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Unconscious (or implicit) biases are extremely common. Data from Harvard University’s online Implicit Association Test (IAT) reveal that about 75% of white and Asian respondents displayed an unconscious bias for whites compared to Black and other candidates with darker skin tones. When those biases affect your company’s hiring processes, your commitment to putting workforce diversity principles into practice is thwarted.
To stop unconscious biases in hiring, adopt a strategic mix of technology and practical process changes. The result is a more equitable process and a stronger, more diverse workforce.
Essentially, an unconscious bias is a prejudice of which the individual is wholly unaware. That bias can be based on one or more of a number of demographic and psychological factors, such as perceived race or ethnic background, gender, age, or neuroatypicality. What’s more, a bias may be wholly at odds with our sincerely-held values and principles.
Evidence of unconscious or implicit biases shows up everywhere. Do a quick Google image search for “CEO”. Most of the page will be pictures of various white men. Type “CEO” into the emoji search bar on your phone and if you’re like most people, a male emoji shows up first.
To achieve full buy-in, use relevant data on diversity in hiring to prove the advantages. Many studies prove those advantages can be measured in dollars and cents, in addition to the beneficial impact on the existing workforce:
When you can objectively measure your progress towards specific corporate goals, you stand a much greater chance of actually meeting those goals. Measurable goals help keep business teams on track in all areas of operations and administration, including HR.
Good diversity goals for hiring processes should be capable of assessment in quantifiable ways. For example, aim for a specific percentage of members of historically marginalized populations in the total pool of applicants invited to proceed to the interview phase for a specific position that has traditionally been held by advantaged groups or genders.
Specific words may create a gendered perception in context. Individuals tend to perceive certain adjectives as typically masculine traits (“competitive,” “direct”) while others are deemed more feminine (“collaborative,” “cooperative”). Using those terms may mean applicants self-sort by gender at the outset.
Software can help counter this. For instance, the Censia Talent Intelligence Data Platform (TI) utilizes “Fairness Aware Machine Learning” to help recruiters and HR teams transcend human limitations. By anonymizing potential candidates to help eliminate both unconscious and conscious hiring biases, TI helps you build a more qualified and diverse workforce.
Two major bottlenecks to creating a more diverse workforce are resume review and interview performance analysis. To correct for that influence, you can eliminate demographic factors and focus strictly on actual qualifications during the resume review process.
Software can help anonymize resumes so that you can be assured you’re considering only the record in front of you and not, for instance, whether or not a particular name “sounds” like it belongs to a privileged ethnic background. For example, Censia’s Instant Applicant Ranking function can objectively assess and rank all the candidates in your Applicant Tracking System.
Too often, interviewers “get creative” during the actual interview. This habit can lead to unfair and biased questioning, which often results in candidates being taken aback and feeling uncertain as to the proper response.
Instead, create a standardized list of interview questions and use it in every interview for that specific position. By asking every applicant the same questions, you can focus on the candidate’s qualifications and responses in a fairer, more equitable way.
If you can’t really articulate a rationale for disfavoring one candidate over others, it’s quite possible that an implicit bias is at work. When an unconscious bias contaminates a hiring decision, often the only rationale the decision-maker can offer is “I just have a gut feeling about this person.”
To ensure that a hiring decision is as free from bias as possible, insist on the use of quantifiable metrics and scores based on articulated qualifications that are relevant to the position.