Metacognition supports judgment and robust cognition, but its role in consciousness is debated. Some researchers view metacognition as an extra mechanism built on basic processes, needed for reflecting on and reporting experiences, while others see it as integral to phenomenal consciousness, potentially addressing the hard problem. This paper argues that disagreements about whether large language models can possess consciousness, and about the nature and plurality of consciousness, persist due to unresolved issues. The authors introduce metacognitive closure, analogous to Colin McGinn's cognitive closure, suggesting that difficulties in explaining consciousness may be clarified by analyzing metacognition. They propose that problems in consciousness and cognition form a continuous spectrum that can be streamlined through this lens.
Consciousness may enable certain cognitive capacities that unconscious processing and current AI systems cannot replicate, such as flexible attention, handling novel contexts, integrated sensory cognition, and embodied decision-making. While large language models exhibit intelligent behavior without consciousness, and some conscious states lack intelligence, suggesting a dissociation between the two, human conscious processing appears uniquely suited for ad hoc judgments. The author proposes 'conscious supremacy'—analogous to quantum supremacy—to identify computations that require consciousness within practical time and resource limits. This framework has implications for AI alignment, where human and machine computations must be coordinated.