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Achieving Gender Equality in CS

Did you know, 85% of AI projects will output unusable results due to human bias in 2022?

This issue is dangerous as it sparks conflict between genders, races, and beliefs but, luckily, can be solved by integrating diversity in perspectives throughout the development process. Specifically, this article will focus on how to increase female representation in the AI field.

How can we increase the number of females in CS?

There are a variety of methods that can be employed to bridge the gender gap in the tech sector, notably by supporting young girls who aspire to pursue a career in STEM. The preconceived notion of females being less skilled regarding mathematics or science often acts to pull girls away from this domain, and after college, it soon becomes too late to change their minds. To combat this, Girl Scouts have provided international STEM learning workshops to bolster girls’ interests and confidence in STEM. Through this, the company hopes to add 2.5 million females to the STEM workforce by 2025. Beyond mentorship programs, teachers could focus on teaching using interactive activities rather than with formulae, showcasing the creative nature of STEM subjects.

Furthermore, females sometimes don’t experience equity in the workplace, being implicitly discriminated against in the recruitment process. For instance, there is little information provided as to the various roles females can work in, creating ambiguity. Worse, job titles and descriptions often include gendered language, which can be fixed by emphasizing performance objectives and avoiding extreme jargon. Hence – by fostering a more inclusive environment – women will become more comfortable and set up for success.

Beyond this, the issue of unequal pay is of paramount importance. Even though the US Equal Pay Act has been enacted for 60+ years, women continue to earn 20% less than men. This discrimination urges women to leave the industry as it prevents them from progressing professionally. As such, firms should tell the public how they intend to address this problem and release updates over time, thus allowing people to gauge their progress.

In a nutshell, if we can get more women in computer science by redefining the field, we can surely work towards the overarching goal of alleviating bias in AI.

Note: One of our articles explores the consequences of gender bias in digital voice assistants. Check it out here:


Written by Amanda Y


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