The technology industry appears to have a diversity problem. While there may be more women than ever in Science, Technology, Engineering, and Math (STEM) careers, they are still underrepresented
in most career fields.
The problem even exists in the pipeline of workers, too. Almost twice as many women enroll in postsecondary education as men do, and women graduate from college at higher rates than their male peers. Even a majority of STEM students are women,
although largely concentrated in degrees related to health professions. But despite
having a clear edge on enrollment and graduation numbers, women are still underrepresented
in math, engineering, and the physical sciences.
The gender disparity in technology fields is an issue we need to address. Technology careers confer high
salaries, and STEM workers solve problems that demand a creativity that we cannot
rightly expect to access if half the population doesn’t consider the field an option
for work. Accordingly, information systems researchers have put a lot of thought into
the intersection of gender, diversity more generally, and technology interest.
But we may be asking the wrong questions about diversity in STEM fields.
Zachary Steelman, associate professor of information systems at the University of Arkansas, says that
there has been inadequate attention placed on individual differences that better explain
the disparity in technology education and career paths. In their recent article, “What
Makes One Intrinsically Interested in IT?,” Steelman, Ronnie Jia and Heather H. Jia argue for an empathizing-systemizing model of technology interest that roots our
career interests in the biological structures of our brains.
The researchers adopted the empathizing-systemizing model from autism spectrum research,
and when they applied it to technology interest (generally, not skill), gender differences
became insignificant. More importantly, their research suggests this model can be applied and generalized across cultures. Steelman, Jia, and Jia say that using this measure of autism spectrum tendencies
better explains the gender disparity in STEM fields without further reinforcing gender
stereotypes.
Systemizing and Technology Interest
Individuals show clear preferences for habits of thought, which are largely divided
between empathizing and systemizing tendencies. Empathizing helps us predict our social
world, whereas the systemizing dimension analyzes and builds rule-based systems. Neither
is better or worse. Rather, they both help us solve different problems.
The empathizing-systemizing model suggests that a great deal of our own interests may indeed be out of our own hands, even before culture swoops in to muddy our agency too. People with autism are hyper-systemizing. There also appears to be a genetic link between systemizing and autism. Moreover, far more males are diagnosed with autism than females are.
Research has shown that students in STEM fields display more of a preference to systemize than their peers in the humanities and social sciences, and those with the highest
autistic tendencies are often drawn to systemizing fields. Researchers have recognized this relationship across cultures
in places such as the UK, the Netherlands, and Japan. Computers themselves are generally an appealing interest for systemizers because
they are governed by predictable, Boolean rules.
Okay, but why does this matter? The researchers can measure an autism quotient (AQ),
which allows them to infer the degree to which someone prefers systemizing or empathizing
modes of thought. Steelman, Jia, and Jia used AQ because it is largely applicable
to the general population—it reveals a continuum between diagnosed autism and subclinical cases.
But the researchers are careful to point out that AQ is not a diagnostic tool, per
se, instead, it functions as a screening tool and can help measure autistic tendencies
in the general population. The researchers and companies with neurodiversity endeavors
are less concerned with capturing clinical cases of autism so much as they are interested
in a particular habit of mind, which comes with a particular outlook and set of skills.
Steelman, Jia, and Jia had participants in both the United States and India respond
to a questionnaire to measure their AQ, systemizing quotient (SQ), and determine their
interest in technology fields. They found that higher AQs and SQs correlated with high levels of interest in technology. More interesting, the researchers found that once the empathizing-systemizing dimension
is considered, gender became an insignificant factor for an individual’s interest
in IT in both the American and Indian participant populations. That is, males and
females with the same modes of thought tend to be interested in similar intellectual
pursuits.
Gender and Tech
This doesn’t mean the gender disparity in STEM fields is natural. The researchers
are quick to remind us that their study merely measures innate interest in technology,
and there may be other contexts where gender is in fact the main driving mechanism.
Rather, these findings suggest that trying to solve this problem by addressing social constructs alone (i.e., demasculinizing
STEM) is not likely to produce the results we might hope for. Steelman, Jia, and Jia say that these findings remind us that it is important to
consider other forces that may be masquerading as gender differences.
The researchers argue that it is best to begin at the individual level and consider
what it is about an individual’s preferences that shape their interests. Exposure
and representation, while good in their own right, won’t necessarily win over new
students when women, who currently work in STEM fields, often describe themselves
as more mathematical, logical, and less social than other woman.
On a population level, women skew towards empathizing thought processes over systemizing, so the researchers urge educators and advisors to emphasize the human and social impact of STEM as much as we encourage systemizers by highlighting the formal logic of the fields.
And women in fact already do outnumber men in STEM fields where its effects on human
lives is much clearer, such as biomedical engineering. As a case in point, the researchers
cite a computer programming course offered by the University of California Berkley.
The university retitled the course “Beauty and the Joy of Programming” from its original
“Introduction to Symbolic Programming,” and consequently, more women than men began
to take the course.
Likewise, the researchers say that counselors should consider using screening tests
to identify systemizing students. In this way, they might be able to better match
academic pursuits with students’ strengths and interests.
We’ve been striving to solve the problems caused by lack of diversity in our communities
and institutions for decades. Steelman and his coauthors suggest that it may be worth
approaching those problems laterally to identify solutions we might not have intuitively
thought of.
