Gender Equity Matters (GEM)
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Unconscious bias

Unconscious bias

Unconscious bias is one of the most damaging problems a workplace can face. It is also one of the most difficult things to identify and recognize.

We are all biased, whether we know and acknowledge it or not. It is part of being human.

Our brain receives 11 million bits of information per second every day, but only has the capacity to process 40 bits per second of that information. This means that 99% of our sensory input is processed unconsciously. This is what makes us functional, but sadly, this lack of awareness also means that we don’t realize that we are biased.

We’re all biased. Our experiences shape who we are, and our gender, race, ethnicity, sexual orientation, place of birth, and other factors impact the lens with which we view the world.

As I mentioned, the hardest part of addressing unconscious bias is that it is unconscious. Most of the time, we don’t even realize that we are biased.

What can we do?

Understanding that biases exist and learning about the different types of biases is the first step in our journey.

Below are the most common types of biases:

  • Affinity bias: tendency to favor people with whom we share characteristics, experiences, backgrounds, interests, and associations.
  • Confirmation bias: tendency to disregard or discount evidence that contradicts our existing viewpoints.
    Anchor bias (or “The Halo Effect”): tendency to think everything about a person is good because our first impression of them was good.
  • Perception bias: tendency to form stereotypes and assumptions about certain groups that makes it difficult for us to make an objective judgment about individual members of that group. A few examples include assumptions about gender, race, religion, sexual orientation, and country of origin

Awareness is the first step. The next step is to ensure that these biases don’t affect the decision-making processes in your organization. This can be achieved by using standardised tools and practices to check for your biases and ensure that the decisions being made use pre-set universal criterion.

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