# As Confidence Aligns: Exploring the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Making

arXiv: https://arxiv.org/abs/2501.12868 · HTML: https://mlsanity.com/paper/2501.12868/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 77 references that are in the map.
- First posted on arXiv 22 Jan 2025.

## Builds on (most cited first, 16 of 16)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [On Calibration of Modern Neural Networks](https://mlsanity.com/paper/1706.04599/) (2017)
- [Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance](https://mlsanity.com/paper/2006.14779/) (2020)
- [Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making](https://mlsanity.com/paper/2001.02114/) (2020)
- [Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?](https://mlsanity.com/paper/2005.01831/) (2020)
- [Expanding Explainability: Towards Social Transparency in AI systems](https://mlsanity.com/paper/2101.04719/) (2021)
- [To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making](https://mlsanity.com/paper/2102.09692/) (2021)
- [Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration](https://mlsanity.com/paper/2109.14285/) (2021)
- [AI in Finance: Challenges, Techniques and Opportunities](https://mlsanity.com/paper/2107.09051/) (2021)
- [Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations](https://mlsanity.com/paper/2301.07255/) (2023)
- [Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation](https://mlsanity.com/paper/2204.11788/) (2022)
- [Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making](https://mlsanity.com/paper/2301.05809/) (2023)
- ["Are You Really Sure?" Understanding the Effects of Human Self-Confidence Calibration in AI-Assisted Decision Making](https://mlsanity.com/paper/2403.09552/) (2024)
- [A Human-Grounded Evaluation of SHAP for Alert Processing](https://mlsanity.com/paper/1907.03324/) (2019)
- [Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI](https://mlsanity.com/paper/2106.01410/) (2021)
- [Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision Making](https://mlsanity.com/paper/2401.07058/) (2024)

## Built on by (most cited first, 19 of 19)

- [ConfTuner: Training Large Language Models to Express Their Confidence Verbally](https://mlsanity.com/paper/2508.18847/) (2025)
- [Conformal Linguistic Calibration: Trading-off between Factuality and Specificity](https://mlsanity.com/paper/2502.19110/) (2025)
- [Exploring the Effects of Chatbot Anthropomorphism and Human Empathy on Human Prosocial Behavior Toward Chatbots](https://mlsanity.com/paper/2506.20748/) (2025)
- [AI-exhibited Personality Traits Can Shape Human Self-concept through Conversations](https://mlsanity.com/paper/2601.12727/) (2026)
- [Psychological and behavioural responses in human-agent vs. human-human interactions: a systematic review and meta-analysis](https://mlsanity.com/paper/2509.21542/) (2025)
- [Exploring the Impact of Explainable AI and Cognitive Capabilities on Users' Decisions](https://mlsanity.com/paper/2505.01192/) (2025)
- [More Isn't Always Better: Balancing Decision Accuracy and Conformity Pressures in Multi-AI Advice](https://mlsanity.com/paper/2603.22152/) (2026)
- [Constructive Alignment: Governing Preference Dynamics in Human-AI Interaction](https://mlsanity.com/paper/2607.00001/) (2026)
- ["Is This Really a Human Peer Supporter?": Misalignments Between Peer Supporters and Experts in LLM-Supported Interactions](https://mlsanity.com/paper/2506.09354/) (2025)
- [Is Length Really A Liability? An Evaluation of Multi-turn LLM Conversations using BoolQ](https://mlsanity.com/paper/2601.16508/) (2026)
- [When Life Gives You AI, Will You Turn It Into A Market for Lemons? Understanding How Information Asymmetries About AI System Capabilities Affect Market Outcomes and Adoption](https://mlsanity.com/paper/2601.21650/) (2026)
- [Density-Informed Pseudo-Counts for Calibrated Evidential Deep Learning](https://mlsanity.com/paper/2602.01477/) (2026)
- [Not All Trust is the Same: Effects of Decision Workflow and Explanations in Human-AI Decision Making](https://mlsanity.com/paper/2603.05229/) (2026)
- [Beyond the Steeper Curve: AI-Mediated Metacognitive Decoupling and the Limits of the Dunning-Kruger Metaphor](https://mlsanity.com/paper/2603.29681/) (2026)
- [Trust the AI, Doubt Yourself: The Effect of Urgency on Self-Confidence in Human-AI Interaction](https://mlsanity.com/paper/2604.07535/) (2026)
- [Identifying High-Confidence Social Biases in LLMs for Trustworthy Conversational Tutoring Agents](https://mlsanity.com/paper/2606.01584/) (2026)
- [Human-AI Coordination Zones: A Framework for Designing Human-in-the-Loop Experiences with Agentic AI](https://mlsanity.com/paper/2606.09848/) (2026)
- [Human-AI Teaming Through the Lens of Calibration](https://mlsanity.com/paper/2606.10906/) (2026)
- [Novice Reliance Calibration in AI-Assisted Decision Making: The Role of Explanations and Self-Assessment](https://mlsanity.com/paper/2610.07800/) (2026)

## Abstract (arXiv)

Complementary collaboration between humans and AI is essential for human-AI decision making. One feasible approach to achieving it involves accounting for the calibrated confidence levels of both AI and users. However, this process would likely be made more difficult by the fact that AI confidence may influence users' self-confidence and its calibration. To explore these dynamics, we conducted a randomized behavioral experiment. Our results indicate that in human-AI decision-making, users' self-confidence aligns with AI confidence and such alignment can persist even after AI ceases to be involved. This alignment then affects users' self-confidence calibration. We also found the presence of real-time correctness feedback of decisions reduced the degree of alignment. These findings suggest that users' self-confidence is not independent of AI confidence, which practitioners aiming to achieve better human-AI collaboration need to be aware of. We call for research focusing on the alignment of human cognition and behavior with AI.