Human beings are not impartial judges of any situation. When doctors triage patients, judges sentence defendants, teachers grade students, or voters choose candidates, all are subject to their underlying cognitive biases. In fact, the current crisis has served as a reminder that the presence of bias is a given anytime ordinary people are being put in positions to make determinations about others.
Consider this question: why were minority communities in the U.S. being disproportionately devastated by COVID-19, particularly at the beginning of the crisis? According to most media coverage, the answer lies in the macro-level picture: higher participation in at-risk occupations, multi-generation living situations, and lack of access to quality nutrition.
Complex socioeconomic interactions are certainly a significant part of this tragic trend, but the macro-level analyses miss an important piece of the story: early on in the pandemic, when black patients showed up to emergency rooms, they were referred for COVID-19 testing at lower rates than white patients. The reason for this unfortunate disparity is not complicated: despite the best intentions of those on the front lines, doctors and nurses are biased.
In pointing out the differences in how black and white patients have been evaluated for COVID-19, the goal is not to criticize medical personnel for being inconsistent. On the contrary, cognitive biases are irrevocable features of the human brain that enable all people to quickly interpret circumstances and make decisions. But while these mental shortcuts are essential, the simplified judgements we make about others are not always accurate or fair. In these cases, it is critical to acknowledge the presence of human prejudices so that constructive action can be taken to reduce their influence. For example, black women in the U.S. are several times more likely to die during childbirth than white women, in part due to the less attentive care they receive from medical personnel. To help address this disparity, California recently passed legislation that adds implicit bias training to continuing education requirements for doctors and nurses.
Strategies for mitigating bias can vary across situations, but the first step an organization must take to work toward equity is to accept that these prejudices exist. In the context of talent selection, an employer struggling with improving its workforce diversity could likely point to a variety of external factors to credibly explain the situation. It is true, for example, that racial disparities in education yield fewer minority candidates with the qualifications to work in the tech sector. But like the media coverage of COVID-19, macro-level trends miss an important part of the inequality story. Countless studies have clearly proven that people are not capable of reading resumes with an objective eye, and even when recruiters might have the best of intentions, the result is the unfair treatment of minority candidates.
So, pymetrics invites employers to consider another question: why are minority communities underrepresented in your workforce? In our experience, when an organization is willing to acknowledge the shortcomings of their human evaluations, modern technology can enable a more equitable solution. We welcome you to reach out to us here to learn more.