On 'Machine Consciousness'

Consciousness in higher animals operates with a 100-millisecond time constant, making it a simplified version of more complex cognitive systems found in processes like wound healing or immune function. These complex systems arose through evolutionary exaptation of information crosstalk between cognitive modules. Because consciousness is stripped-down, building a fast, single-workspace conscious machine that mimics the human neuronal global workspace is feasible. Tied to a backbrain AI that learns hyperrapid pattern responses, such a machine would be elementary and emotional. A more advanced design could use high-speed electronics to create multiple-workspace systems less prone to inattentional blindness. The ultimate utility of such machines remains unclear.

Study at a glance

Abstract

Consciousness in higher animals, by virtue of its 100 millisecond time constant, is a necessarily greatly simplified and stripped-down version of more complex multiple tunable workspace cognition/regulation dyads like wound healing, immune function, gene expression, institutional function and the like. These more complex dynamic entities emerged through evolutionary exaptation of the inevitable information crosstalk between coresident cognitive modules. In consequence of the debrided nature of consciousness, it should not be difficult to construct a fast, single workspace `conscious machine' that mimics the human tunable neuronal global workspace system. Tied to a 'backbrain' AI that has learned hyperrapid stereotypic pattern responses to some particular set of likely challenges, the result is an elementary 'emotional' conscious machine. A clever designer, however, may want to use available high-speed electronics to mimic the more capable multiple-workspace/workforce systems inherently less susceptible to inattentional blindness and related failings of overfocus and thrashing. Contrary to current social constructions, however, the ultimate utility of such machines remains obscure. Here, we explore these matters in formal detail, restricting argument to the asymptotic limit theorems of information and control theories.