The technology sector at large struggles to attract and retain women but in open-source communities, the situation is considerably worse.
Some estimate that just 6% of GitHub contributors are women. On the occasion of Ada Lovelace Day, the annual celebration of women in technology on October 12, this week we look at what is needed to increase gender equality in open source.
Women belong in technology leadership because we think differently. It’s always cool when there’s a project tech lead who is a woman because they come in with a different background and often a new perspective. I think the way we communicate tends to be more collaborative and we think differently: We see the skills of people across different levels of the organization and outside, and so we’re able to loop them into projects.
The gender disparity in the open-source community is massive. When GitHub last surveyed its community in 2017, just 3 percent of the respondents were women. Women say they are interested in making open-source contributions about as much as men (68 percent compared with 73 percent), but fewer say it’s likely they will actually do so (45 percent versus 61 percent).
The reasons probably won’t surprise you. Respondents were more likely to encounter language or content that makes them feel unwelcome (25% vs 15%), stereotyping (12% vs 2%), and unsolicited sexual advances (6% vs 3%). As a result, women were also more likely to reach out to users they already knew as opposed to strangers (22% vs 6%).
To encourage more women to contribute to open-source projects, we need:
- Strong codes of conduct to empower community leaders to call out behaviors that contribute to women feeling unwelcome,
- Clear contributor license agreements so women have clarity on how their work can be used, and
- Flag-bearers — more women visibly contributing to open-source projects and being celebrated for it.
The problems in open-source communities are a reflection of a broader gender disparity in technology that starts in school, with women comprising just 23 percent of those taking high school Advanced Placement computer science exams, 19 percent of computer science degrees, and about 26 percent of the tech workforce.
And then there’s the so-called “leaky pipe” of women leaving technology. You’re probably familiar with the reasons by now: A dearth of opportunities, unequal pay, bro culture, and cultures of sexism. Some 53 percent of women in tech experience harassment at work, compared with 16 percent of men, and female engineers receive 83c in the dollar of a man in the same position.
A survey by nonprofit AnitaB.org found that over half of women leave technology by the mid-point of their career. Most cited environmental factors such as a dearth of management support, stymied advancement and lack of work/life balance as their reasons for leaving tech. Those who stayed in tech had women role models, a peer group, and good training.
We need continued investment in this space. We should be encouraging women not just to be engineers but to lead — as technical leads or in management. There is a narrative that women leave tech because they don’t like the work but that is a theory that doesn’t stand up to the data.
I personally want to see more women in open-source product leadership. There are lots of ways women can step up — in the boardroom, in management, but also in product repositories. I’d like to see more women encouraged to show leadership in places like GitHub threads and project direction. We should be offering more guidance and opinions on how something can technically be run.
Ada was a true visionary. She was able to see the potential in a technology that wasn’t even invented yet, and she founded an entire branch of science in the process. We as engineers must do our part to make the technology sector a place where more women feel welcome — to join, to contribute, and to lead.
Who was Ada Lovelace?
Ada Lovelace was a 19th century English mathematician who is considered the world’s first computer programmer. While working on Charles Babbage’s proposed mechanical calculator, the Analytical Machine, she saw that it could have applications beyond its original scope and published the first-known algorithm for its use. Though the machine was never constructed, hers is the first algorithm to consider that a machine could use code to compute more than just numbers.