Most of the recorded human history is that of one big data-gap which Caroline Perez argues in the very opening of her well researched work—Invisible Women: Exposing Data Bias In A World Designed For Men.
It is ironical at best to say that when it comes to the task of regulating women’s bodies, movements and sexuality, women suddenly become visible to the eyes of the world. However, when it comes to collecting and incorporating data around women, their needs, their mundane issues—they are rendered invisible to the same eyes! Therefore, from the architecture of public toilets to the temperature of the ACs, from the size of our smartphones to the painkillers and medicinal drugs we use—all by default are designed to work in favour of men.
While there are languages that are grammatically gendered, world’s fastest growing language is the emoji, and studies show that women are its heaviest users. However, this emoji characteristically till 2016 was a male! The male bias therefore, needless to mention, seeps into our textbooks and our pedagogy. As a simple example, the writers we read in our books are often male, and there is a separate chapter on ‘women writers’ enlisting some four to six authors who made it in the man’s world as if only those are all we have!
The temperature by default was set way back in the 1970s with men’s physiology as the reference point. What appears in the guise of gender-neutrality therefore is nothing but a system by default designed to work better for men. The cars we drive, the size and adjustment of the seat-belts, the distance of the pedals, the size of our pockets, the working of meritocracy in the corporate industry to the representation of women on interview panels—you name it and the gender-data gaps pop their heads instantly.
The facts that so far have thus been presented as objective to us, are in fact blatant lies loaded with heavy male bias, fueling the myth of male universality.
Has it ever occurred to you, as a woman, while walking in the office space with a working air conditioner, that the temperature felt a bit cold, while it was alright for men?
The temperature by default was set way back in the 1970s with men’s physiology as the reference point. What appears in the guise of gender-neutrality therefore, is nothing but a system by default designed to work better for men. The cars we drive, the size and adjustment of the seat-belts, the distance of the pedals, the size of our pockets, the working of meritocracy in the corporate industry to the representation of women on interview panels—you name it and the gender-data gaps pop their heads instantly. This data-gap has been something that the women have been made accustomed to, while navigating the world, both in the private and public places.
However, that in no sense shall make us undermine the impact of this silence over the data for almost half of the population of the world, for this data-gap does not come without consequences. These consequences are not only oppressive but also become life threatening in so many ways. Consider this statistics—women are 17% more likely to be killed and 47% more likely to be injured in crashes than men. Women are at increased risk simply because they are women—cars are primarily designed, built and tested by male engineers keeping in mind male oriented data, so they are built for the convenience of men. Similarly, historically, heart disease research was primarily conducted on male subjects by male scientists and doctors, so male symptoms are considered typical and female symptoms atypical. As a result, women are misdiagnosed up to 50% more often and are more likely to be dismissed without treatment.
Also read: Infographic: The Global Gender Gap Report 2020
Further, this gender-data gap ideally should have received urgent attention, more than ever before, with the emerging context driven by the big data and use of Artificial Intelligence (AI) as the guide for our world. The gender-data gap in this case could translate and does translate into gaps in the algorithms. However, that is not even half the story. If data is another word for information, human experience is also a source of information. Therefore, failing to include women’s perspective, which comes to pass itself as gender-neutral, is in fact the recipe for intended or unintended design biased towards men.
Men’s experience is taken as the universal parameter to design the world for both, men and women. The lives of men have been taken to represent those of humans overall. The entire culture, be it our history, the stories, theatre, art, medicine, economy, politics, science, planning, etc., are but a reflection of those gender-data gaps which have inevitably resulted in a world designed for men—a world which is biased towards men.
Theoretical Insights
It will not be far-fetched to claim that the reason for such gender-data gaps can also emanate from the idea of representation as that pointed by Simone De Beauvoir. The idea is that men have confused their own point of view with the absolute truth. There are issues, be it the female body, women’s unpaid care burden or the male violence against women that have always warranted serious discussions but have often been overlooked and deemed unimportant. Women thus happen to be perceived, not as the other sex but as the ‘second sex’ as Beauvoir had explained ages ago.
Only the context has changed, the phenomenon of othering remains, with altered and new technologies. Women are seen not as autonomous beings, but as beings in relation to men. Men’s experiences are taken as the universal parameter to design the world for both men and women. The lives of men have been taken to represent those of humans overall. The entire culture, be it our history, the stories, theatre, art, medicine, economy, politics, science, planning, etc., are but a reflection of those gender-data gaps which have inevitably resulted in a world designed for men—a world which is highly biased towards men.
The Everywhere-Everyday Phenomena Which Are Invisible
Women are more likely than men to use public transport and the travel patterns of women are likely to be more difficult than men. Women would travel to drop kids to school, for work, for taking a relative to the doctor, for grocery shopping on the way home, with majority of pedestrians being women. It is unlikely that the policies around travel and transport would take into account these disparities and as a result, the world of transport, be it the peak hours, the metro timings, the crowded station or design of vehicles come out as biased towards men.
