I don't have any unconscious bias when it comes to hiring

I don't have any unconscious bias when it comes to hiring

It’s a commonly felt sentiment. I’m a good person. I’m not biased. But is it true?

Studies have shown that people hate to think of themselves as unfair or selfish. It comes down to what psychologists believe is our need to believe the world is fair - this is illustrated in this Guardian article about the Psychology of Victim Blaming. It is more comforting to believe that good will be rewarded and evil punished. That those who aren’t selected must deserve it, and those who do the selecting do so fairly.

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I absolutely hate to believe I have unconscious bias - that I favour hiring people with a similar background to me. I’d hate to think I judge someone who comes in with a long beard, a strong local accent or lots of tattoos. I am a manager and I hire a lot of individuals - my decisions have an impact.

I speak to many others in the same privileged position as I am - being a middle aged white male manager - who regularly hire, and so many of my peers believe in the main they take on the best person for the job.  

Yet the statistics are clear, in the UK workforce, study after study shows gender bias with respect to hiring. My colleague Ciara Gardiner references an article by Lyssa Test in a blog post she recently wrote. Test’s study shows if you are a diverse employee it is much more likely that your manager shares that diversity as well.

“34 percent of Asian employees, 25 percent of Hispanic employees, and 20 percent of black employees all have managers of the same ethnicity—far exceeding the national workforce averages… Even with fewer female managers, 51 percent of female employees report to women, while 79 percent of male employees report to men.”

So people tend to hire people who are more similar to them than are different, and there is a definite bias when it comes to jobs and gender. In my field of IT, there are well documented biases and a lack of females in technical and managerial roles.

As someone who cares about diversity, I was struck recently by how easy it is to be caught out by bias. Over a curry, I was telling a female friend of mine how I had run out of friends to watch Avengers Endgame with at the cinema. I wanted to go for a sixth time (yes, I’m a big fan!). It turns out she is a huge Marvel geek and we ended up having a long chat about it. Yet it didn't even occur to me that she could be such a massive fan too.

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So what does this all mean? If most people don’t like to believe they are biased, and people tend to hire people who are similar to them, we are in a situation where change is unlikely to happen until those in privileged groups like myself admit they could have unconscious bias and actively work to offset that bias. In IT that means middle aged male managers like myself admitting we may be biased against hiring females, as one example. It’s not we are bad people, it’s just we are humans and wish to believe we are good. And wanting to believe we are good, may be the very thing that is preventing us from addressing our unconscious bias.

So I want to turn the question over to you, how sure are you that you aren’t biased? (You can try this Harvard implicit bias quiz to test yourself.) Are you really 100% confident? Because if you aren’t, then you could be making less than optimal hiring decisions. 

Callum Akehurst-Ryan

Staff Quality Engineer - I talk about exploratory testing, agile testing, diversity and quality engineering

5 年

This is a great article. Unconscious bias is something that we have to observe for and recognise; the hardest one being selective attention, where we ignore statements that seem incongruous with our perception of a person’s ability and listen on what confirms our impression. In IT the structures in place for bias are very inbuilt from the ground up. Bias towards computers being a boys topic and an industry that focuses on being competitive and self-aggrandising (which are very male traits). A focus on hiring from certain schools or universities can also be a pitfall for bias.

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