Invisible Women: Data Bias in a World Designed for Men Kindle Edition

I’m a man, and I knew the problems with women’s data not being collected and women’s needs not being met in the world were bad, but not THIS bad. There are many great sources of data for these claims throughout the book; so many, in fact, that I started to feel overwhelmed after a while.But guys, we have to read sources like these and motivate ourselves to do better. The women in our lives deserve that, at the very least.

The book spend an ENORMOUS amount of time talking about the trials and tribulations faced by women with children quite as if, the concept of female was entirely interchangeable with mother. I got the impression that women who do not have children are quite as invisible to this author as she claims women on the whole are to most men. When the author started advocating 12 month maternity leave for mother only I gave up on it. What about those individuals with minor or moderate physical disabilities who would also benefit from parking closer to the building, and more paid time away from the job to tend to their very REAL healthcare needs, these women and men are clearly invisible to this author, I work in a hospital and from what I have observed the out of all the departments in the hospital, including outpatient surgery, the OB has the healthiest patients and one of the lowest mortality rates, so why does a two day stay in the OB garner a minimum of 6 weeks paid leave when end stage renal disease gives you four days a year tops before you have to be back to work? It sound great to say that women should have 12 months off to spend with their new children, but don't these children have fathers wouldn't the fathers like to spend some time with them as well? The author merrily ignores the co-workers of the new parents who are routinely "asked" to cancel vacations sacrifice time with their families and freinds and put their personal lives on hold to contribute to this state of maternal bliss, the childless, the elderly who are past childbearing and might want to start cutting back the hours a day they work or who are already partially retired are invisible non-entities in this model that elevates motherhood to goddess like status in the workplace. This book has it's own bias similar to that which I have observed to often in the medical profession, when it says "woman" it means uterus, breasts, and children, and not the people who make up the female half of the population, some of whom will not have uteri, some of whom will not have breasts, and many of whom will not have young children.

This is really an eye opening book backed by data (and ironically, by a lack of available data) to make a profound point. I came to this book believing myself already to be proactive about women's rights and issues, but learned that the problem runs so much deeper than I ever realized. And if I'm completely honest, I learned that I've been guilty of unconscious bias by simply not thinking through how certain things might affect women differently. I'm not a big book reviewer or recommender in general, but this important book is one I'm telling people in my world about. I highly recommend that you read this book if you want a better world for everyone.

Read this book. It is incredible. Well written, thoroughly researched and documented, but still extremely readable. Fascinating. Shocking, and not. If you are a woman, or if you care about women, read it. Even if you think you already understand how different the world is for women, you will be surprised.

Tons of facts but nothing boring about it. Most of the information should be in biology textbooks, on the news, and informing public policy in all areas of life. Instead much of it I am hearing for the first time as a middle aged woman. The disproportionate inconvenience, violence and death women face around the globe because women are not consulted or even considered in every area of life! We are not an anomaly or a resource to be exploited. We are an indespensible HALF of the population! Thank you for writing this book!

This book made me so angry that I had to put it down several times just so I could cool off. If you use data, collect data, or think that credible data can be trusted, this book will dissuade you of your illusions. Because so-called credible data kills women. It kills them in car crashes, in hospitals, after natural disasters, and after a winter snowfall. The author shows that gender-neutral data is actually blind to women, and women (and men) suffer the repercussions.

I just finished reading this book, and I'm blown away by how much I learned (and how much I enjoyed learning it). This is a great preparation for the fight ahead, And I truly believe this should be required reading for both men and women.Keep in mind, I don't even enjoy reading, but this book completely changed that.I have 3 books on my current queue, and probably going to read this one again after I'm done. Thank you, Caroline Criado-Perez.10/10.

I struggle to get into nonfiction but cannot put this book down. I'm about halfway through it and every chapter is blowing my mind. The writing is fast-paced and exciting and the content is fascinating!

