Gem Care Advisor

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Reduce bias

5 Ways You Can Reduce Bias in Your Hiring Process

It’s likely most hiring teams don’t set out to discriminate when searching for candidates, but hiring bias occurs all the same. In most cases, unconscious bias is the culprit, causing judgment based on discriminatory factors including gender, appearance, race, and educational background.

Even though they aren’t aware it’s happening, those in charge of hiring are evaluating candidates through these lenses. To fight against this, try these five suggestions for reducing bias in the hiring process.

1. Start with the language in your job description

You can unintentionally exclude someone in the words you use to describe the position. This can come from using generally accepted colloquial terms that represent a group of people, but seemingly excludes others. Particularly, avoid gendered pronouns of any variety.

2. Consider pre-screening with AI

Research shows that bias can occur simply by reading a name, so using artificial intelligence, or AI, to pre-screen your candidates can collect the most relevant applicants in relation to their abilities, not how their name looks or sounds. There are a number of ways you can implement AI to keep human perceptions out of the equation.

3. Improve the interview structure

How and what questions you ask can make a big difference when it comes to bias. The goal is to ask the same series of questions of all the candidates but leave room for unstructured conversation. You don’t want the whole interview to be open, because then you could let your personal feelings get in the way of qualifications.

4. Hold multiple interviews with different interviewers

Bias can slip in easier when you limit the interview process to one person. It’s essential to have different people interview the same candidate so independent opinions can be formed, giving the candidate a more fair and unbiased chance.

5. Implement skills assessments

Another way to eliminate unconscious bias is to test your applicants to determine their skill level. This way, you have data to indicate top candidates instead of your own opinions.

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