The Gender Disparity in Computer Science

By Sashrika Pandey

Credit: wocintechchat.com

In late June, headlines in the technology industry stated the conclusions of a recently published study: this century will not see women publishing the equivalent amount of computer science research as men, based on the most optimistic analysis of past trends. With an apparent increase in the representation of female scientists and coding organizations that aid underrepresented groups, it was disheartening to hear that there are still decades before parity is projected to be achieved. It appears as if this trend has been occurring for decades - women continue to face barriers to entry in technology fields, even with the advent of new products and job opportunities, but any hope for a clear solution is shrouded in years of stereotypes and deeply rooted obstacles in industry and academia alike. With both a gender gap and wage gap in STEM fields, how can incoming computer scientists counter a system that seems to be built against them?

On a social scale, it appears that young women exposed to computer science may shy away from the field based on the stereotypes around it. A study conducted through Microsoft found that 91% of girls and 80% of young women would describe themselves as creative, which conflicts with the traditional description of programming as a purely logical occupation. Placing all of the different aspects of STEM under a specific label inhibits people from making connections with the other parts of the field that may not all fall in that category. Many students may not explore STEM fields because of the traditional descriptions of tech, and without having introductory courses or direct experiences with the field, they may never be able to ignite their interest in STEM. According to BBC, a report from the Council for the Curriculum, Examinations and Assessment found that girls were often uncomfortable with studying computer-related disciplines and felt a pressure to perform better if they did end up pursuing computing. ​

The underlying issues that contribute to the gender gap in computer science also include stereotypes and access to resources. According to the Harvard Business Review, women are often inhibited from pursuing careers in engineering just as men are inhibited from pursuing careers in female-dominated fields like nursing. While we would assume that an influx of new technologies would lead to an increase in job opportunities across the board, 60% of these opportunities in the United States are opened in male-dominated fields. Countering the stigma behind pursuing a career in technical work is definitely a problem that needs to be addressed but creating solutions to increase opportunities to work in newer technologies is also a larger issue that must be considered. The United Nations states that professionals in the field of artificial intelligence are only 22% female globally, according to the World Economic Forum’s Global Gender Gap Report.

The implications of not addressing this issue are apparent in present-day industry. Back in 2018, Amazon used a hiring tool that was trained on data from the past decade, which included a majority of men and therefore, when put into implementation, negatively responded to resumes that included the term “woman.” Amazon did scrap the hiring tool but this event illustrates the magnitude of allowing stereotypes in technology to persist as we grow increasingly reliant on past data and research to improve our future innovations. Even if these stereotypes are unconscious, the technology industry could severely restrict its potential success in the future if its foundation accepts the same social stigmas that past industries have failed to address. The Guardian cites a correlation between companies in the top 25% for gender diversity and ethnic diversity and procuring better results than their competitors. Acknowledging the benefits of diversity is a crucial first step but implementing these strategies in emerging and innovative industries is essential to consistent growth moving forward.

So how do we fix a system that’s been broken for decades? It’s key to learn from the past and see how advancements can gradually be made. The BBC cites a study that found that having strong role models could encourage young women to study computing. After all, being able to see someone’s journey is inspirational to anyone who wants to follow a similar route. From an interview with two women who had had differing experiences in pursuing a career in tech, Forbes found that support networks were a key component of why one of the interviewees was able to continue her studies in computer science. An interviewee also mentioned that “a wider cultural shift” was needed. And to find a long term solution to the disparity between the genders in computer science, it is true that such a reckoning is necessary.

Whether a combination of the aforementioned solutions or an emphasis on one concept is necessary to overturn the disparity in gender representation in computer science, it must be acknowledged that changes do need to be made. Tech is moving the world forward - we see it in our daily lives as much as we see it in the movies. Our constant consumption of newer pieces of technology just hints at the world we may live in ten, twenty years from now. Therefore, pushing for change in the tech industry must be a goal that we work towards together to aid both women and men. Rather than referencing technology as another industry that failed to avoid the mistakes of past enterprises, we must aim for it to be a shining example of successful social change. That begins with encouraging young women to consider careers that they may not have been exposed to and to break down the stereotypes that inhibit male and female students alike from pursuing their interests. We owe it to future generations that we only look to the past for guidance of what mistakes to avoid, not for instructions on how to replicate obsolete institutions.

So, let’s get to work.

Sources:

Chiu, Bonnie. “How Coding Has Changed (And Not) For Women In The Past 30 Years.” Forbes. 12 Jul 2019. https://www.forbes.com/sites/bonniechiu/2019/07/12/how-coding-has-changed-and-not-for-women-in-the-past-30-years/#2a8ff4a83498

Woolston, Chris. “Scientists’ salary data highlight US$18,000 gender pay gap.” Nature. 2019. https://www.nature.com/articles/d41586-019-00220-y

Madgavkar, Anu; Krishnan, Mekala; & Ellingrud, Kweilin. “Will Automation Improve Work for Women — or Make It Worse?” Harvard Business Review. 3 Jul 2019. https://hbr.org/2019/07/will-automation-improve-work-for-women-or-make-it-worse

Meredith, Robbie. “Computer ‘geek’ stereotype puts girls off subject.” BBC News. 19 Jun 2019. https://www.bbc.com/news/uk-northern-ireland-48679123

Baron, Jessica. “We Have A Long Way To Go Before Women Are Equally Represented In The Sciences.” Forbes. 11 Feb 2019. https://www.forbes.com/sites/jessicabaron/2019/02/11/we-have-a-long-way-to-go-before-women-are-equally-represented-in-the-sciences/#5272df0d6168

Metz, Cade. “The Gender Gap in Computer Science Research Won’t Close for 100 Years.” New York Times. 21 Jun 2019. https://www.nytimes.com/2019/06/21/technology/gender-gap-tech-computer-science.html

“More women and girls needed in the sciences to solve world’s biggest challenges.” UN News. 11 Feb 2019. https://news.un.org/en/story/2019/02/1032221

Bernal, Natasha. “UK AI gender diversity is in 'crisis' as number of female scientists drops.” Telegraph. 17 Jul 2019. https://www.telegraph.co.uk/technology/2019/07/17/uk-ai-gender-diversity-crisis-number-female-scientists-drops/

Cook, James. “Amazon scraps 'sexist AI' recruiting tool that showed bias against women.” Telegraph. 10 Oct 2018. https://www.telegraph.co.uk/technology/2018/10/10/amazon-scraps-sexist-ai-recruiting-tool-showed-bias-against/

Atcheson, Sheree. “To create better solutions, the tech industry needs to build diversity into everything it does.” Guardian. 9 Jul 2019. https://www.theguardian.com/careers/2019/jul/09/to-create-better-solutions-the-tech-industry-needs-to-build-diversity-into-everything-it-does