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arXiv · 2511.17509

Beyond Awareness: Investigating How AI and Psychological Factors Shape Human Self-Confidence Calibration

Federico Maria Cau·Lucio Davide Spano
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Abstract

Human-AI collaboration outcomes depend strongly on human self-confidence calibration, which drives reliance or resistance toward AI's suggestions. This work presents two studies examining whether calibration of self-confidence before decision tasks, low versus high levels of Need for Cognition (NFC), and Actively Open-Minded Thinking (AOT), leads to differences in decision accuracy, self-confidence appropriateness during the tasks, and metacognitive perceptions (global and affective). The first study presents strategies to identify well-calibrated users, also comparing decision accuracy and the appropriateness of self-confidence across NFC and AOT levels. The second study investigates the effects of calibrated self-confidence in AI-assisted decision-making (no AI, two-stage AI, and personalized AI), also considering different NFC and AOT levels. Our results show the importance of human self-confidence calibration and psychological traits when designing AI-assisted decision systems. We further propose design recommendations to address the challenge of calibrating self-confidence and supporting tailored, user-centric AI that accounts for individual traits.

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Federico Maria Cau, Lucio Davide Spano. 2025-10-04. Beyond Awareness: Investigating How AI and Psychological Factors Shape Human Self-Confidence Calibration. https://arxiv.org/abs/2511.17509

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