Is Consciousness a Control Process?

Consciousness may have evolved as a social prediction mechanism for anticipating the intentions of others. Drawing on control theory and cybernetics, the authors argue that evolutionary pressures on interacting agents drive the emergence of consciousness, which enables an agent to predict intentional states of both self and others. This capacity supports cooperative and competitive social behaviors needed to optimize survival in resource-limited environments. The paper discusses core functions of consciousness and outlines architectural specifications for agents that could operationalize these functions, linking neuroscience and artificial intelligence.

Study at a glance

Abstract

Understanding the nature of consciousness has been an outstanding scientific puzzle at the crossroads of neuroscience and artificial intelligence. While brains have long since known to be the bearers of consciousness and machines, that of computation, the history of cybernetics has been full of attempts trying to synthesize consciousness in computational architectures. In recent years, ideas from control theory have proven to be extremely useful for addressing systems-level questions in neuroscience and designing cognitive architectures. Extending these ideas to the study of consciousness, we discuss the core functions of consciousness and control architectural specifications of agents capable of operationalizing these functionalities. We suggest that evolutionary pressures on social dynamics of interacting agents leads to the emergence of consciousness, which is a process for predicting intentional states of other agents (and self) in order to generate social cooperative and competitive behaviors necessary to optimize an agent's survival drives in a world with limited resources.