Invisible Women: A World Built for Him, Not Her

I sprinted the moment the MRT doors opened at Bugis station, instantly regretting the two cups of Americano I had downed that morning. My bladder felt like it was ready to burst as I rushed through the crowd, weaving between people until I finally reached the bathrooms. But my relief quickly turned into despair. The queue in front of the female toilet stretched like an endless snake, barely moving. I glanced at the male toilet next door—no line at all. Frustration arose as familiar memories flashed through my mind— Singapore, the States, China— everywhere I’ve traveled, the story was always the same: why does the women’s bathroom always have a longer queue than the men’s?

Men’s and women’s public restrooms are typically allocated the same amount of space, so that simply couldn’t explain this difference. It’s true that, on average, women take 2.3 times as long as men to use the restroom, but is it just because females need more time to pee? Not exactly. 

Women make up the majority of the elderly and disabled—two groups that tend to take more time in the restroom. In other cases, women may also be on their period, meaning they need time to change tampons or sanitary pads. Women also need to use the restroom more frequently than men—pregnancy reduces bladder capacity, and women are just more likely to suffer from urinary-tract infections. On top of all that, women are more likely to be accompanied by young children, regardless of the child’s gender, further increasing the time needed for the bathroom. Therefore, given the difference in gender roles and physical anatomy, allocating “equal” restroom space is not inherently fair—it grants men the privilege of convenience while leaving women to bear the cost of longer waits and greater discomfort. 

This subtle yet pervasive privilege is exactly the issue that campaigner and writer Caroline Criado Perez highlights in her book Invisible Women. By using data to uncover instances where gender bias lurks beneath the surface of seemingly established gender equality, Criado Perez points out how data bias hides male privilege behind the fig leaf of equality, significantly hindering women’s opportunities to thrive or even just survive in their everyday lives.

While the book revealed many hidden and often overlooked areas where gender bias seeps in, such as in public transport and agriculture, a lot of the topics discussed and facts presented didn’t particularly surprise me, nor should they shock most women. Just as we know that the women’s restroom always has a longer line than the men’s, we also know that a gender pay gap exists, that we perform the majority of unpaid labor in our households, and that we are disproportionately more likely to be the victims of domestic violence and sexual assault. However, when these issues are quantified, the data not only gives them more weight, but also helps uncover the underlying complexities and nuances of these phenomena. 

Criado Perez aptly titled the book Invisible Women, exposing how the “invisibility” of women in data and planning perpetuates systemic male privilege. A seemingly minor example—snow-clearing schedules—reveals just how deeply this privilege is embedded. Typically, snow-clearing schedules prioritize clearing roads for private cars over sidewalks for pedestrians. On the surface, this may appear logical, as care users are assumed to be commuting to high-paying jobs and contributing visibly to the economy. However, this assumption in fact privileges the male pattern of mobility: men are more likely to drive, while women, who more often walk or rely on public transport, are marginalized. This failure to account for women’s unpaid labor and caregiving responsibilities reveals how public planning not only renders them invisible but also places them at greater risks. Such supposedly neutral policy leads to a gendered outcome: 69% of those injured in single-person incidents, particularly during winter, are women, often with severe injuries. Therefore, the snow-clearing schedule, which looks like a technical decision, has become a reflection of whose needs are prioritized and whose are dismissed and overlooked.

While invisibility is often associated with being a minority, the paradox of women’s invisibility lies in the fact that we are not a minority—we are the majority. Yet, as Simone de Beauvoir famously proposed, women have long been treated as “the second sex”—defined in relation to men, rather as autonomous subjects. Criado Perez further builds on this legacy by showing how modern systems are still designed around the “default male”— white, working men—while females are casted as the exception rather than the standard. From workplace structures shaped around male career paths to public policies that overlook caregiving roles, women are forced to live in a world built on assumptions that indirectly privilege male experiences. Gender bias in interviews, limited maternity leaves, and inadequate childcare are difficult barriers preventing women from thriving in their careers. And the consequences of such underrepresentation stretch beyond employment. As Criado Perez points out, when women are excluded from the labor force, their needs are often also neglected by the product market, especially in male-dominated industries like tech. For instance, despite clear evidence that women have smaller hands and are more prone to musculoskeletal issues, smartphone designs are still primarily tested on male users, reinforcing the notion that men are the default and women the deviation. In a world increasingly shaped by technology, the lack of female voices in its development risks putting us in an even more disadvantaged position in the future. 

