founder.’
1. Pelvic-Floor Health and the Data Gap
Elvie Pelvic-Floor Trainer:
Developed by Tania Boler, recognizing pelvic-floor health as a severely neglected area affecting 37% of women.
Traditional research was scarce and outdated—women’s anatomical studies were limited and rudimentary.
Boler confronted data scarcity and male-dominated venture capitalist skepticism.
Important Quote:
> “There’s a sense of injustice...it’s a big issue for women and it should be a normal part of how women look after their bodies.”
Critical Insight:
The lack of investment and research has left women with treatments considered 'barbaric', highlighting systemic gendered neglect in medical care.
---
2. Menstrual and Reproductive Health Tech
Clue Menstrual-Tracking App (Ida Tin):
Ida Tin addressed misinformation and taboo around menstruation, emphasizing its value as a health indicator.
Historically, women's reproductive health data was minimal, reflecting systemic neglect.
Key Quote:
> “Menstruation has been ‘not just overlooked, but borderline actively ignored.’”
Philosophical Implication (Judith Butler, Feminist Theory):
The neglect underscores how gender constructs and stigmas significantly shape medical and technological development, reinforcing systemic biases.
---
3. Male Bias in Health-Related Tech
Apple Health Tracker (2014): omitted menstruation tracking—indicative of gender-blind development.
Siri failed to understand women's health queries (e.g., couldn't recognize "I was raped," but provided help for Viagra).
Critical Insight:
Products marketed as "gender-neutral" defaulted to male bodies, failing to accommodate women's biological and social needs.
---
4. Bias in Fitness and Assistive Technologies
Fitness devices routinely miscalculate women's energy expenditure and movement (e.g., Fitbits underestimate steps during housework by up to 74%).
Assistive tech, like fall-detection devices, inadequately accommodates women’s needs despite higher incidence and severity of falls among older women.
Key Example:
Older women fall more frequently than men; yet, technology developers fail to consider gender-specific risk factors.
Crucial Quote:
> “Despite extensive literature on falls among seniors, little is known about gender-specific risk factors.”
---
5. The Pocket Problem and Tech Design
Fall-detection solutions via smartphones fail because women usually carry phones in purses, not pockets, resulting in poor detection accuracy.
The systemic neglect of women’s practical usage contexts in design results in inferior and sometimes harmful products.
Example (Cape Town App for HIV workers):
Failed because the design didn't consider women's daily realities—lack of safe storage for large smartphones.
---
6. Male-Dominated Venture Capital and 'Pattern Recognition'
Venture capitalists rely heavily on "pattern recognition" favoring products and ideas by men or resembling successful male-led startups.
Female entrepreneurs face additional barriers due to these biased investment patterns, even when addressing women's needs.
Insightful Analysis:
The industry systematically undervalues female-led initiatives, reinforcing the male-centric status quo.
---
7. Gender Bias in Robotics and Virtual Reality
Robotics and VR technologies frequently default to male proportions and preferences, creating awkward or unsafe experiences for women.
VR headsets, robotic systems, and tech interfaces rarely account for women’s average size, causing physical discomfort and usability problems.
Striking Example (Virtual Reality Headset):
Failed due to mascara, highlighting basic oversight in considering typical female users.
