Metacognition and Confidence Dynamics in Advice Taking from Generative AI
Clara Colombatto, Sean Rintel, Lev Tankelevitch

TL;DR
This study explores how confidence in oneself and GenAI influences advice-seeking and reliance, revealing that advice exposure boosts confidence and detailed responses often lack thorough checking, affecting decision quality.
Contribution
It introduces a novel paradigm to examine confidence dynamics in advice-taking from GenAI, demonstrating causal effects of advice exposure on confidence and reliance behaviors.
Findings
Advice-seeking increases confidence in GenAI and decreases confidence in self.
Advice exposure causally boosts retrospective confidence in both GenAI and self.
Participants often rely on verbose advice without thorough checking, missing key information.
Abstract
Generative Artificial Intelligence (GenAI) can aid humans in a wide range of tasks, but its effectiveness critically depends on users being able to evaluate the accuracy of GenAI outputs and their own expertise. Here we asked how confidence in self and GenAI contributes to decisions to seek and rely on advice from GenAI ('prospective confidence'), and how advice-taking in turn shapes this confidence ('retrospective confidence'). In a novel paradigm involving text generation, participants formulated plans for events, and could request advice from a GenAI (Study 1; N=200) or were randomly assigned to receive advice (Study 2; N=300), which they could rely on or ignore. Advice requests in Study 1 were related to higher prospective confidence in GenAI and lower confidence in self. Advice-seekers showed increased retrospective confidence in GenAI, while those who declined advice showed…
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