First things first: the designer of this book was clearly on a roll. The font is clear and delightful. The italics, in particular, are so beautiful I had to take a picture of them and send it to my friend so he could appreciate them too. The cover design is subtle and fantastic. When you take the dustjacket off, the overlaid blue male figures disappear, leaving the invisible women behind, which ties in wonderfully with the book’s overarching message. The texture of the dustjacket and hardcover is delightful, with a velvety-smooth overlay that is really pleasing to the touch.The book is heavily referenced throughout with endnotes. These are collected directly after the acknowledgements, a full 69 pages of references. The impact of this collected body of commentary serves to underline the density of information and dedication of the research which went into this book. While I’m not a fan of endnotes, personally, the stylistic choice to collect them all together gives undeniable weight to the book, and makes it difficult to dismiss its conclusions.But that’s enough about the physical construction of this book (for which Chatto and Windus deserves great praise). What about the content itself?Well, I read this book with a combination of mounting horror, frustration, and rage. Criado Perez takes the reader by the hand and gently leads them along a journey of discrimination against women which is endemic in all areas of life. Split into six thematic sections (Daily Life, The Workplace, Design, Going to the Doctor, Public Life, and When it Goes Wrong), this book catalogues a pantheon of circumstances where what is female is considered as abnormal, as less than standard, as Other. Collected together, the ignorance of design to the differing needs of 50% of the population is both fascinating and incredibly infuriating.Criado Perez doesn’t use this book as a stick with which to beat the patriarchy, however. Rather, she delicately unpicks the circumstances which lead to a lack of consideration of the needs of those other than what is considered to be the default. Her examples are wide-ranging, touching on every area of life, and consistently return the same conclusion: women just haven’t been thought about. It’s not that their needs have been considered and dismissed. It’s that the fact that they might have different needs hasn’t even occurred to the people creating these structures.(Generally. There are some notable exceptions. One quote from Tim Schalk really burned my cookies. But it’s not actually the norm.)From Sheryl Sandberg’s explanation at Google that heavily pregnant women can’t walk long distances to Apple Health’s omission of allowing tracking of a menstrual cycle, for many examples in this book, the reason for these omissions is that people didn’t even think of them as a potential need. Cars are crash tested rigorously before making it to market – but the dummies used are 1.7m tall. This is the size of the average man, not the size of the average person, and it leads to shocking statistics like the fact that women – despite being less likely to crash – if they are involved in a crash, are 47% more likely to be seriously injured. Criado Perez points out myriad ways that this unthinking acceptance of male as default – and as applicable to all – unfairly impacts on women, and leads to their being unconsidered in further development.The book has one overarching message, which calls clearly from every page. Do something about this. Don’t accept data as applicable to all. Sex-disaggregate data, and investigate how men and women are differently impacted. In an era which relies on big data more than ever, the gender data gap needs to be acknowledged, counteracted, and filled. And it needs to be done with a specific focus on counteracting the detriment which the gender data gap had caused. Otherwise we end up with situations where a policy designed to create more family-friendly situations actually end up disadvantaging those it intended to help.Criado Perez is not myopic in her discussions either – she skillfully acknowledges the intersections of race, gender identity, disability, and other minority identities can have to create a cumulatively detrimental effect. Invisible Women is a primer on how not to design, a feminist manifesto, a fantastic example of hard research with incredible readability, and a thoroughly engaging experience. It has filled me with rage and frustration – my friends and family have borne the brunt of several rants already – and I’ll be passing it on and recommending it to pretty much everyone I know.

