Hello! I am Brandy. In my last post, I talked about my transition into tech and some of the unexpected labels that I encountered as a black woman in STEM. Today, I will address the imposter syndrome that I suffered from as a result of this newfound “attention.”
Unpacking reality
I came home from the conference burdened. I was already carrying the requisite imposter syndrome as a junior developer. Wondering, “am I good enough, smart enough, technical enough” to be equal with other devs. I knew from talking to other women developers that the extra weight of wondering, “Am I good enough, smart enough, technical enough” to be equal to men developers was normal. The additional weight of wondering, “Am I good enough, smart enough, technical enough” to be equal to men developers and white women developers was something I felt alone carrying. I mean, am I unicorn? Do I even exist? Should I be here? Do I belong here? Even if “here” was Detroit, it suddenly felt like I wasn’t home anymore.
I tackled this stress the way I tackle many things… I turned to Google. I started to research where all the black people in tech were. Specifically, where were all the black women? I discovered it’s not as bad as we think it is.
It’s far worse.
Notable data points:
- Detroit, Michigan is about 80% black, while nationally black people make up about 13% of the population.
- The Metro Detroit area is ranked 3rd in percentage of tech jobs in the nation, but only 5% of Science and Engineering jobs are held by black professionals (that’s in comparison to the 12% we make up in the workforce).
- And women, while we are about 50% of the population, only make up 25% of computing jobs.
- Black women, specifically, only make up 3% of the computing workforce.
To simplify statistically, theoretically, there were at most 75 black women developers out of the 2500 attendees at that conference. Houston, we have a racism problem.
Sound the alarm! All hands on deck! Oh wait… this is a known issue? Yes. This bug in our system is well-documented and has been reported by millions of users. The tech industry product owners have heard the complaints and put a bug fix card at the top of the To Do column. There aren’t enough unicorns, so obviously the solution is to create more unicorns Hence the creation of 300 boot camps in the United States and Canada.
Unicorn Factories
Organizations have popped up to reach out and engage youth in tech, in an effort to break the cycle early. This makes sense, right? If you lack resources, then you have to find a way to generate those resources. Alternative education pathways into technology are something I support wholeheartedly. This is an area where I am decidedly biased because it’s how I got in.
I got into tech by joining the Detroit Labs Apprenticeship program. I started D-Code, a high school program that teaches students JavaScript basics, to bridge the tech education gap for youth in Detroit. I support bringing in more folks who bring with them diversity in training and ideology into a company. I’m absolutely for going into underserved communities to share the possibilities that careers in tech provide. Yet, I couldn’t help wondering if this was THE solution. So I kept researching.
In the year I started my journey into tech, 2.6% of the computer science degrees given were awarded to black women. A year later, 47,000 black women were employed as computer scientists. Yet at the same time, 6% of underrepresented women are educated and unemployed in the science and engineering fields (in comparison to 3% and 2.8% of white men and women respectively). That’s twice as high. Out of these unemployed, underrepresented women, 18.6% of those state the reason as being unable to find a position (compare that to 9.2% of white men and 9.8% of white women). Unable to find a position. The United States is nearing one million unfilled computer engineering positions. It occurred to me that this is not “simply” a scarcity of black women in the field, but an even larger issue of getting these women into positions in which their skills can be fully utilized.
Calling the Plumber
So if it’s not the resource pools, then it MUST be the pipelines they’re being put in, Right? When companies as large and powerful as Facebook release diversity statistics, everyone pays attention. The numbers were stark, but Google had a plan to improve them. Enter “unconscious bias awareness training.” Because it’s important for hiring managers to understand they have unconscious biases. And once they are aware, they can use “blind hiring” practices and software to keep them from facing those biases — or at least allow them to hold off on being biased until the face-to-face interview, where studies have shown that underrepresented applicants are often even more heavily penalized.
So, what happens to black women who do manage to get into tech? 56% of all women who fight their way to get out of the resource pool and down the leaky pipeline end up leaving the tech industry within 12 years. This is twice the attrition rate of men. It’s not about “family planning” either, because only about 20% of women in non-STEM fields left their industries over a 30-year period. So what’s happening to women in tech? I’m glad you asked. 48% of black women stated they felt stalled in their careers. And I don’t know about you, but I wouldn’t want to stay somewhere I felt stuck while I watched others zoom ahead. And I’m sure that if you were one of those stuck women, knowing your coworkers didn’t see diversity as the problem you did would be a sign to see the exit (see Atlassian’s 2017 State of Diversity Report).
I think it’s time we come to terms with reality. Hotfixes and patches won’t fix this problem. We need to do a complete re-arch. A total system refactor. And I know how that sounds. I know the same reason we end up struggling and hating our legacy code bases are the same reasons refactoring them is complicated. We feel like we’ve built ourselves into a box and moving a single method will crash the whole system. I know. And I think we should do it anyway.
Sources:
- http://time.com/3849218/google-diversity-investment/
- https://www.nsf.gov/statistics/2017/nsf17310/
- https://www.ncwit.org/sites/default/files/resources/btn03232017web.pdf
- https://www.ncwit.org/sites/default/files/resources/ncwitwomen-in-it2016-full-report_final-web06012016.pdf
- http://www.michipreneur.com/7-must-know-facts-about-detroits-tech-industry/
- https://www.forbes.com/sites/ellenhuet/2015/11/02/rise-of-the-bias-busters-how-unconscious-bias-became-silicon-valleys-newest-target/#5b1b391219b5