Cognition spaces: natural, artificial, and hybrid

Fuente: arXiv
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Main Authors: Solé, Ricard, Seoane, Luis F, Pla-Mauri, Jordi, Bennett, Michael Timothy, Hochberg, Michael E., Levin, Michael
Format: Preprint
Published: 2026
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author Solé, Ricard
Seoane, Luis F
Pla-Mauri, Jordi
Bennett, Michael Timothy
Hochberg, Michael E.
Levin, Michael
author_facet Solé, Ricard
Seoane, Luis F
Pla-Mauri, Jordi
Bennett, Michael Timothy
Hochberg, Michael E.
Levin, Michael
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2601_12837
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Cognition spaces: natural, artificial, and hybrid
Solé, Ricard
Seoane, Luis F
Pla-Mauri, Jordi
Bennett, Michael Timothy
Hochberg, Michael E.
Levin, Michael
Neurons and Cognition
Artificial Intelligence
Human-Computer Interaction
Neural and Evolutionary Computing
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.
title Cognition spaces: natural, artificial, and hybrid
topic Neurons and Cognition
Artificial Intelligence
Human-Computer Interaction
Neural and Evolutionary Computing
url https://arxiv.org/abs/2601.12837