I bought this book intending it to be a gift for a family member. We have a shared interest in statistics and this seemed like a good punt. Unfortunately it will not be passed on.Firstly the positives:The author is clearly very passionate about her field and has put together a truly awe inspiring set of statistics that completely support the stance that women are biased against in society. This clearly needs to change, and there are some very good examples of where this could be done easily and effectively. It has been an eye opener to me to consider some of the examples brought up, crash test dummies, drug testing and outdated sexist guidance in a number of areas.The negatives:There is a consistent pattern of stating a set of statistics, and then expressing an opinion that this is an example of gender bias which could be fixed with gender disaggregated data. On a first read the conclusions, which seem consistently that men make decisions and that those decisions are implicitly designed to make women worse off off, are not entirely supportable by the statistics gathered.As an example, snow sweeping - which is carried out by clearing the main roads first and then minor roads. The statement made is that this is biased against women as this benefits those commuting by car (men) and harms (physically) those who travel on minor roads as pedestrian (women). The conclusion that data should have been gathered which included more women to prevent this bad decision.Firstly, it could be plausible that the decision makers - being commuters by car themselves - might have made a decision based upon their experience. This is in and off itself is decoupled from gender. One could imagine a mixed panel of working men and working women making the same poor decision with equal gender representation.Secondly, the bias that exists seems to be that men benefit more from the status quo than women due to the nature of the jobs they do (paid work, full time, greater male proportion). The imbalance here is not how streets are cleared but who the jobs are carried out by - so addressing gender bias via the job market would be a better path to removing the gender bias without addressing the poor decision making of how to clear snow.Thirdly, if one were to gather gender dis-aggregated data this might incentivise equal gender participation. However, this does not guarantee that the set of people involved were from different selection groups and might still exclude those "people" that do not commute via main roads. I am sure plenty of women also benefited from the 'main road first' approach - so one could imagine a poll of opinions which covers 50/50 by gender but excludes non-commuters.All of the above are independent on what the best way to clear snow is and what we even mean by "best" in this context (cheapest for execution, reducing road accidents, reducing hospital attendance).I've already fixated on this one example too much, there are others but if you have read this far I risk boring you too much. The issues raised in the book could probably more accurately be expressed as a journey into poor decision making by excluding groups given selection bias. The biases are not specifically gender and do not generally indicate a bias against women (there are other biases and poor decision making at play that predominantly harm women as a side effect) - although there are also examples of terrible bias that deserve to be considered - crash test dummies for everyone please!!I think the author sets off with an axe to grind, and spends the book grinding it. If you are feminist or pro-equality with a view that the world is biased there will be a lot to enjoy here. If you attack it objectively there are still some gems with regards to systemic bias but there are plenty of opinions that do not bear up to analysis.Overall a good book (I think), just lacking a level of objective scientific rigor that would have made it's message more convincing.

This book is amazing at opening the door on invisible bias, unfortunately I am not a fan of the writing style.The author makes fantastic points backs it up with great facts but then in an attempt to cement her point she will suddenly and needlessly jump to unrelated examples of sexism e.g. she makes fantastic eye opening points on why women's toilets should be bigger than men's but then jumps from discussing women's needs and toilet requirements in the West to toilet issues faced by women in India (this just belittles her first point).She also uses the term 'White Men' a lot, I really cannot stand generalisations but stuck with it. The author seems blame all the issues faced by women on men but reading this book makes you think a lot of these issues are a product of their time and are now a systematic societal issue which is as much women's fault as men's; for example 76% of teachers are women and women by far make up the majority of childcare, so why/how are children still being raised with a male gender bias? We have everything we need to change it so why hasn't it been changed? the reason is because the women themselves (and men) don't know issues exist, both genders need educating on these issues.Everyone should read this book as it provides great insight into bias we cannot see but live with but I think blaming one gender for the issues faced by another will create division and stall progression.

Firstly, this is a great read. The reader is taken on a tour of an unknown yet familiar world as the author lays out the facts and costs of the gender data gap. You can't get accurate answers if you don't have quality data- or if you don't ask the right questions in the first place. This isn't presented as a conspiracy against women but as the result of just not seeing slightly more than half the population in the data. The results can range from the inconvenient (not being able to access tall shelves or straps on the Underground) to the fatal (women and men react differently to drugs but mostly only male data is recorded.) The most common reaction to these problems where they are recognised is to try and "fix" women to be more like men (suggesting voice coaching for women to use voice recognition software that responds to male voices). This is a valuable and useful book. Please buy one for the engineer in your life.

Incredible book. Brilliantly researched and backed up. Easy to read, not boring at all. Read if you want to be miserable about the state of the world for women but also more intelligent and having enjoyed a few jokes.