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Invisible Women summary

Invisible Women book cover

An extremely important book for everyone to read. I thought I knew about female bias...turns out I didn't know the half of it. This was truly eye-opening and is a good starting gambit for anyone interested in working towards building a fairer society.

The book is really well organised with dedicated themes that the author then delves into and makes her case. At a top level, my main takeaways were:

  • Data we collect to make decisions off of is not sex-disaggregated, resulting in a significant gender data gap.
  • Males tend to be seen as the "default human". The world is mostly designed by men for men.
  • This is pretty crazy if we think about it because that's 50% of the world's population not really accounted for, which in the best case is annoying, but in the worst case could be deadly.

Daily life

  • Women's travel patterns tends to be a lot less linear than men's, due to the multiple paid/unpaid jobs they tend to take on. This penalises them from a financial and time perspective.
  • Toilets need to consider both the hygiene and safety needs of women. e.g. poorly located public toilets for women can make women very susceptible to shame and attacks.
  • The result of this deeply male-dominated culture is that the male experience, the male perspective, has come to be seen as universal, while the female experience--that of half the global population, after all--is seen as, well, niche.

Workplace

  • Women tend to take on the majority of unpaid work in society, regardless of the proportion of household income they generate.
  • There is no such thing as a woman who doesn’t work. There is only a woman who isn’t paid for her work.
  • Globally, 75% of unpaid work is done by women.
  • There is a significant gender pay gap. More data needs to be collecting as part of hiring processes to try to address this.
  • Typical working environments favours the unencumbered worker. This is disproportionately unfair to women who tend to have to take on caring duties or household duties.
  • There are occupational hazards that affect women (due to their different build) and that aren't necessarily taken into account e.g. in nursing.
  • When we exclude half of humanity from the production of knowledge we lose out on potentially transformative insights.

Design

  • Supposedly gender-neutral products are rarely that - they tend to be "one-size-fits-men". Examples include smartphones, voice-recognition software, grand pianos.
  • 93% of VCs are men and men back men. Given the male domination of VCs, data gaps are particularly problematic when it comes to tech aimed at women. It's consequently difficult for women to fund their women-centric designs.
  • Car design has a long and ignominious history of ignoring women. When a women is involved in a car crash, she is 47% more likely to be seriously injured than a man, and 71% more likely to be moderately injured. Crash test dummies are based on the average man. It was only fairly recently that the EU changed its laws to say that women also have to be accounted for.

Medicine

  • ...a medical system which, from root to tip, is systematically discriminating against women, leaving them chronically misunderstood, mistreated and misdiagnosed.
  • Because women have largely been excluded from medical research, this data is severely lacking.
  • The failure to include women in medical trials is a historical problem that has its roots in seeing the male body as the default human body.
  • The lack of sex-disaggregated data affects our ability to give women sound medical advice. Women are not men and do not function like them! e.g. women's stroke symptoms are really quite different from that of men's.
  • There are some medicines that work for men, but not women (and in cases can even be dangerous!).
  • Yentyl Syndrome is when women are misdiagnosed and poorly treated unless their symptoms or diseases conform to that of men.
  • There's a lack of funding when it comes to diseases or afflictions that only affect women.

Public life

  • Unpaid work is not included in the calculation of a country's GDP.
  • The upshot of the failure to capture all this data is that women's unpaid work seems to be seen as a costless resource to exploit.
  • There are also many examples of tax systems disadvantaging women. Together with our woman-blind approach to GDP and public spending, global tax systems are not simply failing to alleviate gendered poverty: they are driving it.
  • Urban planning that fails to account for women's risk of being sexually assaulted is a clear violation of women's equal right to public spaces.
  • When you exclude half the population from a role in governing itself, you create a gender gap a the very top.
  • The presence of women in politics makes a tangible difference to the laws that get passed.

Disaster situations

  • The presence of women at the negotiating table not only makes it more likely that an agreement will be reached, it also makes it more likely that the peace will last.
  • Women are disproportionately affected by conflict, pandemic and natural disaster.
  • Domestic violence against women increases when conflict breaks out.
  • The data gap when it comes to sexual abuse is compounded in crisis settings by powerful men who blur the lines between aid and sexual assault.
  • A 2013 UN homicide survey found that 96% of homicide perpetrators worldwide are male. So is it humans who are murderous, or men?

Conclusion

  • The introduction of Big Data into a world full of gender data gaps can magnify and accelerate already-existing discriminations. The gender data gap therefore needs to be addressed as a matter of urgent priority.
  • The author identifies 3 themes:
    • The female body - is not the same as a man's and needs to be accounted and designed for in medicine, tech, cities, architecture etc.
    • Male sexual violence against women - we need to design a world that takes this into account so as not to limit a woman's freedom.
    • Unpaid care work - this needs to be accounted for and properly valued in our societies.

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