Intrinsic Biases to Be Aware of When Interviewing

Introduction
Even the best interviewers can fall into patterns of unconscious bias — assumptions and judgments formed automatically and unintentionally. Recognizing and managing these biases is essential for fair, effective hiring decisions that focus on skill, fit, and performance potential rather than instinct or familiarity.

Affinity Bias (a.k.a. “Like-Me” Bias)
You naturally feel more comfortable with candidates who remind you of yourself — similar backgrounds, hobbies, education, or even sense of humor.

Watch out for: Favoring someone because they “feel like a cultural fit” when what you mean is “they’re like me.”
Tip: Evaluate candidates based on job-relevant behaviors and competencies only.

Confirmation Bias
You form an impression early (from their résumé, appearance, or first 30 seconds of conversation) and then subconsciously look for evidence that supports that first impression.

Watch out for: Ignoring data that contradicts your initial opinion.
Tip: Ask consistent questions across candidates and take structured notes to keep evidence objective.

Halo Effect
One impressive trait (e.g., great eye contact, prestigious employer, confident demeanor) overshadows other areas that deserve scrutiny.

Watch out for: Letting one strong quality convince you the person is strong overall.
Tip: Evaluate each competency individually — don’t let one “wow” moment skew the rest.

Horn Effect
The opposite of the halo effect — one negative factor (e.g., nervousness, odd outfit, weak handshake) unfairly colors the rest of the evaluation.

Watch out for: Letting one small misstep overshadow true ability.
Tip: Separate nerves or style from skill and substance. 

Attribution Bias
You attribute your own successes to skill but others’ successes to luck — or their mistakes to personality rather than circumstance.

Watch out for: Assuming a candidate’s gap or setback defines their work ethic.
Tip: Probe for context — ask why and how instead of jumping to conclusions.

Gender Bias
Assuming gender-linked traits (e.g., men are more assertive leaders, women are more empathetic communicators).

Watch out for: Letting gender-coded assumptions affect your perception of leadership, collaboration, or technical ability.
Tip: Evaluate what they did, not how you expect them to behave.

Racial or Ethnic Bias
Forming assumptions based on someone’s name, accent, appearance, or cultural background.

Watch out for: Misjudging communication style or professionalism through a cultural lens.
Tip: Focus on substance and skill — not familiarity or comfort.

Age Bias
Younger candidates may be seen as inexperienced; older candidates as “stuck in their ways.”

Watch out for: Subtle age-based assumptions about adaptability or ambition.
Tip: Ask about relevant skills and examples of continuous learning or growth instead.

Appearance Bias
Making assumptions based on attire, attractiveness, or grooming.

Watch out for: Equating “polished” with “competent.”
Tip: Stick to professional capability — not presentation.

Anchoring Bias
The first piece of information you hear (e.g., last salary, school name, first answer) sets the tone for everything that follows.

Watch out for: Overweighting early impressions or first data points.
Tip: Review the entire interview before making your judgment.

Nonverbal Bias
Over-interpreting body language, tone, or eye contact — often influenced by culture, neurodiversity, or nerves.

Watch out for: Mislabeling a calm or introverted candidate as disengaged.
Tip: Evaluate content of answers more than delivery style.

Contrast Effect
You unconsciously compare one candidate to the previous one rather than to the job criteria.

Watch out for: Letting a “star” or “weak” candidate skew your perception of the next.
Tip: Reset mentally between interviews and use consistent scorecards.

Closing Thought
Hiring decisions shape culture, performance, and reputation. The goal isn’t to eliminate bias — it’s to manage it. Structured interviews, consistent scoring rubrics, and collaborative debriefs are the best tools to keep decisions fair, data-driven, and legally defensible.