Stop Trying to Suppress Your Bias in Hiring

Instead, acknowledge and be aware of your biases and the assumptions they can lead you to make.

You’ve probably been hearing a lot about implicit bias recently, especially if you’ve been to any one of our sessions. As there begins to be more work around increasing equity and diversity in the workplace, the conversation has (thankfully) shifted away from outdated concepts like quotas to more intentional practices like creating sustainable recruitment pipelines and more welcoming office spaces.

As such, implicit bias has become a hot topic as recruiters, HR professionals, and hiring managers look to expand their applicant pools and eventually take on more diverse talent.

So what is implicit bias, and why are people talking about it?

As the name implies, implicit bias is an unconscious attribution of factors or capabilities on an individual or group of people based on our own experiences or learned associations. For instance, some people may assume that Indian people are best-suited for careers in STEM or someone with an accent doesn’t speak English well.

Biases are our brain’s way of protecting us, by categorizing people into familiar boxes. From the examples I gave above, it’s easy to see why some folks might look at this concept and say “We need to remove as much bias as possible from our hiring decisions.”

Well, not quite.

While you don’t want to be hiring based on stereotypes, trying to erase bias from your decision-making would be like trying to stop your stomach growling when you’re hungry. When you simply try to suppress your bias, you run the risk of trying to rely solely on objective evaluation tools for your candidates instead of looking at your candidates as whole human beings with individual stories to tell. Worse yet, as I’ve seen with countless hiring committees, you can run into “analysis paralysis” as you keep trying to find ways to remove all bias from your process and end up not moving forward at all.

I’ve seen this first-hand. I was consulting with a hiring committee for an IT position, and they came across a colleague of theirs within the stack of application packages. Since they wanted to make sure that they didn’t give anyone what could possibly be perceived as preferential treatment, they ended up judging that application package more harshly than others, even though this colleague was more than qualified for the position. This committee ended up failing the search because, even though this applicant performed well, they were scared of any notion of perceived bias in the selection process. That colleague ended up taking a position elsewhere.

This isn’t an argument against using tools like evaluation criteria for resumes, or work tests for applicants – when done right, those are great ways to build a common baseline and language among your hiring committee to make sure that you’re looking at all of the candidates on a level playing field.

A more promising practice would be to learn what your biases are, why they come up, whether it’s useful for the situation at hand, and work with others to make your decision-making as inclusive as possible.

You can start by asking yourself – why does this candidate’s resume appeal to me? What about that answer did I like? Why did I like it? Is it relevant to what the work this person is eventually going to be doing?

Once you have answers to those questions, you bring them up with your hiring team. Let them know where you’re coming from and what informed your decision-making.

Then, you listen. Ask them how they feel, and what’s being informed by their biases. Ask follow up questions, and whether what they’re favoring (or not favoring) is directly linked to the job at hand. By having these brave and important conversations, you’re not only laying the foundation for a more equitable and inclusive hiring process but also setting the tone for the type of organizational culture that people want to be a part of.

Thank you to Step Up facilitator Gautam Jayanthi for this Real Stories guest blog.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.