Why Diversity In Tech Needs To Be A Priority

Tech can be a magical place full of opportunity and innovation. Silicon Valley is and has always been cooler, and more adventurous than Wall Street, Madison Avenue, Capitol Hill and Westminster.

Because it is newer and less rigid than global stalwarts like finance, real estate and law, tech is often perceived as the playground of the young and talented, and a place where diversity and unique thinking is celebrated rather than resisted. 

One prevailing sentiment about tech is that it is a meritocracy. This means that you advance depending on your contribution and skill rather than networking, nepotism or the unconscious biases of employers. A true meritocracy is the holy grail for diversity, and there are some amazing features of the tech industry that make it the perfect prototype for a meritocratic vertical.

For starters, tech is incredibly accommodating to the self-taught. In fact, 69% of people in coding jobs label themselves as totally or partially self- taught. Now picture an industry like healthcare. Its network of prestigious specialist educational facilities and strong emphasis on academic attainment and accreditation make it incredibly hard (almost unheard of) for any type of self-taught individual to break in.

This low bar to entry seems like it would benefit diversity initiatives. It also theoretically negates the necessity to network, as jobs aren’t offered by way of a fraternity connection or familial relationship. Instead, a common tech recruitment process involves a problem solving task, which the best person for the job should have a greater chance of success in.

Another aspect of tech that primes it for greater diversity is the lack of a governing body or mandatory qualifications, like those found in the industries of law, medical practice and real estate. This means that hiring employers aren’t so much looking at what institution an applicant attended or the accreditations they have (which require intensive amounts of money and privilege to be able to attain). Instead they are usually looking at what candidates have previously built themselves. If you have an active Github account you can build a portfolio of work and apply to any role you want, rather than having to invest time and money (that a lot of minorities don’t have access to) in expensive qualifications.

Despite all these opportunities, the prospective hotbed for diversity and equity has sadly not been realised. The tech industry falls victim to the same biases and diversity blind spots as more traditional industries, but the dangers of the myth of meritocracy are exacerbated by the power many tech companies now have in influencing areas like artificial intelligence, the gig economy and social discourse.

What are the facts about diversity in tech?

Broadly speaking, the tech workforce skews massively male, and its ethnic demographics are overwhelmingly white and Asian. If we drill down into Silicon Valley firms, the combined Black, Hispanic, and Indigenous populations comprise only 5% of the total workforce, despite making up roughly 35% of the general population. Even though it’s slightly “better” in the UK, Black, Asian and minority ethic (BAME) people still only comprise 15.2% of the tech market, despite 20% of people living in the UK holding these identities.

Women also are underrepresented in computer science roles, with only 22% of the workforce identifying as female. And this is going to stir up some neckbeards to say “well maybe there are inherent differences between the genders that make men more suitable for computer science!”, and whilst I would usually just ignore it, sometimes it’s fun to pick them apart for sport.

The “inherent gender differences” argument just simply isn’t true. 75% of the people who worked on one of the first ever computers, the ENIAC, were women. The first person to ever decide that code should be written in words rather than numbers and symbols was a woman. In 1995, 37% of people in tech jobs were women and that’s trending down to 22% today. There is clearly a systemic problem that is driving women away from computer science roles rather than any ”genetic differences”.

Well, what could be affecting the hiring process? It could be that only 27% of white people in tech believe that unconscious biases affect hiring processes. 

Research has shown for decades that unconscious biases are unequivocally present in almost all people. There are studies conducted as far back as 1997 that display racial biases in a whole range of everyday life, and the number one remedy to the impact of the biases was listed as simply being aware of biases in the first place. This was over 25 years ago! And we still fall victim to them! The fact that over 70% of white people who may be hiring for tech roles completely dismiss decades worth of data (in an industry that prides itself on being data-driven), goes a long way to explain why it is harder for women and minorities to make it in.

But what about the people from minority ethnic backgrounds that actually are in tech right now? They’re not doing great according to studies. 75% of minority ethnic tech employees say they feel no sense of belonging at work. This shows that something within the actual jobs themselves, not just the hiring process, is affecting employee satisfaction levels and sense of belonging. This might be explained by the preponderance of new diversity-focused recruitment initiatives companies are currently implementing without also evaluating their overall work culture.

