How the Dunning-Kruger Effect Skews Self-Reported Skill Ratings

In this episode, Dr. Azdren Coma explores how the Dunning-Kruger effect distorts self-reported skill ratings in hiring and surveys. A seemingly straightforward question like “On a scale of 0 to 10, how skilled are you in Microsoft Excel?” can produce misleading data because undefined scale points allow respondents to interpret them differently. Beginners often overestimate their abilities due to limited awareness of complexity, while more skilled individuals rate themselves more conservatively as they recognize what they don’t know—potentially reversing the ranking of candidates.

This episode breaks down the psychological mechanism behind the bias, illustrates it with real-world examples, and offers practical fixes for better data quality, including fully labeling scales, using clearer anchors, and shifting to task-specific questions. Ideal for HR professionals, hiring managers, and anyone relying on self-assessments in talent acquisition or people operations.

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