This bias translates into government spending and also infrastructural limitations in city planning. The Nirbhaya Rape case was a case in point, where gender-data gaps resulted into a disaster. Further, planning basis, like zoning laws prioritise the needs of a bread-winning, heterosexual male and home is seen as a place to return for relaxation. However, such laws forget to take into account the unpaid care work done by women at home for whom home in the evening hours too is not a haven to rest or relax, but perform double amount of work. When planners fail to take into account women’s need, public spaces too become men’s spaces by default.
Also read: Book Review: Invisible Women By Caroline Criado Perez
When speaking of work, it is important to bust the myth of meritocracy in the corporate sectors, where there are men in majority on the interview panels and thus, women candidates receive negative personality criticism which really is almost non existent when it comes to male candidates, as per another study.
In the world of academia, students for emotional issues are likely to turn to a female professor, which result in the unpaid workload inside the workplace (FN 39). At this point, one also needs to go into the history of programming as a job which was considered as a low-skilled clerical job, until one day, a team of six women ended up designing the ENIAC, the world’s first fully functional digital computer, in 1946. What happens next is that, owing to brilliance bias, industry leaders started training men for the same by developing hiring tools that were covertly biased against women!
As the world battles another pandemic—COVID-19—the post-pandemic relief efforts, if repeat the mistakes of past, where in women had to suffer the worst in such times, be it Boxing Day Tsunami, Hurricane Andrew or the recent Hurricane Katrina, it will clearly accentuate the rationale that such gender-data gaps are a function of sexism, “a symptom of a world that believes women’s lives are less important than ‘human’ lives, where ‘human’ means male”.
Similarly, in economic crisis, when the government decides to opt for austerity measures, the services provided earlier do not run out of demand overnight or become non-existent. Those services are actually shifted onto the women. As governments take measures to estimate unpaid care work in economic terms, in reality we only have an estimate, and the data on actual contribution of care work to the nation’s GDP goes unaccounted for. There have been committees suggesting to include the same, however, those suggestions were turned down with the reason given that the data collection to such a large extent was very difficult. Such reasoning defeats the very purpose of data collection, for what is the use of data for humanity, when the data is actually incomplete and talks only for half the population?
The same holds true for our politics, wherein women face more hostile environment than men and the working of democracy is not a level playing field but is biased against electing women. The practice of excluding women from decision-making is widespread and you won’t need any more than a glance at the TV screen telecasting the snippets of any major conference or meeting to count the number of men sitting round the table compared to women in the same room.
If one is to talk about India, women make 91% of the workers working in the informal economy and then the question arises as to how many public toilets are there at the workplace—where would these women go during the day then? From lack of better public sanitary facilities for women to the lack of data on the same, gender-data gaps are touching new heights. In addition to that, large scale data for the prevalence of something as serious as sexual harassment is lacking too! Add to that the problematic maternity and paternity leave provisions in many countries and thus, the unfair distribution of care work.
Disaster and Post Disaster Of Gender-Data Gaps
In times of war, conflicts, natural disaster, pandemics—all the usual gender-data gaps, seen from urban planning to medical care are magnified and multiplied. The failure to include women in post-disaster efforts can not only generate vacuum in effective disaster management but also turn out to be fatal for women. This actually underlies a deep-rooted sexism which sees the rights of the 50% of the population (women) as minority interest, convenient to be excluded. An example is the post-disaster effort in Gujarat, in 2001 when an earthquake had just hit the state and thousands of lives were lost and 400,000 homes were destroyed. New homes were needed in the rebuilding effort but Gujarat’s rebuilding project had a major data gap—women were not included in the planning process; the result—they built houses without any kitchens.
Many such instances occur globally. While women have been solution-providers, not heeding them means losing out the chance of incorporating diverse opinions and better solutions to the problems. As the world battles another pandemic—COVID-19—the post-pandemic relief efforts, if repeat the mistakes of past, wherein women had to suffer the worst in such times, be it Boxing Day Tsunami, Hurricane Andrew or the recent Hurricane Katrina, it will clearly accentuate the rationale that such gender-data gaps are a function of sexism, “a symptom of a world that believes women’s lives are less important than ‘human’ lives, where ‘human’ means male”.
Why Bridge Gender-Data Gaps?
The exercise of bridging the gender-data gaps is very simple—collect more and more data. While excuses like it is too expensive, too extensive and too impractical is convenient to publicize, the real question is how can this idea of progress be called real progress when it fails to take into account almost half of the total population of the world! What research is an effective research if it chooses to do away with the experiences of women! What solutions are really inclusive solutions if they simply ignore the solutions that could come from half of the world’s population?
Thus, failing to collect data on women and their lives would mean that we continue to naturalise sex and gender discrimination—while at the same time somehow being ignorant of the existence of such forms of discrimination.
Nobody is arguing that bridging the gender-data gaps will translate into elimination of sexism or bring equality overnight. But it is not an exaggeration to say that bridging the gender-data gaps is a big step in the process of moving towards an inclusive world, which can pave a way for equality. And that is not a bad idea to strive for, even if one is to think in terms of the larger benefit accruing from this for the cause of humanity!
References
Invisible Women: Data Bias in a world designed for Men by Caroline Criado Perez, 2019.
Featured Image Source: Financial Times
