A Theory of Consciousness from a Theoretical Computer Science Perspective: Insights from the Conscious Turing Machine

TL;DR

This paper introduces the Conscious Turing Machine, a formal computational model inspired by the Global Workspace Theory, to analyze consciousness through the lens of theoretical computer science, complexity, and machine learning.

Contribution

It formalizes a simple computational model of consciousness using TCS principles, bridging neuroscience and computation with a novel mathematical framework.

Findings

Model explains feelings of consciousness and related phenomena

Analyzes visual phenomena like blindsight and change blindness

Discusses implications for dreams, free will, and altered states

Abstract

The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. We examine consciousness from the perspective of theoretical computer science (TCS), a branch of mathematics concerned with understanding the underlying principles of computation and complexity, including the implications and surprising consequences of resource limitations. In the spirit of Alan Turing's simple yet powerful definition of a computer, the Turing Machine (TM), and perspective of computational complexity theory, we formalize a modified version of the Global Workspace Theory (GWT) of consciousness originated by cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, Jean-Pierre Changeaux and others. We are not looking for a complex model of the brain nor of cognition, but for a simple computational model of (the admittedly complex concept of) consciousness. We do this by defining the Conscious Turing Machine (CTM), also called a conscious AI, and then we define consciousness and related notions in the CTM. While these are only mathematical (TCS) definitions, we suggest why the CTM has the feeling of consciousness. The TCS perspective provides a simple formal framework to employ tools from computational complexity theory and machine learning to help us understand consciousness and related concepts. Previously we explored high level explanations for the feelings of pain and pleasure in the CTM. Here we consider three examples related to vision (blindsight, inattentional blindness, and change blindness), followed by discussions of dreams, free will, and altered states of consciousness.