10.3 Assessment Errors and Personal Bias

HR and hiring managers must minimize the potential for assessment errors and personal biases to influence their decision-making throughout the selection process. Implicit bias can play a role in deciding who to interview and who to hire. Special attention needs to be given to interviewing the candidates. One major downside of interviews is that they can be very subjective and fraught with conscious and unconscious biases. The interesting aspect of unconscious biases is that they are greatly reduced by raising awareness of their existence, as most people unintentionally make these errors. Awareness can help inform decision-makers on how to make successful hiring decisions. Thus, knowing they can exist and what form they take helps eliminate them from the hiring process. Research has shown that interviewer training is a very effective way to reduce bias (Posthuma et al., 2002).

Assessment errors occur when an interviewer’s evaluation is influenced by something other than the behavioural evidence provided by the candidate. Here is a list of common biases that can cloud an interviewer’s judgment.

Common Biases

Leniency and stringency. This is the general tendency to assess applicants consistently high (leniency effect) or low (stringency effect). Interviewers need to be aware that they might have a different understanding of the job requirements and the qualifications assessed, but they also need to be fair in assessing applicants. The result is that the interviewer consistently rates all applicants either higher or lower than warranted.

 

 

Central tendency. This tendency involves using only the middle points on the interview scoring guide while avoiding the extreme points. Interviewers may be reluctant to rate applicants high or low; therefore, they should rate all applicants as average.

 

 

“Halo” and “Horn” effects. Sometimes, interviewers tend to allow one good (“halo”) or bad (“horn”) characteristic or qualification to influence the evaluation of all the other qualifications of an applicant. For example, a candidate has a degree from a prestigious university, so you think he/she must be highly competent and is therefore looked upon favourably. Interviewers need to be aware that they might be so impressed by an applicant on one qualification that they may falsely attribute positive qualities for all other criteria regardless of the evidence provided. Conversely, when applicants do poorly in one area, they may be under-rated in other areas assessed.

 

 

Fatigue. This is the tendency for interviewers to become fatigued during a lengthy assessment process and become less consistent or less vigilant in applying the assessment criteria.

 

 

Stereotypes. Sometimes, an interviewer’s biases and preconceptions of a desirable employee can influence the evaluation. Stereotyping is often based on demographics such as gender, race, ethnicity, or age, but it can also involve other variables such as degree of education, politics, or interests. Interviewers must be aware that their personal beliefs and perceptions of what is needed for the job may impact their evaluation of applicants.

 

 

Similar-to-me. This error occurs when an applicant is given more favourable evaluations than warranted because of a similarity to the interviewer in some way (e.g., gender, race, age, attitudes or background). Unlike me, the reverse can also occur where an applicant is given a less favourable evaluation than warranted.

 

 

Confirmation Bias: Interviewers may seek out information that confirms their initial perception about the candidate based on their resume, cover letter or application form while discounting or ignoring any information that is not supportive. Essentially, the interviewer wants to believe they are correct.

 

 

Contrast Bias: Interviewers may unintentionally compare candidates against each other rather than against the job requirements. It can result in one person looking stronger in a desired skill when, in fact, they merely look strong compared to the other candidates.

 

 

Nonverbal behaviour bias occurs when an interviewer likes an answer and smiles and nods, making the candidate think they are on the right track when answering a question. HR professionals and managers should know their body language in an interview. The interviewer may also evaluate the candidate based on his or her body language, such as a handshake, a smile, and his or her posture. During a stressful interview, candidates will be judged on their skills and experience, not their body language.

 

 

A gut feeling bias is when an interviewer relies on an intuitive feeling about a candidate.

 

 

Generalization bias can occur when an interviewer assumes that someone behaves in an interview is how they always behave. For example, if a candidate is very nervous and stutters while talking, an assumption may be made that he or she typically stutters.

 

 

Finally, recency bias occurs when the interviewer remembers candidates interviewed most recently, more so than the other candidates. When many candidates are interviewed in a day, they may seem to merge together from the interviewer’s perspective. An interviewer may subconsciously favour a candidate at the end of the interview process, but the best candidate for the job may have been the first candidate interviewed!

 

Be mindful of these errors and biases throughout the interview, and always take detailed notes to document the applicants’ comments.


5.10 Interview Bias” from Human Resources Management – 3rd Edition by Debra Patterson is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.—Modifications: Used first three paragraphs, edited.

Common bias from Structured Interviewing by the Public Service Commission of Canada used under the Crown Copyright – NonCommercial Reproduction Licence (Canada). The Government of Canada is not affiliated with nor endorses the reproduction of its official documents here.—Modifications: Used Section 4: Common assessment errors, edited, reorganized, added additional examples.

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