Interviewer Bias

THE-Spellchecker's avatar
Published Nov 18, 2023Updated May 15, 2024
Contribute to Docs

Interviewer bias refers to bias due to a participant’s perception of the interviewer. This may be due to a user’s own biased perception of an interviewer’s ethnicity, age, gender, or physical appearance — or even details like body language or facial expressions. Interview bias can be difficult to avoid, so it is just important to keep in mind when evaluating the data.

Example

Imagine that a team of four researchers conducts user interviews. Three of the researchers are 25 years old and one researcher is 50 years old. All interview participants are 20-25 years old.

When reviewing the data, the team noticed a clear trend: participants who talked to the younger researchers shared detailed responses that indicated honesty and openness. By contrast, most participants who spoke with the older researcher shared little detail, and their responses indicated an unwillingness to share openly. In this case, participants may have held a bias against the older researcher, which impacted how they approached the interview.

All contributors

Contribute to Docs

Learn UI and UX Design on Codecademy