Biases are like mirrors, showing us a reflection of our true feelings and affecting how we think, act, and make decisions. Interview biases are the same way, they reflect our own personal perspectives back at us, rather than accurately reflecting the candidate. Since the interview process is in effect a quantitative research process, biases not only distort the data collection but also compromise the validity of the research. In this article, we're going to cover how to detect interviewer biases, talk about some interviewer bias examples, and how they affect the questions asked in interviews. Before we get started, let's define "interview bias."

What are Interview Biases?

"Interview biases" is a term used to refer to the tendencies an interviewer may have to form judgments, or opinions based on their own personal experiences, beliefs, or stereotypes. These "preconceived notions," may be conscious or unconscious (meaning they can show up unintentionally). "Interview bias," meaning anything that clouds an accurate perspective of the candidate skews the validity of the interview.

There are several ways interview biases show up in interviews. These are the most common:

1. Confirmation Bias: This occurs when an interviewer forms a first impression about a candidate and seeks out information that confirms that impression while ignoring contradictory evidence.
2. Halo Effect: This bias happens when an interviewer allows one positive aspect of the candidate's character or resume to influence their overall opinion of the candidate.
3. Horn Effect: Conversely, the Horn Effect occurs when an interviewer allows a single negative trait or experience of a candidate to cloud their overall judgment.
4. Similarity Bias: Interviewers may favor candidates who share similar interests, backgrounds, or characteristics with them, leading to a skewed evaluation.
5. Stereotyping: Making assumptions about a candidate's abilities, personality, or work ethic based on their gender, ethnicity, age, or appearance.
6. Recency Bias: Giving more weight to the candidate’s most recent behavior or performance and overlooking the comprehensive history of the candidate's skills and accomplishments.

Being mindful of these biases will help you ensure they don't creep into your interviews (something we're going to talk about in the next sections). However, creating a fair and equitable interview process requires more than just recognizing how they show up. It also takes proactive measures to reduce and eliminate them as much as possible.

In many cases, interviewer biases are not about overt prejudice, in fact, the opposite is actually true. Most often unconscious biases sneak in through two primary culprits: Recency bias, and similarity bias.

Similarity Bias Example: 

Imagine how easy it would be for an interviewer who's proud to have graduated from a great school to notice that the candidate graduated from the same university and give them preferential treatment throughout the interview process. This is a perfect example of confirmation bias. In this case, shared alma mater experiences could dominate the interview, shifting focus from specific skills to traits valued by the company and overlooking areas where the candidate lacks the experience or skills necessary for the role.

Recency Bias Example:

Imagine interviewing a candidate as they close a landmark project. Maybe it was closing the biggest sale in company history, maybe it was getting a new launch "off the ground," or a new product running successfully. Impressed by this recent success, the interviewer places too much focus on the latest win and overlooks a candidate's overall performance and career accomplishments. This will lead to an imbalanced view of the candidate's ability to perform the day-to-day tasks of the role.

Promoting diversity on your team starts with recognizing and addressing these biases. If you'd like to see how interview intelligence can help you recognize when these biases appear and coach your team to eliminate them, click here to learn more.

Biased Interview Questions Examples

Before we get into some biased interview questions examples, let's talk about how the interview generally gets "off track." As we mentioned earlier, it's getting far rarer to see biases like racism and ageism just show up overtly in an interview. As a culture, we've done a great job at fighting for people's right to work and create a great life if we choose (not that we can't do more, and there's still work to be done), but in many studies listed in the National Library of Medicine, we're seeing career based racial discrimination numbers fall dramatically as people are becoming aware of their biases.

To go back to a previous example, the interview often gets "off-track" when an interviewer naturally gravitates towards a candidate who graduated from the same university as them (exemplifying the Similarity Bias)- If a candidate stumbles in their first answer, and the interviewer lets this moment disproportionately define their opinion of the candidate's abilities (demonstrating the Horn Effect)- If a candidate showcases an impressive project right off the bat, and the interviewer overlooks other potential red flags as a result (falling into the trap of the Halo Effect). These common interview biases didn't show up prejudicially they happened because of a lack of awareness and preparation.

