up this book because it talks about data. As a data analyst and computing scientist, it was a dream come true to find a book that analyzes data from so many walks of life, while at the same time, telling a powerful story. All that, I speculated from the synopsis itself. And I was not disappointed.
Themes for Thought
I talked about this book previously on my friend, Alex’s blog during his International Women’s Day post, and have talked non-stop about it with my colleagues and family while reading it. Now it is your turn. 🙂
Invisible Women is a thoroughly researched book that brings together data from public hygiene, urban planning, pension plans, academia, agricultural equipment to phone sizes, impact on women during natural disasters as well as success rate in politics itself. This is probably the only work I have ever read that presents a holistic picture of women, be it unpaid care work or paid employment. So many times places and things are usually designed without much consideration to women. The book is based on data from multiple sources and talks about what happens when women are not considered when making major decisions.
On Role Models
When I was working on my teaching degree, there were a number of times when it would come up that as a woman in computing science, I would be a great role model for girls because they would see that a girl can code too. There are a number of such initiatives to get more women in STEM (Science, Technology, Engineering, and Math) and I have struggled with these ideas because if it wasn’t for where I grew up, I would not have chosen computing science at all. Yes, I love it but just because I do, I do not want to see more women in computing science because the society wants to see more – I want to see women in computing science because they love computing science.
In the Introduction of the Invisible Women, Caroline cites former doctor Peter Davison saying that Doctor Who played by a woman meant ‘the loss of a role model for boys‘. Role models don’t have to do with gender. Role models are who they are for the things they do. I admire my mom for being super independent and bringing me up and taking care of her family while working full time in a very demanding job. Just because she is female does not make her more or less of a role model. I admire my dad for always thinking ahead and being super organized. Him being a man has nothing to do with it.
The things that we admire in someone are not linked to their gender. Maybe their experiences as a man or woman enhance that respect.
On Privilege
In the first part of the book, Caroline talks about public hygiene and how there are places around the world, including India where I grew up, where there is often no public sanitation facilities. Women who work out in the open, selling goods all day, do not have access to a bathroom and actively avoid going all day long because all sorts of risks exist if they happen to.
Looking back at other experiences that I had growing up in India, and how much safer I feel here in Canada, I understand that I come from a place of privilege. I was not born in a poor Indian family and my parents helped me reach this point through all their hard work where I have a full time job that gives me a private bathroom.
With the whole corona virus news and disappearing toilet paper off grocery shelves, does it ever cross our mind that toilet paper is a privilege? In some places and for the people in these places, there are no bathrooms, let alone drinking water.
On Data Privacy
There are days when I get sucked into these rabbit holes on data policies. If I sign up for this service, what kind of data is it collecting from me? What is it doing with that data?
In computing science, we want our algorithms to be able to learn from new data. The aim is that just like a human can understand and figure out a new situation, algorithms should be smart enough to do the same. There are a number of medical and technological studies noted by Caroline in Invisible Women which show that a number of products are not optimized to be used by women. Maybe there were not many women subjects in the studies at all. This made me wonder whether organizations that collect data from me are using it to feed into their algorithms to understand their users better? Is that truly the time for that sort of research though?
After Thoughts
This book had a number of eye opening moments for me. I have not even scratched the surface of the facts that Caroline presents. However, as I was talking to Brent about this book, and trying to get him to read it since I loved it so much, he reminded me about confirmation bias. When there are certain points we are passionate about, we look for things that support our beliefs. It is quite natural. A lot of the research that I read about in Invisible Women was heart breaking that it did not consider women at all. But there were also examples where women were considered. So it is not all bad. And the idea is to share the facts, not make you feel bad or point a finger at an individual.
If you are a man reading this review and feeling that you might be lumped in with people who believe boys can have only male role models, I want to let you know that is neither the intent of the book nor the intent of my blog post.
When we talk about diversity, we automatically end up putting people in groups based on some features to differentiate between them. I am Indian, Asian, South Asian Indian, a woman, a woman in computing science, an immigrant,… I belong to a variety of groups and it is what it is. Those are all part of my identity.
Invisible Women aims to bring many facts together in one place but if, like me, you start to look for an answer as to what one person can do to make life better for all of us (and by ‘all’ I mean both men and women), you won’t find those answers in this book. And maybe that is okay. We have to do this together as a community, support the people who have the influence and continue to stand up for the things that we believe in.
But I did find something in my discussion with Brent. Empathy.
Alex and I were talking about trigger warnings and he mentioned how women are subject to abuses that a high proportion of men will never experience. I know from talking to friends that just because something isn’t expressed, doesn’t mean it doesn’t exist – abuses that men experience are not easily available to read about. Similar is the situation here in Invisible Women. Just because some people forgot or chose not to consult women about their use of daily transit, does not mean that women do not use the public transit and find it meets their needs.
With empathy, we can learn to be fair, really think about what other people are saying and decide if it fits how we think. Maybe our thinking will change a little. Maybe it won’t. But we will learn something. I said in my author – book blogger relationships post that we should try to be in other people’s shoes. That is empathy. Yes, sometimes, lines are drawn between man and woman, or Eastern and Western ideologies. Giving the other side a fair chance and trying to understand it is empathy.
There is so much that women do that we do not think about because we are used to being this way. I love how much thought has gone into this book to expose these thought patterns.
** Invisible Women: Data Bias in a World Designed for Men is now out in stores so get a copy and let me know what you think! Let’s have a book-discussion! **
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Cover image: Photo by Josh Calabrese on Unsplash
Image of child in cape on unsplash.
Image of girl on phone on Unsplash.
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