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Cognitive Metasciences

A broader, more theoretical category encompassing fields that take the entire project of cognitive science—the interdisciplinary study of mind and intelligence—as their object of critique and analysis. This includes questioning the computational metaphor of the mind, the limits of artificial intelligence as a model for human thought, and the cultural assumptions built into our models of intelligence. It's cognitive science reflecting on its own foundational metaphors.
Cognitive Metasciences Example: Critiquing the dominant paradigm in AI research for assuming that intelligence is purely information processing, while ignoring the role of embodied experience, emotion, and social interaction, is an exercise in Cognitive Metascience. It asks if the field is solving the right puzzle, or just the one that fits its preferred tools.
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Cognitive Metasciences

The systematic study of the cognitive sciences themselves—a second-order discipline that takes psychology, neuroscience, artificial intelligence, linguistics, and related fields as its objects of inquiry. Cognitive metasciences ask meta-level questions about cognitive scientific knowledge: How do cognitive scientists know what they claim to know? What methods do different cognitive science disciplines use? How does cognitive scientific knowledge change over time? How do social, cultural, and institutional contexts shape cognitive science? What are the limits of cognitive scientific understanding? Cognitive metasciences are the cognitive sciences reflecting on themselves—the attempt to understand what cognitive science is, what it can achieve, and how it relates to other forms of knowledge. They're essential for cognitive science to be self-aware rather than merely productive, for cognitive scientists to understand their own practices rather than just practicing them.
Example: "Her cognitive metasciences research examined how the dominance of fMRI has shaped what questions get asked in neuroscience—not because other questions aren't important, but because the tool creates a field of visibility that attracts attention and funding. The science studying itself reveals its own biases."
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