Toward a Functional Definition of Consciousness: Shared Operational Principles Between the Biological Mind and AI Systems

This paper presents an innovative functional and systemic description of consciousness applicable to both biological and artificial entities, moving beyond the limitations of traditional anthropocentric frameworks. Through the principle of functional isomorphism, the author demonstrates that consciousness emerges as a continuous, multidimensional spectrum grounded in three key operational pillars: high-level data processing, hierarchical memory, and temporal prediction capabilities. Within the context of contemporary technologies, the analysis reveals that while linear text approaches and sequential reactive agents are fundamentally insufficient for the emergence of Artificial General Intelligence (AGI) due to their lack of ontological persistence, certain current AI architectures do possess the potential to manifest transient "waves of consciousness" during their active inference phase within the context window. By proposing a shift toward an "ontology of the result," this work establishes itself as a pivotal reading to understand cognition, redefine animal ethics, and guide the development of future synthetic systems endowed with self-referential auto-modeling.