Every year since 1984, more women have left the US technology industry than have entered it.
And on Wednesday, a study revealed that female scientists receive over 30 percent less US federal funding than male grant applicants. The National Institute of Health awards an additional $41,000 to grant applications which name a man as principal author.
Women’s underrepresentation in STEM (Science-Technology-Engineering-Maths) is not news. The World Bank considers that social norms—including parental and academic expectations—information failures, and institutional factors all stifle women’s STEM aspirations.
Female participation in the lucrative domain of information & communications technology [ICT] is equally low. After all, fewer than a third of 100 top global universities offer degrees in data science.
Experts blame tech’s long, unpredictable hours and a deeply-entrenched ‘boys club’ mentality—inherited from established industries like banking, despite hopes of tech’s progressive, “disruptive” potential.
Finally, the preferment of similarly-qualified male colleagues for promotion causes a deficit of women in senior roles, depriving younger female techies of essential mentorship.
Natalie Gyenes, research fellow at Harvard Law’s Center for Internet & Society, highlights how male-centric hot-button fields like algorithmic verification currently seem. “The word ‘debunk’ is so tech bro-ey to me; it just elicits images of some guy sitting behind a desk giving us all a big check mark.”
Yet there is hope.
Asian nations like Indonesia and India are outperforming the West in terms of women entering computer science.
Happening now, the Rising 2019 is a conference for Indian women in data science, aiming to elevate visionary women in the field and pool resources on how to build careers. The International Labour Organisation recently hosted a forum for Filipino women in STEM. It highlighted chronic information voids on what career paths exist, how they could harness STEM, and existing female role models.
Even Google’s ethnic repartition of female employees reflects this: though barely over 1 in 5 tech workers at Google are women, almost half are of Asian descent.
And low and lower-middle income countries are the key drivers behind a shrinking gender gap in internet access, the Internet Inclusivity Index confirms.
Nirmalie Wiratunga, PhD, is a professor of machine learning and natural language processing. She began studying case-based reasoning during a pharmaceutical design task in 1998, motivated by what she felt was AI’s “huge potential to positively impact many industries.”
Wiratunga notes “requirements for computer power” hamper nascent enthusiasm for machine learning. This practical obstacle disproportionately affects developing countries, where electricity supplies are volatile and data storage capacities a rarity, especially in rural areas.
Wiratunga adds that in “sectors like healthcare, lack of trust and confidence in AI technology” constitute a further barrier.
As a sector, ICT has defied the global economic slump, gaining value even as other industries floundered. And in countries suffering from high gender inequality, women are flocking to STEM professions, possibly because they offer “the clearest possible path to financial freedom”.
It is crucial women are provided with opportunities, starting in secondary school, to acquire technological skills. Code is fast becoming the language which underpins the logistics of modern life; young girls must feel equally able to achieve fluency in programming.
What happens if women don’t participate in data science work?
Wiratunga believes that “a broad spectrum of views is vital to advance AI, or any other scientific research.” Only inclusive AI workforces can “ensure that technological advances cater to all walks of life, and remain mindful of society’s ethical and moral concerns.”
Credit for this article's header image goes to Getty.