If women’s invisibility is the root of the issue, then the solution seems simple—amplify women’s voices and make their needs visible. This is the approach championed by Criado Perez: uncover hidden data biases, bring them to light, and ultimately push for systemic correction. On the surface, the fixes may appear tangible and practical: if there aren’t enough women’s bathrooms, build more; if maternity leave policies are flawed, implement better ones; if street lighting is insufficient, install more. But are these solutions enough to completely remove such deeply ingrained inequality? These changes, while necessary, will most likely do little to shift the entrenched social norms that allow men to remain the default and women the exception. More bathrooms won’t persuade men to share caregiving duties in public spaces. Improved maternity leave policies won’t stop employers from penalizing women who may plan to have children. Brighter streets alone won’t dismantle the cultural conditioning that enables, and at times excuses, male violence in the absence of true accountability. The truth is that biases don’t just live in policies or infrastructure—they live in the people. 

While exposing data bias can certainly raise awareness about gender inequality, I question whether it will truly lead to genuine behavioral change or simply create an echo chamber within the female community. To take the simplest example, I doubt whether any men would be interested in reading this book. As I mentioned earlier, as a woman, much of the data presented didn’t surprise me, and I imagine the same is true for many other women. The real challenge is that the people who most need to be aware of these biases are men, especially those who are largely insensitive to gender discrimination. However, they are unlikely to be moved by simply exposing the data. As Angela Saini, a science writer and MIT lecturer, noted: “What should worry us more than the data gap, then, is that huge and seemingly intractable don’t-give-a-damn gap.” (Saini 2019). Simply put, men currently just don’t care enough, and without a shift in mindsets and behaviors, addressing these biases one by one will be extremely slow and ineffective— worse, new biases may emerge even faster than we can eliminate the old ones. 

Speaking of “new” biases, Criado Perez touched on a particular technology that may embed even deeper gender biases into our society in the coming decades— artificial intelligence. When the book was written in 2019, tools like ChatGPT and other generative AI hadn't yet achieved the level of influence they have today. The rapid expansion of AI risks amplifying data bias. For example, in a 2017 images study, pictures of cooking were over 33% more likely to involve women than men. When algorithms were trained on this dataset, AI began associating kitchens with women 68% of the time. The study further found that the stronger the initial bias, the stronger the amplification effect. As Criado Perez pointed out, the AI industry is overwhelmingly male-dominated. In an industry where top-performing coders are predominantly men, preventing gender biases from infiltrating the technology and accounting for socialized gender differences in the algorithms presents significant challenges. As AI tools begin to reshape critical areas like healthcare, business, and even education, will our future generations, who will grow up surrounded by these potentially biased technologies, still be able to recognize gender inequalities and take initiatives to challenge them?

Overall, the data presented in Invisible Women was powerful, serving as a stethoscope to diagnose the “sickness” in our society. While the book did a great job in identifying biases, it still has limitations in proposing effective treatments and solutions to address these issues. Criado Perez aimed to use “recognizing” data biases to tackle these problems, but I would argue that recognition alone is not enough. While acknowledging data bias is crucial, the greater challenge lies in how we handle this data going forward, and how we implement systemic solutions to ensure the world is no longer set by default for men, but also considers women. Despite its limitations, the book is undeniably inspirational. Criado Perez successfully spotted seemingly insignificant everyday occurrences—such as smartphone sizes and snow-clearing schedules—and uncovered the underlying biases and inequalities. It made me realize that what I once saw as random, unlucky incidents, like long restroom lines, are a part of a much greater issue.