So how do we keep these types of bias in interviews "at bay?" Create a structured interview process with objective interview questions.

Structured Interview Process: Example

To illustrate, let's say you're interviewing candidates for a project management (PM) position. Instead of opening with a general query like "Tell me about yourself," which might inadvertently steer the conversation towards common ground and trigger similarity bias, initiate with a structured question that levels the playing field. For instance:

"Describe a situation where a project you were managing was off-schedule. How did you identify the issues causing the delay, and what steps did you take to get the project back on track?"

This question is specifically designed to focus on the candidate's problem-solving and project-management skills. Questions like this narrow the conversation to relevant experiences and competencies required for the position and force you and your team to consider each candidate based on their responses to similarly posed questions, thereby promoting a fairer and more equal assessment process.

Biased interview question examples include:

• "What year did you graduate from college?" (Age Bias)
• "How do you handle stress in a fast-paced environment?" (Stereotyping based on perceived gender or age differences)
• "Why do you think you'd be a good fit for our company culture?" (Confirmation Bias based on shared interests or backgrounds)

Avoiding questions like these that focus on religion, age, race, gender, family status, and other protected characteristics can help create a more fair and equitable interview process. Instead, focus on asking questions that directly relate to the skills and abilities required for the role.

In closing this section, I want to address what's become a cultural norm for most people. Asking "filler" questions. Filler questions are the natural conversation bits we use to fill the silence, but when used in an interview setting can lead to unintentional bias. Examples of filler questions include:

• "I see a ring on your finger, when are you getting married?" (Marital status bias)

• "Do you have young children?" (Family status bias)

• "Where are you from?" (Geographical or cultural background bias)

These questions are better left for fun team activities and happy hours once the candidate has been hired and settled into their role. As interviewers, we must be aware of the words we use and understand how they could potentially affect our evaluation of a candidate.

Detecting Interview Biases

Finally, let's talk about detecting interview biases so we can be on guard against them. I find that the easiest way to do this is to start at the end. My goal is to hire the best person for the role, and the interview is a data collection process that allows me to quantify who that is - meaning, if I bring biases into the interview, I skew the data which throws off the quality of hires. To put it another way, if I'm evaluating candidates based on factors that have nothing to do with the job requirements, I am not hiring objectively.

So how can we identify and avoid interview biases effectively in the interviewing process? Here are some strategies and techniques:

1. Be aware of your biases: The first step in identifying and avoiding interview biases is to be aware of our own biases. This requires taking assessments like Harvard's FREE test created in collaboration with Project Implicit to uncover any implicit biases we may hold.
2. Use a structured interview process: As discussed earlier, using a structured interview process with objective questions can help minimize the influence of bias in the interviewing process. This ensures that all candidates are evaluated on the same criteria and avoids potential favoritism based on similarities or superficial factors.
3. Have multiple interviewers: Having multiple people involved in the interview process can provide diverse perspectives and help catch any potential biases that one individual may have overlooked. Multiple interviewers will also help you detect when interviewing biases show up in interviews.
4. Use standardized evaluation criteria: Similar to having a structured interview process, using standardized evaluation criteria can help remove subjectivity from the hiring decision. This could include specific scales or rubrics for evaluating each candidate's skills and qualifications.
5. Continuously reassess and reflect: It's important to continuously reassess our interviewing process and reflect on any biases that may have inadvertently slipped through. This can help us improve and grow as interviewers, ultimately leading to a fairer and more effective hiring process.

Remember to be aware that interview bias examples show up when we're least expecting it. Be on guard through intentionality and structure, and have the right tools and technology to help you mitigate and avoid biases in your hiring practices.

Pillar's interview intelligence software was built to help you eliminate bias and increase diversity through structured interviews. Our suite of AI-powered tools helps you assess a candidate's skills and find the best fit for your team. Book a demo to learn more.