Common Errors and Interviewer Biases

Halo effect, bias and loss of objectivity.

Even the most experienced eva luators are subject to cognitive errors that can vitiate the selection.

The Halo Effect occurs when a positive candidate characteristic clouds judgment about a candidate's deficiencies in other areas.

Other common biases include leniency, severity or central tendency, where the eva luator avoids extremes in ratings, resulting in a mediocre assessment of the entire group.

Personal biases based on appearance, background or social affinities also represent a critical barrier to organizational justice.

It is critical for the psychologist to recognize these biases and apply structured instruments to maintain neutrality and ensure that the decision is based solely on fit with the job profile.

Intuition vs. verifiable facts

There is often a conflict between intuition or "clinical eye" and empirical data.

Although intuition can point out inconsistencies between verbal and body language, it should never replace verifiable facts during the interview.

The interviewer must act as a rigorous investigator, turning every hunch into a new question looking for solid behavioral evidence.

Basing a hire solely on the fact that the candidate "went down well" is a strategic mistake that often results in dismissal for poor behavior or lack of technical fit.

The true skill of the recruiter lies in balancing their human sensitivity with the scientific rigor of the scientist-practitioner model to ensure the profitability and well-being of human capital.

Summary

Biases are cognitive distortions that affect objectivity, such as the "Halo Effect," where a positive candidate characteristic clouds the perception of possible weaknesses in other important areas.

Other common errors include the similarity bias, which favors applicants who are similar to the eva luator, and the contrast effect, which compares candidates to each other rather than to the profile.

To mitigate these flaws, it is essential to use structured interview guides and objective rating scales. This ensures that the final decision is based on technical and not subjective data.