mlsanityData to 14 Oct 2026

Beyond Accuracy: How AI Metacognitive Sensitivity improves AI-assisted Decision Making

arXiv 2507.22365 ↗First posted 30 Jul 2025cs.AI cs.HCcited by 2

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Abstract (arXiv)

In settings where human decision-making relies on AI input, both the predictive accuracy of the AI system and the reliability of its confidence estimates influence decision quality. We highlight the role of AI metacognitive sensitivity -- its ability to assign confidence scores that accurately distinguish correct from incorrect predictions -- and introduce a theoretical framework for assessing the joint impact of AI's predictive accuracy and metacognitive sensitivity in hybrid decision-making settings. Our analysis identifies conditions under which an AI with lower predictive accuracy but higher metacognitive sensitivity can enhance the overall accuracy of human decision making. Finally, a behavioral experiment confirms that greater AI metacognitive sensitivity improves human decision performance. Together, these findings underscore the importance of evaluating AI assistance not only by accuracy but also by metacognitive sensitivity, and of optimizing both to achieve superior decision outcomes.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 12 of its 41 references that are in the map. First posted on arXiv 30 Jul 2025.

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12 of 41 references.

References · 12

  1. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,448
  2. 2022Language Models (Mostly) Know What They Knowcited by 1,856
  3. 2020How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answeringcited by 445
  4. 2020Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Makingcited by 281
  5. 2017Predict Responsibly: Improving Fairness and Accuracy by Learning to Defercited by 233
  6. 2024Benchmarking LLMs via Uncertainty Quantificationcited by 126
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  8. 2021Towards Unbiased and Accurate Deferral to Multiple Expertscited by 72
  9. 2023Human-Aligned Calibration for AI-Assisted Decision Makingcited by 28
  10. 2022Uncalibrated Models Can Improve Human-AI Collaborationcited by 26
  11. 2024"Are You Really Sure?" Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision Makingcited by 26
  12. 2024Hybrid Forecasting of Geopolitical Eventscited by 3

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Citing papers per year: 2026: 2.

2 papers.