As a twenty year old woman studying ‘Digital Humanities and Information Technology’ I have already become aware that technology appears to be substantially lacking gender balance. I can see this both in my own computer science classes and even in my workplace, so I became curious,is the divide really that large?
The first ever programmer is regarded to be Ada Lovelace.Grace Hopper was the first person to create a compiler for a programming language.Margaret Hamilton was the director of the Software Engineering Division of the MIT Instrumentation Laboratory, that developed on-board flight software for the Apollo space program(1).This is to name a few women that in the past have shaped so much of what we take for granted in tech today, so lets take a look at the largest industries of modern day to compare.
Below is a visualisation I created on ‘RAW’.I searched thoroughly and experimented with various tools I had found for visualisation purposes from the ‘DIRT directory’(A very convenient platform to discover various digital research tools).I explored various tools such as ‘Vida.io’‘Cytoscape’ ‘Gephi’and even ‘Open Processing’ .I will be sure to return to in the hopes of manipulating this open source code on Processing to give my visualisations a more interactive narrative.
The reason I chose ‘RAW’ is because it’s format was best suited to my Data i.e: I could use strings as well as numbers in a very straight forward and simplistic interface. I found this tool to be very user friendly even with a drag and drop function for my CSV file.
My visualisation below is showing the span of male and female in some of the largest technology companies in the world today.Each segment represents the gender filling that space in the company and the colours relating to the same location, predominantly
Distribution of just female workers
As you can see above, my data is showing the span of female workers in these companies.When I created this visualisation I believed that it looked as if there are quite a lot of females here,until I made the comparative below of the just male workers. Without the need of trawling through piles of data and numbers I am showing you here a direct comparative outlining that there is clearly an imbalance.
Distribution of just male workers
Here we can see a rapid increase in the amount of technology companies employing males.To ensure this data’s clarity I have created a control below with a side by side comparative. Women compared to the final total of workers(of both genders).
Judging from the findings above it appears that today technology is predominantly composed of male workers, even though it began the other way around and was even equal.
One strong theory for this downward slope include:
After the release of PC’s the marketing for computers was towards the male demographic which discouraged the female youth at the time to pursue technological careers(NPR site).
This marketing has since equalled but the culture of “bro-grammers”has developed which still discourages young women today.Even on television programmes based on technology makes this very clear e.g.:”Silicon Valley” even named the usual dynamic of programmer groups (seen here).
In an attempt to counteract this and in order to entice young women to pursue these careers the creation of workshops have been necessary to even make the addition of technology to a choice in a young girls life.
For example,the hashtag #ILookLikeAnEngineer was a campaign created to encourage young women to fill STEM-related positions that proved to be successful.It can be seen on ‘Twitter’ under that hashtag the impact that it had on young women.Common occurrences here include the girls stating how they’d not considered the career path until awareness had been raised.
In summation, the lack of women in technology/STEM related fields isn’t just in a classroom, it’s widespread worldwide. There is solid proof that this was not and will not always be the way as even just the encouragement from a campaign has proved it can increase numbers of young women.With the application of these simple steps it would be easy to recreate the gender balance that has previously been in place.
Statistics from visualisation:
CSV file(inclusive of statistics sources)