Invisible Woman throws light on gender data bias – the practice of unconsciously ignoring the experience of women – in fields as diverse as technology, governance, workplaces and the media, highlighting how systemic problems can often cause disastrous results.
Invisible Women by Caroline Criado Perez
Invisible Women is listed as current affairs/feminism but addresses a pressing problem for both men and women alike.
Written by the writer, broadcaster and political campaigner Caroline C Perez, the book is well researched and extensive in scope and, while passionate, doesn’t come across as an ideological polemic.
Acknowledging the role of unconscious bias in Big Data, the book is also a timely read that explains not only how women have been misrepresented in the past but will likely continue to struggle in the future, as technological solutions are built from a biased dataset.
Below are some of the key insights I took from this book:
- Most of recorded human history is one big data gap prioritising the experience of white males as the default over all other identities, genders and perspectives.
- Feminism is often derided as identity politics but this assumes that anyone can step outside of their perspective into a truly neutral viewpoint.
- As a result of the male default, traffic systems and snow clearing programmes operate with an unconscious bias towards male drivers.
- Even gender neutral practices such as equal space public toilets fail to account for the different experiences of women.
- Although women have entered the [paid] workplace, measures of GDP systematically discount [unpaid] work such as childcare, housework and caring for elderly relatives.
- Expense codes are also based on the male experience discounting childcare costs for example as deductible.
- Meritocracy is a pernicious myth that is highly imperfect and is subject to societal expectations of brilliance bias that continue to shape gender viewpoints.
- Most reference systems assume the 70kg average male affecting everything from airplane cockpits, office temperature and PPE.
- The gender pay gap continues in part because women are more likely to end up in precarious employment or face social pressure to provide unpaid work for childcare.
- One-size-fits-all products and services including iPhones and Voice assistants will nearly always use a male reference point resulting in continued unconscious bias.
- Female representation in STEM subjects can be thought of as entering a gender neutral workspace which is nevertheless typically male orientated in culture.
- The pharmaceutical industry is also subject to unconscious bias basing most trials and observations on the default male human body and systematically overlooking areas of specific female concern [e.g. endometriosis]
- GDP was invented in the 1920s after the great depression but continues to be based on flawed assumptions that only count labour when it exists as paid employment.
- Governance in general is also subject to unconscious bias when setting budgetary priorities as female concerns and experiences are not adequately represented.
- Where representation exists, women often have to work harder to overcome cultural barriers and soft objections from existing power structures.
- More generally, women’s rights issues are often thought of as niche rather than universal and consequently fail to attract adequate support and invite political rebuke.
- Closing the gender data gap is an important step to achieving a more equitable society for all and should be a priority for governance worldwide.