The Top 10 (%) Tech Rules
Every step along the way, exclusionary hurdles are introduced to limit the candidate pool.
Working as an engineer at Google, Apple, and Twitter has afforded me a view of the hiring process that for years has produced a homogenous culture: mostly male, and significantly white and Asian. And while Apple, Facebook, Google, LinkedIn, Twitter, are publicly committed to improving diversity, the reality on the ground paints a much different picture, and processes will need to undergo drastic changes in order to make a difference.
The hiring process I have witnessed first hand goes something like this:
The Screening Process:
- Focuses on top tier schools: Berkeley, CMU, Cornell, MIT, Stanford
- Focuses on top tier companies: Facebook, Google, LinkedIn
- Emphasizes employee referrals: Bonus, stock awards
- For new grads: assemble list of questions that focus on CS fundamentals
- For experienced engineers: focus on problems that they would have had to solve if they worked at a top tier company
The Continuous Problem:
- Candidates are penalized for not knowing the curriculum of top schools
- Experience outside of top tech companies is widely dismissed
- Employee referrals deliver a less diverse candidate pool
This process is so biased it’s amazing it still exists. Every step along the way, exclusionary hurdles are introduced to limit the candidate pool. Sourcers are directed to specific companies and instructed to focus on certain schools. Recruiters are told by hiring managers that they prefer certain companies and schools over others. By the time candidates are in the on-site interview it’s clear they went to the right school, worked at the right companies and in the case of employee referrals, know the right people. They are shepherded through the process much like a child is taken to their first day at preschool.
Why is there bias against candidates that have overcome hardship or obstacles? Here is the answer:
- Top Tier tech companies are a mirror for the distribution of wealth in the United States. Of the top 10% of earners, 86.7% were White, Asian Americans were 6.8%, Hispanics 5.2% and African Americans being the least represented with 5.1%. These numbers mirror the diversity of most top tier tech companies.
Not being in the top 10% economically, overcoming struggles to obtain a college degree and/or practical experience should show adaptability, determination and tenacity. Unfortunately, unless you happen to have a path much like Tristan Walker who despite growing up in the ghetto, having his father killed, and having to navigate extreme violence and societal apathy on a daily basis, was afforded an opportunity to obtain an education from top schools, you aren’t likely to get the attention of recruiters.
This bias ensures that a majority of African Americans and Hispanics and most of the bottom 90% will always be excluded simply because of the economic state they are in.
And, the irony is that these underrepresented groups are the most valued users of the platforms that have successfully excluded them in the name of maintaining a high standard. Social networking site adoption is identical among white and black internet users: 72% of online whites and 73% of online blacks use online social networks. And for both whites and blacks, social networking site usage is near-ubiquitous among students and young adults (some 96% of black internet users ages 18-29 are social networking site users). Source
The more I research and talk to people about this, the more I realize that this is the most insidious form of discrimination. It limits wealth, knowledge, and access to power to a very small group. It perpetuates this by restricting access to students and working professionals by creating a system they cannot hope to compete in.
This is usually where the ethos of tech comes in, and I give concrete examples on what could be done, suggestions and data showing how diverse teams perform better. Instead I will turn this back on the leaders in tech who have assembled (by their own proclamations) the smartest workforce on the planet to actually solve this. The solutions themselves are not difficult. What is difficult is the humility, self reflection, and understanding that hardship is not getting an A in Combinatorics and Discrete Probability, but actually getting a CS degree from San Jose State while living at home and taking care of your younger siblings.
At one time, employers in the United States valued that work ethic and overcoming odds. Now, we hold it against people by maintaining a ‘high bar’. The bar that is now in place at many of these companies would exclude most of the innovators who built the foundation of Silicon Valley. These innovators knew the value of diversity and different perspectives, they understood that top 10% was meaningless when it came to innovation. They also understood that diverse teams produce better results. And if you take a look back on Silicon Valley, you will see women engineers and designers at Apple in the 80s, an African-American running Symantec during its 90s growth period, and many other companies having college dropouts and liberal arts majors working to create the future we all live in.
I am not optimistic about the future of diversity in tech. I see too many of my co-workers ask what university before they ask what applicants have accomplished. I see bias in the CS questions culled from the top universities, and preference given to candidates from the top companies, referred by their peers. The system now serves itself. And that will be the hardest habit to break.