The book Invisible Women is a highly significant and well researched book that highlights how most of the recorded human history is one big data gap, wherein the lives of men have been taken to represent those of humans overall. What ensues from this is therefore a huge gender data gap, embodying centuries of silence when it comes to representation of the other half of humanity, i.e women. The entire culture, be it our history, the stories, theatre, art, medicine, economy, politics, science, planning, etc are but a reflection of that data gap which has inevitably resulted in a word designed for men. A world which is bias towards men.
Invisible Women: Data Bias in a World Designed For Men 2019
Author: Caroline Criado Perez
Publisher: Abrams Press, New York; 2019
Major Themes And Structure Of The Book
Invisible Women is structured into six broad parts, running up to sixteen chapters, with each part focusing on diverse aspects of our world, like the daily life, the workplace, the world of medicine, planning and the public life.
The question of gender-data gap is flagged in each chapter to highlight the diverse planes where in the gender-data gap has had serious ramifications, often in ways difficult to capture in one simple glance and other times, with life-threatening consequences.
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, argues the author. 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.
Thus, the main argument goes, that if we are designing a world that is meant for everyone, we will need women in the room too. Therefore, failing to include women’s perspective, which comes to pass itself as gender-neutral, is in fact the recipe of intended or unintended design biased towards men.
Theoretical Underpinnings And Understanding Gender Data Gap
The book basis its idea of representation derived from that of Simone De Beauvoir’s. 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.
The book at the outset differentiates sex from gender, and reiterates the significant of both for women, as they navigate this world constructed on male data. The “Invisible Women” is precisely a story about this absence called data-gap and in places where the data is collected, there is no sex-disaggregated data; and where we do have data, it is conveniently overlooked.
The women thus happen to be perceived, not as the other sex but as the ‘second sex’ as Beauvoir had put it ages ago. Women is seen not as an autonomous being, but as a being in relation to men. Men’s experience is taken as the universal parameter to design the world for both, men and women.
Invisible For Count And Visible For Subserving
Women are more likely than men to use public transport and the travel patterns of women are likely to be difficult than men. While women would travel to drop kids to school, for work, for taking a relative to 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 comes 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 gap 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 of return for relaxations. 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 for rest or relaxation, but double work. When planners fail to take into account women’s need, public spaces too become men’s spaces by default.
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 these 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 large extend 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.
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 not seeing any of this discrimination. In words of the author, “It’s the irony of being a woman: at once hyper-visible when it comes to being treated as the subservient sex class, and invisible when it counts- when it comes to being counted”.
The Disaster That Is Gender Data Gap
In times of war, conflicts, natural disaster, pandemics- all the usual 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 disastrous. 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 in the case 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 are there 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, 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 this gender-data gap is a function of sexism, “a symptom of a world that believes women’s lives are less important than ‘human’ lives, where ‘human’ means male”.
Featured Image Source: Women You Should Know