There’s no point renovating the door of a house built on shit foundations. Companies need to make the internal culture of their teams more inclusive whilst also working on hiring a more representative workforce.

This all paints a grim picture that is worlds apart from what I outlined in the opening paragraphs. So how did an industry with so much potential end up goofing it that hard?

Why does tech have these diversity problems?

When you consider a tech hub like Silicon Valley, one major barrier to entry is the rent. It’s too damn high. Minority ethnic groups are far less likely to come from more affluent backgrounds, meaning the more influential and profitable jobs go to people with the ability to survive in a competitive rent market on an entry level salary. The pandemic offered a reprieve from this issue, but sadly with more and more tech firms determined to force employees back to the office, it looks like this problem will continue to affect the industry.

Another aspect is that the most advanced positions, like those working with AI and quantum computing, are incredibly competitive. This means that firms compete for graduates from top level universities to quickly excel and grow. 

A firm on the cusp of creating a cutting edge product is more likely to pick someone who graduated top of their class in Computer Science in Stanford than someone who taught themself Python in their spare time. It’s a safer bet to take an accredited student vs a self taught one, and because tech primarily exists within the same capitalist structures other industries do, they’re going to take the safe bet every time.

It’s widely understood that higher education favours white, male students. Poorer, more ethnically diverse neighbourhoods tend to have schools with larger class sizes, which is detrimental to students’ learning and have been empirically proven to affect student attainment, meaning their access to universities and colleges is limited and they miss the chance to work on projects that shape our future as a species. 

But there is also an underlying psychological reason that white and Asian males are predominantly favoured in tech roles : a small unconscious bias called the Representativeness Heuristic. 

This bias essentially affects how we determine a person or event based on the representative model we create of the perfect version of that person or event.

An excellent example of this comes from my favourite sport: basketball. 

In 2010, a young Asian-American Harvard graduate named Jeremy Lin went undrafted in the NBA draft. 

In 2011, the same Jeremy Lin played a string of games so good he created a worldwide fever pitch known as “Linsanity”. 

How did 30 NBA teams pass up on a guy so electric that he, at one point, hit a shot so good that his opposition even cheered it? 

Because of the Representativeness Heuristic. 

Asian American players in the NBA comprise roughly 0.4% of the league, so when scouts were sent out to see whether Jeremy Lin was a good basketball player, they unconsciously checked him against their representative model of “a good basketball player”. 

As there weren’t any analogies to be drawn between Lin and any current or former players, scouts couldn’t see how good he was and rated him as “unathletic”. 

When data analysts started measuring the speed of a player's first two steps, Lin was amongst the most athletic players in the league. Because he didn’t fit a model in an old school scout's mind, Lin was passed on by the best scouts in the country.

It’s the same with tech jobs. There’s even a predominant phrase for it : tech bro. 

Computer science history is littered with straight, white men like Steve Jobs, Bill Gates, Elon Musk and Mark Zuckerberg, which can strongly influence the mental representative model a potential hirer has when looking for their next employee.

This is why diversity drives are so important. To shift the representativeness heuristic, there needs to be immediately available, real world examples of all genders and races, so the homogeneity of tech doesn’t become a self fulfilling prophecy and a true meritocracy can be established.

Why does tech's diversity problem matter?

Firstly because it’s the right thing to do. 

Not everything has to directly impact the bottom line or increase shareholder value. Providing access to jobs and giving underrepresented groups a voice in some of the most exciting and influential discussions in tech is morally right and should be pursued by all companies, not just as a company but as a collection of people who have compassion for fellow people.

But if you want stats, you know I got ‘em.

A recent McKinsey report showed that companies who focus on racial and ethnic diversity are 36% more likely to have better profit margins than their industry’s average.. Those with increased gender diversity were 21% more likely to have an above average profitability. It’s free money as well as the morally right thing to do! When has that ever happened?! Never!

Tech loves to talk about making the world a better place, but it often gets so caught up in the minutiae that it loses sight of the bigger picture. To truly advance the march of humanity, you need to actually include all of humanity in the thinking behind your solution. By ignoring well over 50% of the world’s available brainpower, the tech industry as it stands is actively slowing the progress down.