A couple of years ago, I attended a coding bootcamp for nine months. It was a regimented program that involved getting up at 6 AM, commuting for two hours, and then arriving at 48 Wall Street so that I, and other wide-eyed students, could code from 9 a.m. till 8 p.m. The bootcamp, with it’s ergonomic chairs and standing desks, looked like the stereotypical startup. It even had wall art. Up till this point, I wasn’t really schooled in the diversity issues associated with tech startups, though I was faintly aware of the statistics. At the start, my cohort was diverse across ages, gender, and race. Gender-wise, the ratio of men to women was nearly 1:1.
As time went on, the number of women in my cohort dwindled. This was a result of the assessment tests that had to be taken every three months. There were two major tests before the final project. If you passed, you got to move on to the next leg of the journey. If you failed, you were left behind. Another failure resulted in extermination. By the time I entered the finals, there were six others with me.
We were all guys.
It didn’t take long for us to call ourselves the Seven Samurai after watching Kurosawa’s legendary film together over the period of several lunch breaks. Kevin, the artist of the group, eventually drew a mural of anthropomorphic otters wielding katanas on a whiteboard. Looking back on my time there, I never truly paused to consider how much of a statistic we were. The lack of females aside, I was the only African American in the group. There were three Asians and three whites. My cohort was a snapshot of Silicon Valley.
It’s important to understand how damaging the lack of diversity in the tech industry is seeing that our world revolves around startups from Venmo to Uber to Postmates. On its rules page Twitter claims, “We believe that everyone should have the power to create and share ideas and information instantly, without barriers.” What this mantra doesn’t anticipate is that some voices have a disproportionate advantage over others, and that “everyone” is viewed through the white heterosexual male lens.
Facebook, according to its latest diversity report, specifically has a workforce that is 5% Hispanic, 3% Black, and 1% Other. This lack of diversity in Facebook and other tech companies can result in implicit biases that rear their heads in policies. Take, for example, Facebook’s real name policy that didn’t take into account the problem of authenticating Native Americans. A more diverse workforce may have grounded the policy before it ever had a chance to take off. Or the new Apple floor that was made of glass, not taking into account that some women wear skirts.
Lack of diversity can be far more damaging than poorly thought out ideas. It can affect how the majority handle minority and womens’ right issues. A couple of past controversies involving Uber and Facebook spell out the problems of a monolithic company.
On February 2017, Susan Fowler detailed the sexual harassment and subsequent discrimination that an Uber manager put her through. According to Fowler, Uber’s response to her complaints, to paraphrase, was, “just deal with it.”
After Facebook realized in 2012 that 83 million users on the social media site were fake users, they instituted the real name policy, weeding out what they considered “fake names.” Unfortunately, the policy failed to consider authenticating Native Americans whose names weren’t considered to be real by Facebook’s real name algorithm. This caused several Native American Facebook users–as well as several other marginalized groups–to be suddenly locked out of their accounts, effectively shutting them out of their digital social circles.
All of the cases share a common thread: under-representation doesn’t allow for a proper safety net. Everyone makes mistakes, but, as problem solvers, our job is to fix those mistakes. The point of this article isn’t to lambaste tech companies, it’s to point out the obvious disparity and to offer a solution.
My mentioning the weeding out process that occurred during my bootcamp experience can be a good way to question how companies assess candidates. Perhaps white-boarding may not be advantageous to someone who had to self learn how to code and didn’t have the money to sit through advanced algorithm courses in college. Other students may not have had the opportunity to earn a Computer Science degree from a prestigious university due to poor economic backgrounds, barring them from the top companies. Perhaps, filtering systems can be modified to weigh experience over a degree.
Additionally, many would point to the pipeline of education as the root of the problem. There are articles that address this, including an article written by Roli Varma in 2006 called Making Computer Science Minority Friendly. The article undermines the pipeline argument because, as Varma claims, the “focus tends to neglect the persistence of barriers to entry and retention of minorities into CS.” Instead, she focuses on how the education system fosters intellectual growth through faculty, advisers, and peers.
The pipeline argument can sometimes look like a punt. Though the education in low income neighborhoods should be improved through increased funding, we have to consider what to do with the available pool.
I still clearly remember the moment we, the “Seven Samurai,” went in to visit our Engineering Empathy counselor for the first time. Among our more diverse groups, we’d been talking about implicit biases and the lack of diversity in tech.
“That’s it? It’s just you guys?”
She needed a few moments to collect herself.
“I can’t believe this,” she finally said. “Wow.”