Abstract General AI has pursued the replication of human-level intelligence without first decomposing human cognition into structurally distinct components. Human cognition, however, is shaped by embodied constraints such as mortality, survival pressures, finite lifespan, and physiological states. This paper argues that when cognition is treated as a single undifferentiated whole, embodied modulation is not accidentally introduced into AI systems but structurally entailed. Any attempt to imitate “human intelligence” under a monolithic model necessarily incorporates variability shaped by mortal embodiment. The tensions observed in contemporary AI systems are better understood as consequences of copying an undecomposed target rather than isolated implementation errors. A dual-layer framework—Core and Modulation—clarifies this structural necessity and renders selective architectural differentiation possible for the first time, redefining AI as an architecture capable of explicitly separating logical coherence from embodied variability.
Griselda Poe (2026) studied this question.