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Mitigating the Impact of Implicit Bias in High-Stakes Settings


Mitigating the Impact of Implicit Bias in High-Stakes Settings


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Feb 15, 2017 | by Mike Heil


Police shootings of unarmed African Americans, talk of a proposed ban on Muslim immigration, significant under-representation of women in science, technology, engineering, and math (STEM) professions—the dream of a post-racial, post-sexist society remains elusive. Although laws, guidelines, and regulations such as the Civil Rights Act of 1964 and the Uniform Guidelines on Employee Selection Procedures offer protection from explicit discrimination, bias remains pervasive. Rather than being overt, discrimination now tends to occur through implicit bias, which is an unconscious and automatic prejudiced judgment that influences behavior.

Our perceptions of people, which are not always positive, impact how we behave toward them. What choices will we make if we have a negative opinion of someone? Are we likely to be fair to them if we see them as somehow “less than”? Now, consider how we will behave if we do not realize that our biased attitudes even exist.  How will we treat Muslims if we believe they are terrorists? African-Americans if we believe they are criminals? Mexicans if we believe they are drug dealers? Women if we believe they are inferior to men? These biases are likely to affect both personnel decisions (e.g. whom to hire, train, and promote) and professional decisions (e.g. who gets attention in the classroom, who receives medical treatment, and who is arrested or shot). The confounding nature of implicit attitudes is that we hold them, yet are unaware of them and of their effects on our behavioral choices. Thus, a better understanding of the role of implicit bias and strategies for mitigation not only allows for fair treatment in the workplace, but can literally have life or death consequences. 

A large amount of human reactions are triggered automatically and outside of our awareness1. These reactions constitute our implicit attitudes, which differ from self-reported, explicit attitudes, and may be more predictive of behavior in certain situations2. Research shows that relying solely on explicit attitudes when trying to understand human reactions and behaviors is insufficient. To fully understand human interactions and behaviors, we must consider not just the characteristics of the situation, but also peoples’ motivations, which include their implicit attitudes and their efforts to conceal their biases. In actuality, people may react to others in ways of which they are not consciously aware. In some circumstances, this could mean that split-second decisions are based on implicit attitudes and are not influenced by more controlled explicit attitudes. Thus, a person could appear to be a threat or unqualified because of implicit attitudes triggered by surface diversity traits, and not due to actual intentions or qualifications. In addition to these more overt reactions, implicit attitudes can also result in subtle forms of discrimination, which are significantly detrimental.

Racial disparity throughout the criminal justice system is reflected by disproportionally more searches, arrests, and incarcerations of African Americans3. Bias in law enforcement subjects racial and ethnic minorities to higher levels of suspicion, surveillance, and intrusion3. Regardless of the extent to which prejudice or discrimination actually exists within law enforcement, shootings of unarmed African Americans contributes to a perception that police officers are racially biased, which undermines public trust and relations3. These perceptions are very likely to impact how people, particularly racial minorities, interact with law enforcement officers. As more examples of bias in law enforcement make the news, more people are likely to take them as evidence of actual discrimination against minorities4.

Research that examined religious discrimination in employment settings found examples of implicit bias. The results of a study in which people dressed in either Muslim-identified or nonreligious attire applied for retail jobs concluded that Muslims may face challenges to employment that reflect a lack of acceptance of their religious identity5. For example, Muslim applicants were unfavorably judged in salary assignment and job-related characteristics in the presence of negative information. Research has also noted that Muslim women perceive this stereotype threat to be based on their religious expression, and that Muslim women are less likely to expect offers of employment or even feel that certain high-status careers are within reach6.

Women remain severely underrepresented in STEM jobs. While making up nearly half of the workforce in the U.S., they comprise just 25% of the STEM workforce7. Similarly, women graduating with STEM degrees are more likely to go to work in healthcare or education than men with the same degrees. Two common explanations are: 1) there are fewer women who are interested in STEM subjects and 2) women are pursuing other careers so that they have better work-life balance8. However, some researchers have found that, even when math skills were identical, both men and women were twice as likely to hire a man for a job that required math9. Another possible explanation for underrepresentation is that implicit gender stereotypes disincline young women from pursuing STEM fields.  

A panel of experts will address these issues at the Society for Industrial and Organizational Psychology conference in Orlando, FL. The purpose of this panel discussion is to raise consciousness about implicit bias and its impact both in the workplace and society, as well as the responsibilities I-O Psychologists have to contribute to the solution and mitigate their consequences. Although there is evidence that bias exists across a broad spectrum of high-stakes settings, this session will focus on implicit bias in law enforcement, against women in STEM occupations, and against Muslims in the workplace.





References

1. Dijksterhuis, A., & Bargh, J. A. (2001). The perception-behavior expressway: Automatic effects of social perception on social behavior. Advances in experimental social psychology, 33, 1-40.
2. Ziegert, J. C., & Hanges, P. J. (2005). Employment discrimination: The role of implicit attitudes, motivation, and a climate for racial bias. Journal of Applied Psychology, 90(3), 553.
3. Kahn, K. B., & Martin, K. D. (2016). Policing and race: Disparate treatment, perceptions, and policy responses. Social Issues and Policy Review, 10(1), 82-121.
4. Spencer, K. B., Charbonneau, A. K., & Glaser, J. (2016). Implicit bias and policing. Social and Personality Psychology Compass, 10(1), 50-63.
5. King, E. B., & Ahmad, A. S. (2010). An experimental field study of interpersonal discrimination toward Muslim job applicants. Personnel Psychology, 63(4), 881-906.
6. Ghumman, S., & Jackson, L. (2010). The downside of religious attire: The Muslim headscarf and expectations of obtaining employment. Journal of organizational behavior, 31(1), 4-23.
7. Beede, D. N., Julian, T. A., Langdon, D., McKittrick, G., Khan, B., & Doms, M. E. (2011). Women in STEM: A gender gap to innovation. Economics and Statistics Administration Issue Brief (Issue Brief No. 04-11).
8. Williams, J.C., Phillips, K.W., & Hall, E.V. (2014) Tools for Change; Boosting the Retention of Women in the STEM Pipeline. Retrieved from
www.worklifelaw.org.
9. Reuben, E., Sapienza, P., & Zingales, L. (2014). How stereotypes impair women’s careers in science. Proceedings of the National Academy of Sciences of the United States, 111(12), 4403-4408.

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