mlsanityData to 14 Oct 2026

Confidence Freeze: Early Success Induces a Metastable Decoupling of Metacognition and Behaviour

arXiv 2603.21043 ↗First posted 22 Mar 2026cs.LGcited by 0

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Abstract (arXiv)

Humans must flexibly arbitrate between exploring alternatives and exploiting learned strategies, yet they frequently exhibit maladaptive persistence by continuing to execute failing strategies despite accumulating negative evidence. Here we propose a ``confidence-freeze'' account that reframes such persistence as a dynamic learning state rather than a stable dispositional trait. Using a multi-reversal two-armed bandit task across three experiments (total N = 332; 19,920 trials), we first show that human learners normally make use of the symmetric statistical structure inherent in outcome trajectories: runs of successes provide positive evidence for environmental stability and thus for strategy maintenance, whereas runs of failures provide negative evidence and should raise switching probability. Behaviour in the control group conformed to this normative pattern. However, individuals who experienced a high rate of early success (90% vs. 60%) displayed a robust and selective distortion after the first reversal: they persisted through long stretches of non-reward (mean = 6.2 consecutive losses) while their metacognitive confidence ratings simultaneously dropped from 5 to 2 on a 7-point scale.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 18 references that are in the map. First posted on arXiv 22 Mar 2026.

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References · 5

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2017Deep Reinforcement Learning that Matterscited by 754
  3. 2025Language Models Are Capable of Metacognitive Monitoring and Control of Their Internal Activationscited by 41
  4. 2021A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithfulcited by 28
  5. 2025How Metacognitive Architectures Remember Their Own Thoughts: A Systematic Reviewcited by 2

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