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

TL;DR

This study investigates how AI confidence influences human self-confidence during decision-making, revealing that confidence levels tend to align and persist, affecting calibration and collaboration effectiveness.

Contribution

It provides empirical evidence that AI confidence impacts human self-confidence and highlights factors that influence this alignment in human-AI decision processes.

Findings

Users' self-confidence aligns with AI confidence.

Alignment persists even after AI is removed.

Real-time feedback reduces confidence alignment.

Abstract

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.