The Core Belief Keeping Marginalized Groups Out of Tech
Two ideas conspire to drive underrepresented groups from the field: the belief that innate ability and brilliance are required to succeed; and the belief that certain groups of people do not have that innate brilliance.
“Sometimes the situation is only a problem because it is looked at in a certain way. Looked at in another way, the right course of action may be so obvious that the problem no longer exists.” – Edward de Bono
We hear constant complaints about the “talent shortage” from our peers in the tech industry. The refrain is sounded on stages, and in news articles and think pieces across the field; big tech is throwing millions of dollars at the “pipeline problem,” and the shortage is considered so urgent that many industry leaders have lobbied Congress to extend more visas to skilled foreigners. However, this supposed dearth of talent could be solved at a stroke simply by looking for it where we aren’t used to looking: within the large population of marginalized people tech has been keeping out.
Women and people of color are strongly underrepresented in technical roles in the US software industry. The best available data shows that women make up about 15% of technical staff. The Bureau of Labor Statistics has more optimistic numbers for women in computer and information management, at 27%, but reports only slightly more than 5% Black and 5% Latino workers in those ranks; a 2012 AFL-CIO study also reports Black and Latino workers in math and computing occupations at 6% – 7% [source]. We don’t have good data on the exit of minority populations from tech, but we know that women drop out of the technology industry at a much higher rate than men: after 10 years, 41% of women will leave their technology careers compared to 17% of men. This is not because they are dropping out of the workforce, but because they are switching to non-STEM careers.
We know that differences in ability aren’t behind this underrepresentation in STEM: “biological sex differences in inherent aptitude for math and science are small or nonexistent,” and the same holds true for differences across racial and ethnic groups. Sadly, research suggests it is the beliefs of professionals in the industry keeping marginalized people from joining tech, and driving out a disproportionate number of those who do.
Beliefs or Abilities: Which is More Important?
Photo CC-BY nancynance, filtered.
In particular, two beliefs conspire to drive underrepresented groups from the field: the belief that innate ability and brilliance are required to succeed; and the belief that certain groups of people do not have that innate brilliance.
These beliefs are pervasive in technology. In fact, the myth that certain software engineers are significantly better than others — the “10x developer” myth — is persistent, and it is widely assumed that these people are born and not made. For example, Paul Graham makes this assumption explicit in his article urging higher levels of immigration, “Let The Other 95% In”:
“What the anti-immigration people don’t understand is that there is a huge variation in ability between competent programmers and exceptional ones, and while you can train people to be competent, you can’t train them to be exceptional. Exceptional programmers have an aptitude for and interest in programming that is not merely the product of training.”
Unfortunately, beliefs in “innate ability” have the power to not only influence VC investing patterns — and potentially immigration policy — but also to keep minorities out of tech.
Beliefs about innate ability and their effects on gender imbalance in STEM professions were investigated by Dr. Sarah-Jane Leslie and her collaborators, and published in Science magazine in January 2015 [pdf]. This large-scale, nation-wide study examined the beliefs and work practices of STEM PhDs from multiple fields of study, and how these beliefs and practices correlated with field demographics. The study tested:
1) gender differences in willingness or ability to work long hours;
2) gender differences in the high end of the aptitude distribution (in other words, ability);
3) the extent to which a particular discipline requires systemizing (the need to understand abstract principles and rules) over empathizing (the need to understand human thoughts and feelings); and
4) the extent to which practitioners believe that raw, innate talent is the main requirement for success.
The authors found that across STEM fields, only the final hypothesis correlated in a statistically significant way with the percentage of US PhDs who were female.
In other words, there were no significant differences between men and women in the willingness or ability to work long hours, no significant differences between men and women in aptitude, and no significant gender differences around the systematic vs. empathetic nature of the field. The only significant differences were in the beliefs that innate talent was required for success. In other words, fields where professionals believed innate ability and raw talent were required for success had significantly less women. These fields? Math, physics, computer science, and engineering.
Shame on us. It is simply our belief that women lack the innate intellectual ability to do the work that is keeping them out of certain STEM fields. The research then doubles down and reports that African Americans are poorly represented for precisely the same reason — the pervasive belief that they lack the innate talent to do the work.
