The Data That Forgot About Women

The Default Human is Still Male 

I always knew the world wasn’t exactly fair to women. We talk about the gender pay gap, unequal opportunities, and how women are still underrepresented in leadership roles. It’s not new. 

Reading Invisible Women  felt like peeling off layers of assumptions I didn’t even know I had. The stories Caroline Criado Perez  brings forward are not just statistics — they are moments of everyday discrimination, invisibility, and discomfort that women all over the world silently endure. 

Invisible Women sheds light on the pervasive gender data gap that results in a world predominantly tailored to men. This gap manifests across various sectors, leading to systemic disadvantages for women. 

Before this book, I saw inequality as something societal, yes — but somewhat abstract. Structural. Big-picture stuff. But this book shattered that illusion. It made me realise just how embedded the bias is. Not just in institutions, but in the data. In the systems we trust. In the roads we walk, the phones we use, the medicine we take. And suddenly, I couldn’t unsee it. 

That’s when it hit me: we really are living in a man’s world — and not just metaphorically. The default human is still male. And unless we change the way data is collected, interpreted, and applied, women will keep being treated like an edge case. 

While the core argument isn’t entirely new, what makes this book stand out is the depth and rigor of its research. Each chapter is backed by a wealth of scientific studies and journalistic sources. It’s also thoughtfully organised, this book isn’t speculative or abstract. It’s grounded in hard data, which makes it impossible to ignore. 

Work Without Value: The Cost of Invisible Labour 

Imagine a resource so vast and essential that without it, entire economies would collapse. It sustains the workforce, enables productivity, and supports societal wellbeing. Now imagine this resource is not accounted for in any economic system, not paid, and largely performed by one gender. 

Welcome to the hidden world of unpaid labour, the costless resource that powers our lives — and our economies. The numbers are staggering. 

Globally, women do over three-quarters of the unpaid work. In some regions, women spend ten times more hours on unpaid care than men. In monetary terms, this “invisible” labour would equate to trillions of dollars if it were paid — even contributing up to 50% of GDP in high-income countries if properly accounted for. 

In other words: if women stopped doing unpaid work today, the economy would crash tomorrow. 

But because it’s “free,” governments rely on it without recognition. And because it’s unpaid, it is undervalued — even by those who perform it. 

When Austerity Hits, Women Pay Twice 

After the 2008 financial crash, austerity policies swept across the UK and other countries. Budgets were slashed. Public services shrank. But the unpaid labour didn’t vanish — it just shifted. 

Who filled the gap? 

Women. 

They took on care work for the elderly when social care was cut. They managed disabled family members at home. They made up for fewer meals at schools, fewer community services, fewer transport links. The government saved money. Women spent more time, more energy, more of their lives — without pay, without acknowledgement. 

Perez calls this “costless labour” — but only because the cost is not absorbed by the economy. It is paid in time, in stress, in opportunity. It’s a systemic subsidy that women provide for free. 

Chapter 3 of Invisible Women, titled “The Long Friday,” recounts the historic women’s strike in Iceland on October 24, 1975, when 90% of Icelandic women stopped all paid and unpaid labour to highlight the critical — but invisible — role they played in society. The strike brought the country to a near halt, revealing how dependent everyday life was on women’s unpaid work. 

Using this event as a springboard, the chapter explores the global imbalance in unpaid labour, showing that women consistently perform the majority of household chores, childcare, and eldercare — regardless of whether they also have full-time jobs. Despite this, unpaid work is not recognised in economic systems or workplace structures, which are largely designed around a male-centred model assuming a worker without caregiving responsibilities. 

These outdated structures penalise women — from academic tenure timelines to reimbursement systems that don’t cover essential caregiving costs. Even well-meaning policies fail when they ignore the real-life dynamics of unpaid labour. 

The chapter closes with a call to action: if we want true equality, we must start designing the world of paid work to recognise and value the unpaid work that sustains it. Without this, women will remain invisible within systems built to exclude them. 

A study by Cake.com, Gender Inequality in Unpaid Domestic Work, explored the state of household labour inequality and revealed that among remote-working couples, 72% of housework is still done by women — highlighting that proximity to home doesn’t equal parity at home. 

Figure 1: Housework distribution between men and women (Source: cake.com)  

 

Crash-Test Dummies That Don’t Represent Women 

For decades, vehicle safety testing has relied on crash test dummies modelled on the “average man” — roughly 5’9” tall and 76 kg. This male standard defines how cars are designed, how seatbelts fit, how airbags deploy, and ultimately, who survives a crash. Women, by contrast, are an afterthought. 

The result? Women are 47% more likely to be seriously injured and 17% more likely to die in the same crashes. This isn’t due to worse driving but because of anatomical differences like shorter stature — Women typically sit closer to the steering wheel (due to shorter legs), different muscle mass distribution, they have less upper body strength, which affects bracing during impact and unique spinal and pelvic structures — none of which are accounted for in standard tests. 

Even the so-called “female” crash dummy is just a scaled-down male, used only in passenger seats. Pregnant bodies? Not tested for at all. 

This oversight stems from a persistent bias in design: the assumption that “male” equals “neutral.” But if your definition of “user” doesn’t include half the population, your design isn’t universal — it’s exclusionary, and in this case, deadly. 

