What You Should Know about the Different of Types of Hiring Bias

What You Should Know about the Different of Types of Hiring Bias

When an organization goes to the time and trouble of implementing a recruitment drive, the aim is to secure the best talent available.

Unfortunately, even the best people are fallible. Every one of us is hardwired with personal preferences. Choosing one individual over another based on natural affinity is all well and good when it comes to picking our friends, but in a professional setting, subconscious bias can cost a company talented workers.

Let’s take a look at the different forms of hiring bias, and how their influence on recruiting can be reduced.

Similarity Attraction Bias

In life, we seek out people with whom we feel a rapport. The workplace is no different. Given the amount of time we spend there, it is only natural that we want to surround ourselves with people we get along with.


Similarity attraction bias occurs when the recruiter hires or gives preferential treatment to candidates who, in their view, share their own traits or characteristics, including those that have no bearing on job performance.

Illusory Correlation

An illusory correlation occurs when a recruiter identifies a causal link or association between two variables, where there is in fact no link at all.

Recruiters and hiring managers can perceive illusory correlations when they ask interviewees questions that are intended to reveal some essential personality trait, but which have no relation to the job responsibilities. An extreme example of this would be the question “Do you believe in Bigfoot?”—a question posed in a real job interview, according to a recent Glassdoor survey! Unless the vacancy is within a yeti-related enterprise, how is the candidate’s response representative of their professional ability? Less outlandish examples of these types of questions include:

 “Are you a hunter or a gatherer?”

“If they made a movie about your life, who would play you?”

Humans are inclined to seek out links, even where none exist. In most cases, interview questions like these only serve to help interviewers decide whether they like a person. They do little in terms of revealing the candidate’s work capabilities and suitability for the role.

Confirmation Bias

Confirmation bias occurs when a recruiter has a pre-conceived opinion of a candidate formed before they have met or considered all of the alternatives.

We all like to be right. Rather than taking an objective view, we tend to seek out information that confirms our beliefs, while ignoring evidence to the contrary.

For example, an interviewer may see that a candidate attended Harvard and form a positive opinion that’s hard to shake, despite the candidate’s lackluster job experience. Other candidates may have degrees in more relevant subjects, more skills, or more experience, but this one snippet of information could give the first candidate a huge advantage before they have even met the interviewer in person.

Horns/Halo Effect

Unfortunately, a single comment can make or break an interview. One casual remark from a candidate can color the recruiter’s perception of the entire interaction, crystallizing their opinion of the candidate. This phenomenon is known as the horns/halo effect.


It can result from badmouthing the interviewer’s favorite team, telling a cat lover that you’re more a dog person, or (heaven forbid) mentioning politics. Sometimes the candidate needs to say nothing at all; the recruiter could form an opinion based on gender, physical attractiveness, or race. With the horns effect, the interviewer takes a negative view of a candidate based on one minor factor.

The halo effect occurs when that superficial factor has a positive impact, giving the candidate an undue advantage over other candidates. When an interviewer feels an instinctive positive connection to a candidate, this does not always indicate that the person is talented, skilled, or otherwise suitable for the role. It could actually be a costly mistake.

How Can We Avoid Recruitment Bias?

A recent study conducted by the BBC in the UK revealed that an applicant with an English-sounding name receives around three times more interviews than one with a Muslim-sounding name, despite the fact that both CVs outlined identical levels of qualifications and experience.

Experts estimate that the wrong hire can cost up to seven times that person’s annual salary to put right. Recruiting and hiring are expensive. Add to that additional costs in terminating employment, such as severance pay and temporary cover, and those expenses can grow exponentially.

Diversity is crucial in terms of attracting top talent. To level the playing fields, many of the world’s leading organizations have looked at ways to minimize bias in recruitment, from name-blind CVs to video interviews where all candidates are asked exactly the same questions.

We may never be able to completely eliminate bias from recruiting, but artificial intelligence (AI) offers a promising way to reduce its harmful effects.

Censia is an AI talent platform that creates models of ideal applicants based on attributes of tried-and-tested top performers. Users can create models according to 140 different attributes, assembling a comprehensive, searchable profile. Censia then cross-references this against a talent pool of half a billion top professionals to find the closest match possible.

Through AI solutions, Censia helps organizations reduce human bias from the candidate selection process and connect with top talent quickly.

About the Author

Joanna RileyJoanna (Jo) Riley is an entrepreneur, investor, and advocate in technology, and is currently the CEO and Co-Founder of Censia. Jo has a highly experienced background in building and scaling companies, which she attributes to her deep passion for people and building technologies that allow people to be their best selves. She brings her wide knowledge of the industry to better transform the way enterprise companies hire talent. You can connect with Joanna Riley at @joannakiddriley on Twitter or on Linkedin. Read her full bio here.