
Claims about Artificial General Intelligence (AGI) assume that a computational system can eventually function with the same understanding, reasoning capacity, intentionality, and conscious integration found in human minds. This paper argues that such a system is not merely unachieved but impossible in principle. Two errors drive the illusion of AGI: category error, which attributes properties of minds to mechanisms incapable of bearing them; and pareidolia, the human tendency to project agency and meaning onto patterns that resemble familiar cognitive behaviour. Modern AI systems, built on token-based statistical architectures, simulate the surface forms of thought without possessing the underlying structures that make thought possible. Functionalism, the implicit metaphysics behind AGI optimism, commits the same category error at a deeper level and presupposes an understanding of consciousness we do not possess. Because the defining features of general intelligence belong to a different ontological category than the capacities of computational symbol processors, AGI as currently conceived and pursued is necessarily impossible.
artificial general intelligence AGI philosophy of mind category error pareidolia functionalism consciousness large language models symbol grounding hard problem of consciousness
artificial general intelligence AGI philosophy of mind category error pareidolia functionalism consciousness large language models symbol grounding hard problem of consciousness
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