To fix this, we need anatomically accurate female dummies, mandated testing in all car positions, and policy that demands inclusive data. Because designing for safety shouldn’t be a privilege — it should be a right. 

The Drugs Don’t Work — But Only If You’re a Woman 

Imagine being prescribed a medication that was never actually tested on someone like you. That’s not a dystopian sci-fi plot — it’s the lived reality for countless women today. 

Women are still underrepresented in medical studies, often excluded due to the “complication” of hormonal cycles. The consequences are deadly: heart attacks in women often present with different symptoms than in men, but since most training data is based on male cases, many women go undiagnosed — or die. 

So, the vast majority of drugs on the market have been designed with one default in mind — the average male body. From clinical trials to dosage recommendations, women have been largely excluded from the research process. Even lab animals are often male. The assumption? That male bodies can represent humanity as a whole. 

But they don’t. 

Women metabolise drugs differently. They experience different symptoms. Their immune responses, hormone cycles, and even heart attack signs diverge dramatically from men’s. And yet, they’re still being treated with protocols based on data that barely includes them. The consequences aren’t just academic — they’re deadly. 

Heart medications, antidepressants, even surgical implants like CRT-Ds have shown reduced efficacy — or increased harm — when applied to women. In some trials, only 22% of participants were female. In others, the data wasn’t even disaggregated by sex. 

This is not just a data gap. It’s a design flaw embedded deep in the structure of modern medicine. One that can cost lives. 

Workplace Structures Are Male-Centric by Default 

When Facebook Chief Operating Officer Sheryl Sandberg became pregnant for the first time, she suddenly found herself struggling to walk across the company parking lot. The distance, once inconsequential, had become a painful challenge. So she approached Google — where she had worked previously — and asked why there weren’t designated parking spots for pregnant women. It hadn’t even occurred to them. No one had noticed the problem because no one who made the decisions had ever experienced it. 

Most modern workplaces weren’t designed with women in mind — they were built around the archetype of the “ideal worker”: someone fully dedicated to their job, available long hours, and unburdened by caregiving. In other words, a man with a wife at home. 

Systems that appear gender-neutral are anything but. Consider temperature controls in office buildings — still based on a formula from the 1960s that assumed the metabolic rate of a 40-year-old, 70kg man. Or workplace safety standards that don’t accommodate women’s average strength or body proportions, leaving them less protected and more fatigued in environments designed without them in mind. 

This framework persists in everything from how we measure productivity to how promotions are granted. 

And even when gender-inclusive policies exist — like paid parental leave — they’re often sabotaged by hidden penalties. Women who take leave are subtly punished, perceived as less committed, and passed over for promotions. In academia, tenure clocks tick mercilessly during the very years women are most likely to have children, forcing many to choose between motherhood and career advancement. 

Bias is embedded not just in attitudes but in the systems themselves. Evaluation processes often reward traits traditionally coded as “masculine” — aggression, overconfidence, constant availability — while penalising collaboration, empathy, and boundary-setting, traits more frequently expressed by women. 

Nicholas Wolfinger’s work (sociologist and professor at the University of Utah, known for his research on family structure, marriage, work-family balance, and gender inequality) — illustrates how women are systematically excluded from career ladders that don’t account for their realities. This isn’t about individual choices — this is structural neglect. It’s not just that the ladder is harder to climb; it’s that it was built for someone else entirely. 

Until institutions redesign the rungs, pace, and expectations of professional success with all humans in mind — not just men — women will continue to be punished by systems that claim to serve them. 

Voice Recognition That Doesn’t Hear Women 

Voice technology — from Siri and Alexa to in-car command systems — has consistently performed better for male voices than for female ones. This isn’t just a quirky tech glitch. It’s the result of machine learning models trained primarily on male voice data. 

Caroline Criado Perez illustrates this problem with a story that’s both absurd and deeply relatable: a woman purchased a new car equipped with voice control features. She couldn’t get it to respond to her commands, no matter how clearly she spoke. But then her husband tried… and it worked perfectly. In her car. 

Why? Because the voice recognition system, like many others, was trained predominantly on male speech patterns — deeper pitch, more monotone, and less variation in syntax. Women’s voices, with naturally higher pitch and greater vocal range, are often misinterpreted or ignored entirely. 

This design flaw doesn’t just frustrate — it excludes. Studies show voice recognition is up to 13% more accurate for men, a gap with consequences in areas like medical devices, customer service, or emergency tech where voice is becoming the main interface. 

At its core, the issue reflects a familiar pattern: the “default user” is male, and everyone else must adapt — or be left unheard. 

These Aren’t Gaps — They’re Chasms 

What shocked me most wasn’t just the existence of these stories — it was how normal they’ve been made to feel. They’re brushed off as exceptions or oversights, when in reality, they’re symptoms of a world that was built with only half the population in mind. 

This isn’t about special treatment. It’s about equal consideration. 

 

Written by Diana Leon

Sr. UX Designer and Researcher at The Access Group 

DFI Community Member

Established in 2015,  Digital Frontiers Institute  is a proud brand of  Digital Frontiers. Learn more about the Gender Equality Changemakers programme and find out how to enrol: https://genderequality.digitalfrontiersinstitute.org/   

 

(Article originally shared on Medium by Diana Leon on 3 May 2025)