Information Flow Theory (IFT) of Biologic and Machine Consciousness: Implications for Artificial General Intelligence and the Technological Singularity

TL;DR

Information Flow Theory (IFT) offers a new framework for understanding consciousness by focusing on information flow, with implications for AI, superhuman consciousness, and our perception of reality.

Contribution

IFT introduces a novel perspective on consciousness emphasizing information flow, applicable to biological and artificial systems, and predicts new phenomena in AI and superintelligence.

Findings

IFT predicts new forms of artificial consciousness.

IFT suggests information flow direction is key to consciousness.

Implications for AI development and understanding of reality.

Abstract

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.