Few people admit to being prejudiced, but from a very early age, we are inundated with subliminal messages. From the toys we play with to the media we consume, we are subjected to a constant stream of subtle (and not so subtle) stereotypes about different groups of people. These stereotypes affect our perceptions of people based on their race, ethnicity, religion, gender, sexual orientation, class, language, disability, and other aspects of identity.
In this article, we look at the impact of social stereotyping.
Social stereotyping affects our feelings, thoughts and behavior.
Stereotyping promotes favoritism and prejudice, often on an unconscious level. Just as often, however, the bias is conscious and overt. There is obviously no shortage of examples of discrimination in our world, but one worth mentioning here is the ongoing persecution of LGBTQ people in Russia.
In recent years, the Russian government has implemented legislation targeting the country’s LGBTQ community. This series of laws cites that all LGBTQ organizations must register as “foreign agents.” The regulations ban all depictions of homosexuality in front of young people, including rainbow flags. LGBTQ groups in Russia are now banned from organizing pride parades.
The tone adopted by some Russian media outlets reflects these attitudes. For example, one publication recently portrayed the LGBTQ community as an “aggressive minority,” claiming that their children have venereal disease. Another famous Russian news anchor stated that the internal organs of LGBTQ car accident victims were unfit for use as transplants and should be “buried or burnt” instead.
It is easy to see the effect anti-LGBTQ prejudice is having in Russia, particularly when it is backed by authorities and disseminated in the media at such a high level. However, sometimes bias takes much more subtle forms.
Implicit stereotyping is the process of unconsciously attributing certain qualities to a specific social group.
One persistent stereotype is that boys are better at math, while girls are better at reading and language arts. This stereotype is deeply entrenched—even among educated people in the most advanced societies. Its roots run deep, but is public perception really based on fact?
This widely held belief would, on the face of it, seem to hold true. Although boys and girls perform similarly at the preschool and elementary school level, once they reach high school and college, the gap begins to widen, particularly between high-performing students. Boys do tend to perform better in math, among school top performers. But why do these gender gaps start to appear?
One potential reason is that boys tend to have a more positive attitude toward math. Math anxiety is more common in girls. Even when boys and girls perform at similar levels, girls are often less sure of themselves. It’s not hard to understand that, if girls constantly hear that they aren’t good at math, or that math isn’t “for” them, they will feel less confident about it. The stereotype becomes a self-fulfilling prophecy.
A recent study published in the UK’s Independent newspaper revealed that more than 50% of British teachers admitted to subconscious stereotyping about girls and boys in relation to STEM (science, technology, engineering, and math) subjects. In addition, 54% of teachers said that they knew of a female student who had dropped a STEM class because of pressure from their parents.
In the UK today, just 14% of the STEM workforce is female, yet the country is experiencing a serious shortage of skilled workers. Women are consistently underrepresented across all scientific fields.
Speaking with the Independent, Accenture Technology senior managing director Emma McGuigan explained that that we need to do more to spark girls’ interest in STEM careers. We need to help them see beyond traditional, outdated stereotypes, to show them that they can succeed and thrive in STEM degree programs and careers.
Bias has harmful effects on recruiting and staffing.
Human biases also affect the recruitment process, both consciously and unconsciously. Bias can start to creep in from the moment of contact, when a recruiter first sees a candidate’s name, picture, or even their address. Our brains start to make connections between these bits of information and what we think we know about people with similar attributes. Whether consciously or unconsciously, we often fall back on stereotypes when we do this, and that’s where the problems begin. At its most harmful, this kind of bias reinforces racism and denies opportunities to members of disadvantaged groups.
For instance, a large 2017 study by researchers from Northwestern University, Harvard, and the Institute for Social Research found that white job applicants received 36% more callbacks than equally qualified African American applicants, and 24% more callbacks than Latinos.
Other examples of bias in recruiting may seem less malignant, but they still can cause problems and hinder diversity goals. The similarity attraction bias refers to the human tendency to instinctively like people who we perceive as similar to us. This may not sound sinister, but in hiring, it can hamper diversity and cause companies to pass on talented candidates simply because the recruiter did not feel a personal affinity with them. It can also result in situations where a recruiter promotes a candidate based on the fact that they went to the same university—though this has nothing to do with the candidate’s ability to succeed on the job.
AI offers a solution to the problem of human bias and stereotyping in recruitment.
Censia offers an intelligent talent platform that helps recruiters identify and engage with talent while minimizing the effects of bias. Their product allows hiring teams to create ideal candidate models based on up to 140 different attributes of real top performers within their company or industry. The technology then cross-references this information across a large database of talented professionals, finding the perfect person for the job.
Censia’s core mission is to eliminate human stereotyping, discrimination, and bias from the recruitment process. The company works with a number of multinational organizations, including Anthem, The World Bank, and L’Oréal.