── ── Cognitive bias
Dunning-Kruger Effect
The Dunning-Kruger effect is the systematic self-assessment asymmetry demonstrated by Kruger & Dunning (1999): bottom-quartile performers overestimate rank by ~50 percentile points; top-quartile performers underestimate by ~5 points. Mechanism: the cognitive skills needed to perform a task are the same ones needed to evaluate performance — so novices lack the metacognition to see their own gap. The corrective is external…
How it works
Step 1 — State the claim: Domain · verbatim claim · self-assessed percentile · basis for assessment · stakes.
Step 2 — Test metacognitive prerequisite: Can the person evaluate others' performance in this domain? Have they received external feedback? Can they articulate what failure looks like?
Step 3 — Get external data: Objective metrics · blind peer comparison · expert evaluation · track record · calibration test (predict score → take test → compare).
When to use it
- someone says 'how hard could it be' about an unfamiliar domain
- a novice dismisses expert opinion or says 'I could do that'
- someone's self-assessed confidence seems disconnected from their actual track record
- a hiring or promotion decision is driven by self-presentation
- feedback loops are absent and someone is operating on gut confidence alone
When not to use it
the person is a known expert with an established external track record; the confidence claim is in a domain with tight, recent feedback loops that already calibrate performance.
Worked example
Kruger and Dunning's 1999 Cornell Studies
The empirical foundation is Kruger and Dunning's four-study sequence at Cornell University in 1999, which together demonstrated the effect across multiple domains and tested its mechanism.
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skills