Cognition spaces: natural, artificial, and hybrid
🤖 AI Summary
This study addresses the absence of a unified framework for systematically comparing the characteristics and potentials of natural, artificial, and hybrid cognitive systems. It proposes a “cognitive space” approach that represents diverse systems—ranging from those without nervous systems to biological and human-machine hybrids—along continuous dimensions of perceptual, processing, and responsive capabilities, thereby moving beyond traditional carrier-centric definitions. Through conceptual modeling and cross-system comparison, the research reveals that existing cognitive systems cluster in specific regions of this space, leaving vast areas unoccupied. This distribution reflects constraints imposed by evolutionary trajectories, physical laws, and prevailing design paradigms. The framework not only clarifies the limitations of current cognitive architectures but also delineates viable pathways for exploring novel forms of cognition that transcend biological evolution.
Application Category
📝 Abstract
Cognitive processes are realized across an extraordinary range of natural, artificial, and hybrid systems, yet there is no unified framework for comparing their forms, limits, and unrealized possibilities. Here, we propose a cognition space approach that replaces narrow, substrate-dependent definitions with a comparative representation based on organizational and informational dimensions. Within this framework, cognition is treated as a graded capacity to sense, process, and act upon information, allowing systems as diverse as cells, brains, artificial agents, and human-AI collectives to be analyzed within a common conceptual landscape. We introduce and examine three cognition spaces -- basal aneural, neural, and human-AI hybrid -- and show that their occupation is highly uneven, with clusters of realized systems separated by large unoccupied regions. We argue that these voids are not accidental but reflect evolutionary contingencies, physical constraints, and design limitations. By focusing on the structure of cognition spaces rather than on categorical definitions, this approach clarifies the diversity of existing cognitive systems and highlights hybrid cognition as a promising frontier for exploring novel forms of complexity beyond those produced by biological evolution.
Problem
Research questions and friction points this paper is trying to address.
cognition space
cognitive systems
hybrid cognition
comparative framework
cognitive diversity
Innovation
Methods, ideas, or system contributions that make the work stand out.
cognition space
hybrid cognition
information processing
comparative framework
graded cognition
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