CNL-TN-2025-024 Technical Note

Scale-Integrated Consciousness and the Cognitive Prosthesis

Published: December 28, 2025 Version: 1

Abstract

Recent theoretical work by Milinkovic and Aru (2026) argues that biological consciousness depends on computational properties absent from digital systems: scale-inseparable processing across organizational levels and hybrid discrete-continuous dynamics embedded in metabolically constrained substrates. This technical note extends their framework by examining how environmental sensing systems and AI collaboration might extend, rather than replicate, biological conscious processing. Drawing on thirty-six years of field station research and the ongoing development of the Macroscope environmental intelligence platform, we propose that the naturalist's mode of cognition—simultaneous multi-scale apprehension of ecological pattern—exemplifies the scale-integrated processing Milinkovic and Aru identify as essential to consciousness. We further argue that properly designed environmental sensing systems can function as genuine extensions of this biological cognitive mode, providing sensory reach across geographic distance while preserving the continuous, substrate-embedded character of conscious experience. Finally, we examine how AI systems contextualized by shared environmental data streams can participate in cognitive mutualism with human researchers, not as independent conscious entities, but as components continuous with biological consciousness through shared environmental embedding. This framework has implications for environmental intelligence system design, human-AI collaboration, and the broader question of how consciousness relates to its technological extensions.

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AI Collaboration Disclosure

Claude (Anthropic ) — Analysis

This technical note was developed collaboratively with Claude (Anthropic, Opus 4.5) during a morning discussion session. The AI contributed to theoretical synthesis, literature integration, structural organization, and manuscript drafting. The conceptual framework emerged through dialogue, with the author providing domain expertise, experiential grounding, and editorial direction. The author takes full responsibility for the content, accuracy, and conclusions.

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Cite This Document

(2025). "Scale-Integrated Consciousness and the Cognitive Prosthesis." Canemah Nature Laboratory Technical Note CNL-TN-2025-024. https://canemah.org/archive/CNL-TN-2025-024

BibTeX

@techreport{cnl2025scaleintegrated, author = {}, title = {Scale-Integrated Consciousness and the Cognitive Prosthesis}, institution = {Canemah Nature Laboratory}, year = {2025}, number = {CNL-TN-2025-024}, month = {december}, url = {https://canemah.org/archive/document.php?id=CNL-TN-2025-024}, abstract = {Recent theoretical work by Milinkovic and Aru (2026) argues that biological consciousness depends on computational properties absent from digital systems: scale-inseparable processing across organizational levels and hybrid discrete-continuous dynamics embedded in metabolically constrained substrates. This technical note extends their framework by examining how environmental sensing systems and AI collaboration might extend, rather than replicate, biological conscious processing. Drawing on thirty-six years of field station research and the ongoing development of the Macroscope environmental intelligence platform, we propose that the naturalist's mode of cognition—simultaneous multi-scale apprehension of ecological pattern—exemplifies the scale-integrated processing Milinkovic and Aru identify as essential to consciousness. We further argue that properly designed environmental sensing systems can function as genuine extensions of this biological cognitive mode, providing sensory reach across geographic distance while preserving the continuous, substrate-embedded character of conscious experience. Finally, we examine how AI systems contextualized by shared environmental data streams can participate in cognitive mutualism with human researchers, not as independent conscious entities, but as components continuous with biological consciousness through shared environmental embedding. This framework has implications for environmental intelligence system design, human-AI collaboration, and the broader question of how consciousness relates to its technological extensions.} }

Permanent URL: https://canemah.org/archive/document.php?id=CNL-TN-2025-024