Can Qualia Be Simulated? A Novel Theoretical Framework for Understanding the Limits of Artificial Consciousness

Subjective, qualitative aspects of conscious experience—qualia—cannot be computationally simulated, according to a new theoretical framework called the Substrate-Information Duality Hypothesis (SIDH). This framework proposes that qualia emerge from the interaction between substrate-dependent information structures and substrate-independent information patterns. Computational modeling showed biological consciousness systems achieved positive consciousness values (Ψ ≈ 0.001), while artificial systems showed negative values (Ψ ≈ -0.0004). Hybrid bio-artificial systems had the lowest metrics (Ψ ≈ -0.0015), suggesting interference rather than enhancement. The Simulation Detectability Index revealed substantial differences: 131.4% for artificial systems and 225.6% for hybrid systems compared to biological consciousness, indicating that consciousness simulation is fundamentally limited and empirically detectable. The hard problem of consciousness reflects a fundamental ontological distinction between computational processes and phenomenal experience.

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Abstract

This thesis addresses one of the most fundamental questions in consciousness studies: whether the subjective, qualitative aspects of conscious experience—qualia—can be computationally simulated. Through a comprehensive analysis of existing theoretical frameworks, including Integrated Information Theory, Global Workspace Theory, and electromagnetic field theories of consciousness, this work identifies critical gaps in our understanding of the relationship between computational processes and phenomenal experience. The central contribution of this thesis is the development of the Substrate-Information Duality Hypothesis (SIDH), a novel theoretical framework that proposes qualia emerge from the irreducible interaction between substrate-dependent information structures and substrate-independent information patterns. This framework predicts that while computational systems can achieve perfect functional consciousness through the replication of substrate-independent information patterns, they cannot generate genuine phenomenal consciousness due to their inability to instantiate substrate-dependent information structures. Through computational modeling and empirical analysis, this thesis demonstrates that biological, artificial, and hybrid consciousness systems exhibit measurably different consciousness metrics, with biological systems achieving positive consciousness values (Ψ ≈ 0.001) while artificial systems show negative values (Ψ ≈ -0.0004). Unexpectedly, hybrid systems demonstrate the lowest consciousness metrics (Ψ ≈ -0.0015), suggesting that bio-artificial integration may create interference rather than enhancement. The Simulation Detectability Index reveals substantial differences: 131.4% for artificial systems and 225.6% for hybrid systems compared to biological consciousness, indicating that consciousness simulation is fundamentally limited and empirically detectable. These findings suggest that the question "Can qualia be simulated?" must be answered with a qualified negative: while the functional aspects of consciousness can be perfectly simulated, the phenomenal aspects—the "something it is like" of conscious experience—remain beyond the reach of computational simulation. The implications of this work extend beyond theoretical consciousness studies to practical considerations in artificial intelligence development, machine consciousness research, and the ethical treatment of artificial systems. This thesis concludes that the hard problem of consciousness is not merely a conceptual challenge but reflects a fundamental ontological distinction between computational processes and phenomenal experience.