Very, very few kids in my modest community graduated university. The odds of me making it to university were slim, and the odds of me ending up being a woman who’d dare have her say on the impact of technology were slim to none. So, when I read today that only 15 per cent of scientists come from working-class households. It struck close to home.
The stats about women in STEM are also shockingly low and cause concern for how AI is developed, used and what it is used for.
The scientists determine “the kinds of questions we ask, the kinds of problems we think worth tackling and the ways in which we go about doing our work,” argues Dr James Moore, from Goldsmiths, University of London.
So who will be deciding how AI is implemented?
Women in Business?
Businesses are naturally fueled by ambitious, educated, creative leaders and they are excited about innovation. Unfortunately, from start-ups to entrepreneurs to CEO’s, women are too few.
I’d like the next AI business map to look at how many of those are women and what role they have.
Women in Parliament?
UN reports that women’s representation in local governments make a huge difference. The number of drinking water projects in areas with women-led councils was 62 per cent higher than in those with men-led councils. In Norway, a direct causal relationship between the presence of women in municipal councils and childcare coverage was found. In Canada, the parliamentary gap persists and women represent 25% of elected officials.
So, women aren’t represented enough in parliament, STEM nor in business.
Where are women? Stats in Canada indicated close to 70% are in the social sector such as education, administration, social work, health etc.
We’ve seen incremental increase of women in politics this year. It actually is an area that can change relatively quickly if we try hard. However, the reasons underlying why the number of women in STEM, especially computer science, has in fact dropped over the past 50 years (!) and why women take less risk and prefer stable salaried positions to being entrepreneurs are more complex. It makes them both sectors that require taking the time to understand the system we’re trying to change.
For example, I’ve been curious about the impact of business legal formats on the mission of an organization. Is supporting financially one format over the other, say profit versus non-profit, sending the message that one is better and more important?
If a strong majority of women are in the social sector, which legal format are they most likely to choose if they had the chance, the opportunity to start their own organization?
If non-profit social entrepreneurship was supported financially by the next budget, would more women get into “business” faster?
My other theory is that getting AI into the hands of the social sector will empower women and ensure a better implementation of AI. It is done at the University of Southern California. They joined the Engineering Faculty and the Social Work Faculty and apply AI systems to Social Work research and their projects are inspiring.
Keeping in mind, how AI is implemented is determined by who decides what “questions we ask, the problems we think worth tackling and the ways in which we go about doing our work”, we should do everything we can to make AI interesting, appealing, accessible to women in the sector that they are in. Currently, 67% of them are in the social sector.
Besides, recent numbers show that companies with people in Humanities, Engineering, Art and Technology (HEAT) show the best results in creative and innovative thinking. Proactively seeking out women in art and humanities supports the creation of a more entrepreneurial society, leading the race to become world leaders in the implementation of AI.
So, for Women’s Day 2018, I wish us all a creative, inclusive, fundamentally innovative, ethical and exciting year in implementing AI together.