Information Flow Theory (IFT) of Biologic and Machine Consciousness: Implications for Artificial General Intelligence and the Technological Singularity
This foundational theory addresses the challenge of understanding consciousness for AI researchers and philosophers, potentially enabling artificial general intelligence and superhuman consciousness.
The paper tackles the problem of explaining consciousness by proposing Information Flow Theory (IFT) as a novel framework that scales across biological and artificial systems, focusing on information flow direction rather than computation to generate new predictions.
The subjective experience of consciousness is at once familiar and yet deeply mysterious. Strategies exploring the top-down mechanisms of conscious thought within the human brain have been unable to produce a generalized explanatory theory that scales through evolution and can be applied to artificial systems. Information Flow Theory (IFT) provides a novel framework for understanding both the development and nature of consciousness in any system capable of processing information. In prioritizing the direction of information flow over information computation, IFT produces a range of unexpected predictions. The purpose of this manuscript is to introduce the basic concepts of IFT and explore the manifold implications regarding artificial intelligence, superhuman consciousness, and our basic perception of reality.