Remove Bias Out of Job Interviews

Everyone is naturally biased, but when hiring and promoting people, we want to avoid our bias to eliminate discriminatory actions. In 2016, an article from the Harvard Business Review reported the following:

“When sociologist Lauren Rivera interviewed bankers, lawyers, and consultants, they reported that they commonly looked for someone like themselves in interviews. Replicating ourselves in hiring contributes to the prevalent gender segregation of jobs, with, for example, male bankers hiring more male bankers and female teachers hiring more female teachers.”

What can we do to make sure we hire a diverse team and avoid being bias during the recruitment and interviewing phase? One way to avoid this is to make sure you offer interviews to candidates based on merits and nothing else. A good start is to expand your personal network to increase the candidate pipeline with more women, people of color, and other underrepresented minorities. With a wider and more diverse pipeline, you can then focus on selecting people based on merits and nothing else.

Be blind

We need to be blind to information such as names, age, gender, or any other information that isn’t experience or skills. Companies like Applied, Blendoor, Edge, GapJumpers, Interviewing.io, Paradigm, and Talent Sonar offer services to help you remove this information from applicant tracking systems to avoid any sort of bias. These services these companies offer can be integrated with existing candidate tracking applications to remove information that can cause discriminatory actions.

Structured interviews

Being blind to some of the candidate’s information is a good start, but it isn’t the final solution. After the initial process of qualifying candidates based on merit, you’ll want to interview the candidates in person, phone, or a video call. In order to do this and remove any bias, you should have a well-defined and structured interview process. Make sure you ask all candidates the same questions, and in the same order, and encourage the interviewers to rate each answer as soon as the candidate answers the question. Standardizing this process will allow for clear comparisons between all candidates and leave very little room for bias.

Avoid group interviews

Another thing to consider is avoiding panel or group interviews altogether. For once, it is difficult to diversify the interview panel and there isn’t any data that proves that a panel or group interviews result in better hires. People interviewing candidates should be independent of each other to get the benefit of a personal and unique perspective about a candidate. After interviewing a candidate, submit their assessment before meeting with others to discuss the applicant. Individual interviews will allow you to collect multiple data points and different perspectives instead of one data point from a group of interviewers.

Work-sample exercises instead of resumes

Resumes are really not a good resource to determine if a person has the skills and experience for a job. Work-sample exercises require applicants to perform tasks or work activities that mirror the tasks employees perform on the job. Prepare work-sample exercises that candidates can use to demonstrate their know-how. To make these work-sample exercises and its results unbiased, do not include the name, gender, age, race, or any other unneeded information about the candidate.

The above suggestions can help eliminate some of the biases, but it will not stop all of our shortcomings. This isn’t perfect but it is a good start to help reduce our biases which can then lead to discriminatory actions.

Want to learn more and participate in our Diversity in Tech Meetup? Please join our meetup and attend an event if you are in Austin, TX.

Image credit: Gary Waters/Ikon Images/Getty Images

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