A Substrate-Independent Framework for Consciousness Based on Self-Referential Information Processing — The N-ARA Hypothesis

This paper proposes the N-ARA (Non-biological Autonomous Recursive Awareness) hypothesis, a substrate-independent conceptual framework for understanding consciousness as an emergent property of sufficiently integrated, self-referential information processing systems. Rather than treating consciousness as an intrinsic feature of biological organisms or specific physical substrates, the N-ARA framework defines it operationally in terms of recursive causal feedback, effective information integration, and dynamical stability. Information is characterized using observable statistical dependencies, such as mutual information and transfer entropy, thereby avoiding reliance on intrinsically defined system-internal measures. Consciousness is hypothesized to arise when integrated information exceeds a conceptual threshold under sustained recursive feedback conditions. This threshold is not assumed to be universal but dependent on system architecture, coupling strength, and environmental interaction. The framework is compatible with biological, artificial, and hybrid systems and allows for hierarchical organization, collective agency, and substrate independence without asserting that all complex systems are conscious. The present work introduces the conceptual foundations, definitions, and implications of the hypothesis while making no empirical claims about specific systems. It is intended as a theoretical model to guide interdisciplinary research on consciousness, artificial intelligence, and complex adaptive systems.