There is growing interest in the introspective and metacognitive capacities of AI systems (eg Comsa & Shanahan, 2025; Steyvers & Peters, 2025). Most recent work, including that from our group, has focused on the abilities of large language models (LLMs) to reflect on individual, isolated decisions or events (Kumaran et al., 2025; Lindsey, 2026). However, (human) metacognition is richer than this, involving the building of “self-models” over longer timescales (Fleming, 2024).
This project will characterise the dynamics and features of local-global metacognitive integration in LLMs.
University College London, UK
Ali is a postdoctoral researcher in cognitive neuroscience whose work focuses on the neural mechanisms underlying cognitive representations. He combines MEG, fMRI, computational modeling, and machine learning to investigate how the human brain represents and organizes information over space and time. His broader research interests lie at the intersection of neuroscience and artificial intelligence, with an emphasis on understanding intelligence through both biological and computational systems.