A Theoretical Computer Science Perspective on Consciousness

Abstract

The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. This paper studies consciousness from the perspective of theoretical computer science. It formalizes the Global Workspace Theory (GWT) originated by the cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, and others. Our major contribution lies in the precise formal definition of a Conscious Turing Machine (CTM), also called a Conscious AI. We define the CTM in the spirit of Alan Turing’s simple yet powerful definition of a computer, the Turing Machine (TM). We are not looking for a complex model of the brain nor of cognition but for a simple model of (the admittedly complex concept of) consciousness. After formally defining CTM, we give a formal definition of consciousness in CTM. We later suggest why the CTM has the feeling of consciousness. The reasonableness of the definitions and explanations can be judged by how well they agree with commonly accepted intuitive concepts of human consciousness, the range of related concepts that the model explains easily and naturally, and the extent of its agreement with scientific evidence.

A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine

“…This paper presents an overview of the CTM model; we refer the reader to refs. 48 and 49 for additional details. Whereas ref.…”

“…Whereas ref. 48 explores explanations for the feelings of pain and pleasure in the CTM, this paper presents additional phenomena generally associated with consciousness. We start (in section 4 ) with three examples related to vision (blindsight, inattentional blindness, and change blindness) and then, follow with a discussion of dreams and free will.…”

“…We note that the size of the chunk (and hence, the size of its components, including its gist) will necessarily be bounded by computational complexity considerations (section 2.4 and ref. 48 have more specifics).…”

“…This puts bounds on both the amount of computation that can be performed in a node and on the size of the chunk in that node (section 2.4 and ref. 48 have more specifics).…”

AI4R2R (AI for Rock to Revenue): A Review of the Applications of AI in Mineral Processing

“…What if there is no mathematical framework to capture intelligence? The machine to implement AI need not be a Turing machine [28]. With this extremely short historical summary of the domain of AI, I note that AI is the super-set of all the pertinent endeavours.…”