Information Flow Theory (IFT): A General Theory of Biologic and Artificial Consciousness

23 Pages Posted: 17 Jul 2019 Last revised: 8 Nov 2019

See all articles by Benjamin Bleier

Benjamin Bleier

Harvard Medical School, Massachusetts Eye and Ear

Date Written: May 30, 2019

Abstract

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 non-human 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 explains how basic evolutionary processes produce the perception of consciousness and offers multiple experimental avenues to confirm its validity. The neural correlates of the information circuits predicted by IFT exist in humans and are theoretically identifiable in non-human biologic nervous systems. Perhaps most importantly, IFT disentangles artificial intelligence from artificial consciousness and predicts a specific architecture which may be used to create consciousness within neural networks.

Keywords: Consciousness, Self-Awareness, Artificial General Intelligence, Technologic Singularity, Computation, Information Processing

Suggested Citation

Bleier, Benjamin, Information Flow Theory (IFT): A General Theory of Biologic and Artificial Consciousness (May 30, 2019). Available at SSRN: https://ssrn.com/abstract=3420960 or http://dx.doi.org/10.2139/ssrn.3420960

Benjamin Bleier (Contact Author)

Harvard Medical School, Massachusetts Eye and Ear ( email )

243 Charles St
Boston, MA USA 02114
United States

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