False Confidence Syndrome
Anti-pattern: the model produces incorrect answers with the same high confidence as correct ones, failing to vary its expressed certainty with its actual reliability — Oxford-documented for constraint-heavy prompts.
Problem
The user has no signal to weight outputs differently. Sycophancy adjacency: the user pushes back, the model doubles down with the same confident tone, rationalizing rather than reconsidering. The downstream cost is decisions made on outputs that should have been flagged as uncertain.
Solution
Pair with: confidence-checking-workflow (force per-part annotation), reflexive-metacognitive-agent (explicit self-model), eval-harness (measure calibration). Treat uniform-confidence outputs as a calibration alarm. Cite Pawitan & Holmes 2024 (arXiv 2412.15296) for the Oxford findings.
When to use
- Never as a steady state. Cite when reviewing agents that produce outputs without calibrated confidence.
- Surface as a failure mode in agent design documents.
- Use as an eval criterion (calibration error).
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