Unfortunately this belief also sneaks into our education system, as shown by a study from 2012 in which researchers asked 127 biology, chemistry, and physics professors from across the USA to evaluate a science laboratory manager who had just applied for the position in their lab. The professors were all given identical job application materials from an undergraduate science student, but the application packets were randomly assigned either a male or female-coded name. Participants were asked to rate the student’s “competence and hireability, as well as the amount of salary and the amount of mentoring they would offer the student.” Applicants with male names were perceived as significantly more competent and hirable, and deserving of higher pay and mentorship. Perhaps most interestingly, both male and female professors demonstrated the same bias, showing that it is not intentional or explicit but rather “shaped by implicit or unintended biases, stemming from repeated exposure to pervasive cultural stereotypes that portray women as less competent.” Other studies have shown the same effects in different domains, as well as a similar effect with regard to race. (See, for example, “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination,” Bertrand, M. and Mullainathan, S.; and “Study Reveals Ethnic Discrimination in Recruitment of Young Workers,” International Labour Organization.)
What Can We Do?
The results of the studies are clear: pervasive cultural stereotypes that “brilliance” is required to succeed in programming, and that women and people of color are less competent, are the greatest barriers to increasing and maintaining representation. There are several important steps we can take to correct these problems.
First, industry leaders and managers at every level must actively and consistently work to combat these stereotypes. We must stop talking about “10x developers,” ninjas, rockstars, and the scarcity of “talent.” The idea that you create great organizations by hiring brilliant people has been roundly debunked (for example, Enron was explicitly managed according to this principle.) As Malcolm Gladwell points out in his article on the “Talent Myth,” which expands on Enron’s collapse, it is not individuals that make organizations smart, but teams:
“…our lives are so obviously enriched by individual brilliance. Groups don’t write great novels, and a committee didn’t come up with the theory of relativity. But companies work by different rules. They don’t just create; they execute and compete and coordinate the efforts of many different people, and the organizations that are most successful at that task are the ones where the system is the star.”
Second, we must look beyond ideas of innate ability to focus on what really leads to success in the tech world. Neither software engineers nor IT operations personnel have gotten where they are simply through inherent brilliance, formal education, or training. Rather, as with sports or music, mastery is gained through repeated practice. This is highlighted in the NPR Planet Money episode “When Women Stopped Coding” by Steve Henn, which examined the steep drop-off in women’s graduation from computer science degrees that occurred in the 80s. Henn found this exodus of women from CS degrees was correlated with the rise of cheap home computers, which were targeted almost exclusively at boys. Students who spent time programming on home computers experienced a significantly easier time adjusting to the course material, causing many women — who had not had exposure to home computers — to drop out. Some universities have now redesigned their CS courses to ensure they compensate for effects like this: UC Berkeley’s CS 101 course, “The Beauty and Joy of Computing”, enrolled 106 women and 104 men in its first year. Similarly, the industry must look for innovative ways to engage with communities that haven’t traditionally been in tech, because it is these communities that may bring us the best insights and opportunities for creativity and innovation.
Photo CC-BY Kool Cats Photography, filtered.
Third, companies should review their processes and correct obvious inequalities. Review staff by role and look for statistically significant differences in salary when people are aggregated by gender and by race, then correct for them. Correct any outliers. Monitor tenure, rate of advancement and job satisfaction by gender and race, make the results visible, and update them. Examine recruiting and performance reviews for evidence of bias — are women more likely than men to be rejected in interviews for “culture fit”, or more likely to receive negative performance reviews? Do recruitment specs use language that is likely to put off women? Hire an external expert to review interactions, policies, and HR processes, make recommendations, and return regularly to monitor implementation and review progress.
Finally, companies must invest in developing their people and creating an environment where people can practice and improve. We can’t over-emphasize the extent to which many of the problems in the software industry today are the result of focusing on short-term goals and hiring the necessary talent to achieve them, rather than focusing on longer-term goals and developing our people in pursuit of them. Managers should help software developers set stretch goals for their development, provide them with the support, training and slack time to gain the necessary skills to meet these goals, and ensure the work they are doing provides opportunities to work towards them.
Fixing the underrepresentation of women and people of color in the industry is not just about making sure we have the necessary people. It is also a matter of social justice, and indeed creating better products and services. Tech jobs are extremely highly paid, provide excellent benefits, and often offer flexibility in terms of the number of hours worked or the ability to work from remote locations. It is inequitable that white men have disproportionate access to such jobs. Research also shows that group diversity leads to better outcomes, and diversity in leadership produces better organizational outcomes.
If we’re serious about fixing the talent shortage, we should start at home.
This article was originally published in the Model View Culture 2015 Quarterly Two. Support independent tech media and subscribe to our 2016 issues here.
