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Challenging our Biases

Our brains rely on mental shortcuts to process the overwhelming amount of information we encounter daily. While helpful, these shortcuts can lead to biases—unconscious preferences or judgments that are often unfair and not based on objective reasoning. Everyone has biases, but they can result in mistakes in reasoning, evaluation, and decision-making.

In the hiring process, biases can lead to discriminatory practices. As a result, we have a legal and ethical responsibility to identify and control for biases when evaluating candidates. Here are some common types of biases to watch for:

Cloning (Affinity Bias)
  • Unconsciously favouring people with similar attributes or backgrounds as ourselves.
  • Undervaluing unfamiliar approaches or experiences.
  • Expecting candidates to resemble the person being replaced.
Snap Judgements
  • Making judgments about a candidate without sufficient evidence.
  • Dismissing a candidate for minor reasons.
“Good Fit” Bias
  • Defining “fit” based on personal comfort or cultural familiarity, which can hinder diversity.

  • Prioritizing familiarity over the ability to meet the role’s needs.

Negative Stereotypes
  • Assuming incompetence in historically underrepresented groups (e.g., women, Indigenous people, Black people, people of color, 2SLGBTQ individuals, people with disabilities, older employees, newcomers).

  • Requiring individuals from these groups to repeatedly prove their competence.

Positive Stereotypes
  • Assuming competence or overlooking flaws in candidates from dominant groups (e.g., white, wealthy, male, highly credentialed).

Prescriptive Stereotypes
  • Expecting different workplace behaviour based on social identities. For example:
    • women are often expected to be mild-mannered team players, but this may be optional for men.
    • assertive and direct behaviour may be seen favourable for some groups and interpreted as difficult, abrasive, or tactless behaviour for other groups.
    • 2SLGBTQ employees may be stereotyped as too masculine or too feminine, which is irrelevant to the ability to do a job.
Elitist Thinking
  • Favouring candidates from elite schools

  • Favouring candidates with credentials from North America or Western Europe.

  • Downgrading candidates based on appearance or mannerisms.

Horns and Halos
  • Allowing one weakness to unfairly influence an overall negative evaluation (horns).

  • Allowing one strength to unfairly influence an overall positive evaluation (halos).

Before starting the interview process, take time to reflect on these biases. If you notice a bias in your thinking, ask yourself:

  • Where did this thought come from?
  • Is it fair?
  • What impact could acting on this bias have?

Through ongoing learning, reflection, and intentional action, we can challenge these biases and create a more equitable hiring process.

References:

Center for WorkLife Law (2021). “Bias Interrupters for Hiring & Recruiting.” Retrieved from https://biasinterrupters.org/wp-content/uploads/2022/12/identifying-bias-in-hiring-guide-no-citations.pdf

University of Waterloo Office of Equity, Diversity, Inclusion and Anti-Racism (2020). “Implicit Bias Pre-Reading.” Retrieved from https://uwaterloo.ca/equity-diversity-inclusion-anti-racism/sites/default/files/uploads/documents/implicit-bias-pre-reading-1.pdf

Cognitive Bias Codex

The Cognitive Bias Codex by John Manoogian III is an interactive tool for researching the cognitive biases listed in Wikipedia. Click the image to view a larger format and click the individual items to visit the corresponding Wikiepdia article.

Wikipedia’s list of 188 cognitive biases, grouped into categories and rendered by John Manoogian III (jm3) as a radial dendrogram (circle diagram). Category model by Buster Benson, biases linked to corresponding Wikipedia articles by TilmannR. The source below can be used to create translated or updated versions of this file.

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Equitable Faculty Hiring at Vancouver Community College Copyright © 2025 by Shantel Ivits is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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