This article was originally written as a response to this post...
As someone who’s hired A LOT of people in the past, this is definitely a topic that comes top of mind. Here are some comments:
How do you account for and address unconscious or prevent conscious biases?
Often ‘best candidate for the job’ ends up being ‘someone who looks similar to others who do the job now’ - which ends up being similar schooling, background, and unfortunately gender, race, etc. When I took Engineering at school there were only 3-5 women in my classes, so selecting for background ends up with a very biased sample set on one criteria.
I look back now and early in my career as a hiring manager my teams looked a lot like me - male, white, 25-35, etc. I can’t honestly say whether I had unconscious biases playing - we had very few female applicants, non-white applicants. Biases could have been exaggerated because other team members also got involved in hiring, which means a single member’s bias could have influenced decision making.
Later, my teams were more diverse - partly because I was hiring in more diverse job roles and so ended up with a more diverse set of candidates. But maybe because I tried to think about my unconscious biases. I honestly don’t know. It’s something I struggle with.
How do you account for the value of diversity on a team?
When hiring for a specific role, we like to use the word ‘meritocracy’ or ‘superior ability to do the job’ - but in reality nobody exists in a vacuum. Diversity in perspective, background and skill on a team has a value independent of the necessities of the specific role. If you aren’t accounting for that, and hiring with a myopic view of just the specific role, often you can be cutting yourself off of critical benefits from broader perspectives. It requires thought, but it is thought worth undertaking.
A great example here is Tristan Walker’s perspective and starting his company based on the Bevel Razor. If everyone has the same background then everyone's working from within the same box - same perspective, set of tools. I often refer to the 'echo chamber' that inevitably builds inside any organization - it's why you need to reach outside, bring in fresh blood, ideas, diverse opinions. Hiring is one way to do that which is more persistent, culturally.
How do you know you’re not measuring ‘superior ability to do the job’ based on an unequal metric?
Just because someone has achieved certain outcomes in the past, doesn’t mean they have more or less ability - it could mean they had an unfair handicap.
How often do you handicap a candidate because of written language skills, verbal communication skills? Does this become a heavier weighting than it should, leading towards structural biases? What about the woman who has taken maternity leave for a couple of years - do you hold the 2-3 years less experience against her compared to another candidate?
These choices and biases aren’t always obvious, but often I find that we tend to fall back on language like ‘meritocracy’ and ‘superior ability to do the job’ without really understanding the whole picture of what that means, how we measure it, and if we’ve truly accounted for personal and structural biases.
Hiring the best candidates - value diversity, offset biases, deal with structural issues.
To close, here are some ideas to help reduce biases in hiring.
1. Remove names, gender references, possibly even specific higher educational institutions from resumes before sending them on to HR or hiring managers for screening.
2. Consider your screening requirements and consider whether they have inherent biases. 'Years of experience' translates to ageist screening. Written/spoken language skills will screen out candidates from other language backgrounds.
3. Watch for 'culture fit'. Culture fit can be a bundle of biases that will screen out diversity simply because it can be inflexible to different people's working needs, backgrounds, desire to party (or not).
4. Check out the structural biases within your organization. Your HR policies are probably geared towards people of specific ages, demographics, work styles or genders. Examples - you might offer extended benefits - great for families, less interesting to young single people. Parental top-up for women but not men sends a message about who should be taking parental leave and creates all sorts of downstream structural biases. So - consider how your HR policies, benefits packages, vacation, bonus pay, stock options, leave policies, etc - how all these attract or push away candidates of different backgrounds.