As an EECS major, I usually have the same thoughts as I walk to my new classes for the first time each semester. “I wonder if so-and-so from last semester is taking this class too?”, “How long are these projects going to take?”, and “Oh god, I hope we don’t have to do ice-breakers”. Once I arrive, I look around the room to find a place to sit. This quick glance around the room re-affirms what I assumed would be true… there are WAY more men than women in this class. While it may seem like the only thing this affects is the likelihood that I find a new girlfriend, it actually plays into Phillip Brey’s idea of pre-existing biases in technology. So how do the demographics of my EECS courses exactly relate to Brey’s theories?
First, you need to understand that Brey describes pre-existing biases as values and attitudes that exist prior to the design of a system. He states that these biases can arise in two ways, one of which is through the values of those who have a significant input into the design of the systems. Those with a significant input into the design of these technological systems are for the most part people with computer science knowledge, and as we can see from my EECS courses, the large majority of these people are men. And if you’re thinking that I can’t assume that there is a gender disparity in the computer science field based solely off of the demographics of my classes, you’d be right, but I will say that recent studies estimate that women will hold only 20 percent of computing jobs by 2025. So yea, don’t try to fact check me.
Anyways, with men holding such a large portion of computing jobs, it is hard to prevent these pre-existing biases from arising in technology. An example of this is gender biases in AI. This has been shown in natural language processing (NLP), a critical ingredient of things like Amazon’s Alexa and Apple’s Siri, displaying gender-word biases, and Amazon recruitment tools ranking equally qualified female candidates lower than their male counterparts as a result of being written and tested with males in mind.
Unfortunately, until the gender ratio in computing closes, these pre-existing biases will likely remain and cause more and more problems as technology becomes ever more important.
I really enjoyed reading this post. You had a very strong voice, and it almost felt like we were having a personal conversation. As a woman in CS, I can relate to this topic. In a classroom with 20 students, I am usually one of three girls. To be honest, I didn't realize that men also notice this gender imbalance until reading your post.
ReplyDeleteI thought that your references to Brey were very well done, and your examples made sense in the context of the post. However, I wish you had cited your sources. In particular, I would have liked to read about the study claiming that women will hold only 20% of computing jobs by 2020. Also, if possible, I would have liked to have heard your suggestion for a call to action. Do you think it's possible to eliminate this gender bias? If so, how? Overall, really good job with this post!