Throughout the Between a Graph and A Hard Place blog series, we’ve often spoken of bias and controlling bias. From keeping your own bias in check during qualitative data analysis to understanding social desirability bias during surveys and observations, managing bias is a constant challenge throughout all aspects of evaluation from planning to presenting. During interviews bias can be particularly difficult to avoid, taking many different forms and heavily impacting the quality of the data being collected. This post will take a look at what bias is and three different ways it can distort data during an interview. The next LRS post will tackle ways to mitigate bias, not only during interviews but throughout our lives.
What is Bias
In order to mitigate bias, you need to be able to recognize it. In order to recognize it, you need to understand what bias is and the intricate ways it can manifest itself. In fact, just hearing the word bias could bring feelings or images into your head. Do you feel defensive because you generally try to ignore your bias? Or do you picture news media outlets covering political controversies? Either of these thoughts could influence how you read this article and the information that you take away from it, which is actually an effect of bias we will discuss further. Many slightly different definitions for bias float around the internet, but let’s try our best to start with the facts. Bias is defined on Dictionary.com as “a particular tendency, trend, inclination, feeling, or opinion, especially one that is preconceived or unreasoned.” This broad definition shows how difficult it can be to avoid bias. I think we can all admit to having at least some arbitrary tendencies or opinions that are based on our preconceived notions rather than facts. Taking time to understand the prevalence of bias throughout our day to day life is important to realizing how much consideration and effort it takes to limit the many different types of biases from creeping into our research.
A Biased Interviewer
There’s some pretty obvious, and some not so obvious, ways that bias may influence an interview. Since we’re library professionals who may find ourselves conducting interviews, let’s first examine how an interviewer’s personal bias can affect the data collected in an interview. If an interviewer sits down to conduct an interview but already has preconceived notions about who the interviewee is and what they are likely to say, their takeaways from the interview may be completely different than if they listened with an open mind. Even if you’re outwardly presenting all the correct active listening skills during an interview, if internally you aren’t managing your biases, it’s likely you won’t accurately hear what the interviewee is telling you.
“Cat People” versus “Dog People”
Let’s use a long standing divide between pet owners as an example – are you a “cat person” or a “dog person”? Maybe this is my own bias creeping in, but for this example let’s say the interviewer is a library staff member and a “cat person” and the interviewee is a community member who owns five dogs. The library staff want feedback on the library’s outreach efforts, so they have organized interviews with some regular patrons and these two characters are sitting down for a semi-structured interview. The interviewer is aware that this community member owns many dogs and therefore, has already labeled them as a “dog person.” During the interview the library staff asks, “How do you think the library can increase engagement throughout the community?” The dog owner responds, “Maybe the library could have a library mascot, such as a mascot dog, to be part of its branding and engage children and animal lovers.” However, the interviewer sat down for the interview stuck with the impression that this person is a “dog person” so when they hear “dog” included in the response they immediately stop listening and dismiss the idea of a mascot. This library staff member has assumed the interviewee just likes to make everything about dogs and also assumes that others won’t find this idea nearly as engaging.
Is a library mascot a bad idea to engage the community? Probably not. Is the community member insisting that the mascot be a dog? Not at all. Does their reasoning behind the suggestion make sense? Yes. Nevertheless, the interviewer’s bias towards cats and their preconceived notions of the interviewee stops them from considering the positives of a library mascot or following up with the idea.
Obviously, this example only scratches the surface of how detrimental holding biases can be to data collection. Biases can make us blind to the ideas of people we have othered and this blindness may lead to poor interview takeaways and the dismissal of otherwise brilliant ideas.
The Interviewee’s Bias
Now remember that everyone may hold biases, including the person being interviewed. Not only does the interviewer’s bias influence what they hear, but how the interviewee perceives the interviewer will also influence what they say. Let’s rewind. Say these same two people, the “cat person” interviewer and the dog owning interviewee, sit down for the same interview, but this time the interviewer is wearing a sweater with kittens all over it. Because of the sweater the interviewee makes the correct assumption that the interviewer likes cats. The community member wants the library staff to like them and their ideas, so they respond to the same question by suggesting a library mascot “such as a cat” instead of a dog. In this case, the suggestion of a library mascot cat is only given because the interviewee feels that the library staff will respond positively if cats are brought up. When characteristics of the interviewer influence the response of the interviewee such as this, it is known as the interviewer effect.
Displaying Bias Towards Responses
The interviewer may be surprised that the dog owner suggested the mascot be a cat instead of a dog, and this brings us back to interviewer bias and the third type of bias we will discuss. If the interviewer shows they are pleasantly surprised by sitting up, leaning forward, and smiling, this will likely encourage the interviewee to elaborate further on their mascot idea. The interviewer then goes off script to hear more about this idea of a library cat mascot and the interviewee, happy there is interest in their idea, responds enthusiastically. In this case, the library staff’s outward expressions are influencing the community member to continue talking on a subject they otherwise wouldn’t have. Suddenly the data collected in this interview is completely different than in our first example, and this interview may result in the library staff following up with their colleagues regarding the development of a mascot which is also a completely different outcome.
Returning to Reality
These subtle shifts in interview responses and the consequentially different outcomes of these two interviews all took place because of how the interviewer and interviewee perceived each other. As you can imagine, when the biases we hold are more deeply ingrained than a preference towards dogs versus cats and are rooted in fear as biases often are, the effects can be even more significant. In the next post we will explore how to mitigate bias in research interviews and throughout our lives. In the meantime, here are five points to keep in mind.
- In order to recognize and mitigate your own biases you must first understand what bias is.
- Bias can affect interviews when the interviewer has a preconceived idea of who the interviewee is and what they will say. This may cause the interviewer to only focus on certain parts of what is said and not the whole story.
- The interviewee can also be biased towards characteristics of the interviewer which may influence how they respond.
- Both positive and negative reactions by the interviewer to responses can influence what the interviewee says if they are basing their responses on what they think the interviewer wants to hear.
- While bias during interviews can be subtle, it can still have a significant impact on the data collected if not left unchecked, and in many cases conducting a biased interview may harm or retraumatize the parties involved.
LRS’s Between a Graph and a Hard Place blog series provides instruction on how to evaluate in a library context. Each post covers an aspect of evaluating. To receive posts via email, please complete this form.