Embodied cognition remains a contested concept in cognitive science and AI. Some researchers treat the body as a sensorimotor interface that grounds computational processes in environmental interaction, while biologically-oriented views stress the living body's homeostatic and allostatic self-regulation as foundational for both sensorimotor interaction and cognition. Adopting the latter perspective—a multi-tiered affectively embodied view—the author argues that modeling organisms as layered networks of bodily self-regulation mechanisms can advance scientific understanding of embodied cognition.
Information theory and control theory can model embodied cognition without requiring time-reversal symmetry. An iterated Morse function provides a 'higher entropy' analog that follows Onsager-like nonequilibrium thermodynamics, but because palindromes are unlikely, reciprocal relations do not hold. Group symmetry-breaking in physical phase transitions appears as groupoids linked to high-probability developmental paths. The formalism yields the Yerkes-Dodson inverted-U relation and stochastic dynamics, and suggests a canonical approach to consciousness. Context is central to real-world cognition, contrary to Western cultural emphasis on individual salience over context.
Consciousness likely depends on biological processes within individual cells that have no equivalent in computer-based artificial intelligence. The argument challenges the prevailing view that AI consciousness is primarily a matter of functional information density and integration, and that no technical barriers prevent its achievement. When cognition is understood as a cellular attribute, the premises underlying the possibility of AI consciousness are directly contradicted. The innate characteristics of biological information and how cells manage that information have no parallels in machine-based AI systems. Any claim of computer-based AI consciousness represents a fundamental misunderstanding of these crucial differences.
A productive strategy for investigating consciousness compares brain processes that are conscious with those that are not. A related but less explored strategy examines how brain processes transition from unconscious to conscious as individuals develop and across evolution. These transitions occur when brain processes become object to a new, emergent, higher-level subject. The paper reconstructs a minimally-complex subject-object subsystem capable of giving rise to consciousness, suggesting its emergence was driven by coordinating body-environment interactions in real time, such as hand-eye coordination. Conscious processing initially served to organize real-time sensorimotor coordination. Subsequent major transitions include the emergence of conscious mental modelling, which arose from simulations of motor actions used to anticipate consequences, enabling evaluation of alternative responses. The paper predicts further major transitions in consciousness.