Charlotte Cheatle
Academic and research departments
Faculty of Health and Medical Sciences, School of Psychology, Cognitive Psychology research group, Brain and Behaviour section.About
My research project
Distributed Cognition in the Age of AI: Understanding the Mechanisms and Outcomes of Cognitive Offloading in AI-Assisted Decision MakingMy research examines how distributing cognition to AI systems changes the cognitive and metacognitive processes underlying human judgement and decision making. In particular, I focus on how different forms of cognitive offloading, such as delegating memory or judgement processes to AI, alters cognitive engagement, information sampling, and the internal cues people use to monitor their own performance. Across a series of studies, I investigate the mechanisms underlying metacognitive calibration and the performance outcomes associated with AI-augmented decision making.
Supervisors
My research examines how distributing cognition to AI systems changes the cognitive and metacognitive processes underlying human judgement and decision making. In particular, I focus on how different forms of cognitive offloading, such as delegating memory or judgement processes to AI, alters cognitive engagement, information sampling, and the internal cues people use to monitor their own performance. Across a series of studies, I investigate the mechanisms underlying metacognitive calibration and the performance outcomes associated with AI-augmented decision making.
University roles and responsibilities
- Graduate Teaching Assistant
- SEF Chair for the Faculty of Health and Medical Sciences
- University Research and Innovation Committee PGR Representative
- School of Psychology PGR Representative
My qualifications
Publications
Appropriate AI reliance requires users to accurately evaluate their own performance in order to discern whether to retain or defer responsibility. While underconfidence is a known driver of automation bias, little is known about how collaboration with AI itself influences users’ metacognition. We investigated how cognitive offloading different stages of the decision-making process affects confidence calibration. Participants completed diagnostic decision-making tasks with varying levels of memory and judgement support. Overall, cognitive offloading impaired confidence calibration, with unaided decision makers showing the greatest alignment between confidence and accuracy. Importantly, offloading different cognitive processes produced distinct metacognitive biases: judgement offloading led to overconfidence, whereas combined offloading of memory and judgement processes led to underconfidence. These findings demonstrate that AI support can disrupt user confidence calibration in systematic ways, depending on the type and extent of cognitive delegation. The results highlight metacognitive miscalibration as a critical and underexplored consequence of human-AI collaboration.