Everyone is biased. We all have our own preconceptions and prejudices, and we all make assumptions about other people - often without even realising we're doing so.
This is all part of being human, and it's not a problem as long as you don't allow your biases to affect the decisions you make. Unfortunately, there are still a lot of powerful decision-makers in the world who (consciously or otherwise) make choices largely based on stereotypes and their own flawed preconceptions.
This is a particularly contentious issue in the world of recruitment. While the recruitment industry has made great progress on this front in recent years, unconscious bias is still rife; you don't have to look very hard to find stories of, for example, women who struggled to find employment until they switched to more gender-neutral names, or people of Middle Eastern and African heritage who were able to improve their job application success rate by assuming white British identities.
This happens not because UK employers are unabashedly sexist or racist, but because one's unconscious prejudices sometimes limit one's ability to make an impartial decision. However, there are ways to avoid unconscious bias in recruitment, and that's what we're going to look at today.
What is unconscious bias?
Unconscious biases are assumptions you make about people without realising it (that is, unconsciously) and without any evidence to support those assumptions.
In recruitment, unconscious bias is a problem because it can lead employers to make irrational hiring decisions that are based on stereotypes or personal preconceptions rather than on what the candidate actually brings to the table.
Most conversations about unconscious bias in recruitment revolve around racism, sexism and so on - and as we've already mentioned, it is certainly true that women and minorities sometimes find it harder to get hired as a result of unconscious bias. But unconscious bias is much broader than that (technically including any judgement you make subconsciously and without strong evidence), and false assumptions can be positive as well as negative.