Listen to the show here.
When we talk about bias or differential treatment, most people think of deliberate negative attitudes expressed toward a group. Social psychologists call this explicit prejudice.
But that just tells part of the story, as people can also harbor implicit prejudices and stereotypes. This represents a form of bias that is not consciously expressed. Instead, people form associations in their mind of which they are not even aware. For example, people might implicitly associate men with being good at math, or women with poor performance in that area. Even though they don’t explicitly say as much, it is the associations in their minds that are important here, as these linkages can drive behaviors.
Recently, Ernesto Reuben, of Columbia University, and his colleagues, examined how implicit biases might negatively affect women in science, math, engineering, and technology fields, or STEM fields, for short.
They conducted a study where the participant was to hire someone to perform math-related tasks. They found that participants were twice as likely to hire a man as they were a woman. This pattern held regardless of the gender of the person doing the hiring.
The math performance of the potential employees varied. When this performance was shared with the people doing the hiring, the gender bias was reduced, but it still remained. Thus, even in cases when performance among women and men differed, people still preferred men.
Finally, the research team assessed the participants’ implicit biases against women in STEM fields. They found that it was these implicit biases that helped explain the preference for hiring men to complete the math-related tasks.
Collectively, the findings show that biases against women in STEM persist, that it impacts the hiring of women in STEM-related jobs, and that because of these biases, people are likely to hire people who might not be the best suited for the job.